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{"question":"How to use the sessionstate feature in Streamlit","document_title":"What is serializable session state?","document_link":"https://docs.streamlit.io/knowledge-base/using-streamlit/serializable-session-state#pickle.PicklingError","document_text":"## Serializable Session State\n\nSerialization refers to the process of converting an object or data structure into a format that can be persisted and shared, and allowing you to recover the data’s original structure. Python’s built-in [pickle](https://docs.python.org/3/library/pickle.html) module serializes Python objects to a byte stream (\"pickling\") and deserializes the stream into an object (\"unpickling\").\n\nBy default, Streamlit’s [Session State](https://docs.streamlit.io/library/advanced-features/session-state) allows you to persist any Python object for the duration of the session, irrespective of the object’s pickle-serializability. This property lets you store Python primitives such as integers, floating-point numbers, complex numbers and booleans, dataframes, and even [lambdas](https://docs.python.org/3/reference/expressions.html#lambda) returned by functions. However, some execution environments may require serializing all data in Session State, so it may be useful to detect incompatibility during development, or when the execution environment will stop supporting it in the future.\n\nTo that end, Streamlit provides a `runner.enforceSerializableSessionState` [configuration option](https://docs.streamlit.io/library/advanced-features/configuration) that, when set to `true`, only allows pickle-serializable objects in Session State. To enable the option, either create a global or project config file with the following or use it as a command-line flag:\n\n\n```\n# .streamlit/config.toml\n[runner]\nenforceSerializableSessionState = true\n\n```\nBy \"*pickle-serializable*\", we mean calling `pickle.dumps(obj)` should not raise a [`PicklingError`](https://docs.python.org/3/library/pickle.html#pickle.PicklingError) exception. When the config option is enabled, adding unserializable data to session state should result in an exception. E.g.,\n\n\n```\nimport streamlit as st\n\ndef unserializable_data():\n return lambda x: x\n\n#👇 results in an exception when enforceSerializableSessionState is on\nst.session_state.unserializable = unserializable_data()\n\n```\n![UnserializableSessionStateError](https://docs.streamlit.io/images/unserializable-session-state-error.png)","answer":"erialization refers to the process of converting an object or data structure into a format that can be persisted and shared, and allowing you to recover the data’s original structure.\n\nBy default, Streamlit’s [Session State](https://docs.streamlit.io/library/advanced-features/session-state) allows you to persist any Python object for the duration of the session, irrespective of the object’s pickle-serializability. \n\nStreamlit provides a `runner.enforceSerializableSessionState` [configuration option](https://docs.streamlit.io/library/advanced-features/configuration) that, when set to `true`, only allows pickle-serializable objects in Session State.\n\nBy \"*pickle-serializable*\", we mean calling `pickle.dumps(obj)` should not raise a [`PicklingError`](https://docs.python.org/3/library/pickle.html#pickle.PicklingError) exception","question_idx":2,"row_idx":0,"model":"gpt-3.5-turbo","idx":0,"Template":0,"persona":"bot","response":"<EMPTY 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{"question":"How can I create histograms with different bucket colors in Streamlit","document_title":"API reference","document_link":"https://docs.streamlit.io/1.9.0/library/api-reference/charts/st.plotly_chart#stplotly_chart","document_text":"ader(\"Define a custom colorscale\")\ndf = px.data.iris()\nfig = px.scatter(\n df,\n x=\"sepal_width\",\n y=\"sepal_length\",\n color=\"sepal_length\",\n color_continuous_scale=\"reds\",\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\n```\nNotice how the custom color scale is still reflected in the chart, even when the Streamlit theme is enabled 👇\n\nFor many more examples of Plotly charts with and without the Streamlit theme, check out the [plotly.streamlit.app](https://plotly.streamlit.app).\n\n","answer":"EMPTY 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{"question":"Can I create histograms with different bucket colors in Streamlit","document_title":"API reference","document_link":"https://docs.streamlit.io/1.10.0/library/api-reference/charts/st.plotly_chart#stplotly_chart","document_text":"eader(\"Define a custom colorscale\")\ndf = px.data.iris()\nfig = px.scatter(\n df,\n x=\"sepal_width\",\n y=\"sepal_length\",\n color=\"sepal_length\",\n color_continuous_scale=\"reds\",\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\n```\nNotice how the custom color scale is still reflected in the chart, even when the Streamlit theme is enabled 👇\n\nFor many more examples of Plotly charts with and without the Streamlit theme, check out the [plotly.streamlit.app](https://plotly.streamlit.app).\n\n","answer":"EMPTY 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{"question":"Can I create histograms with different bucket colors in Streamlit","document_title":"API reference","document_link":"https://docs.streamlit.io/1.6.0/library/api-reference/charts/st.plotly_chart#stplotly_chart","document_text":"ader(\"Define a custom colorscale\")\ndf = px.data.iris()\nfig = px.scatter(\n df,\n x=\"sepal_width\",\n y=\"sepal_length\",\n color=\"sepal_length\",\n color_continuous_scale=\"reds\",\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\n```\nNotice how the custom color scale is still reflected in the chart, even when the Streamlit theme is enabled 👇\n\nFor many more examples of Plotly charts with and without the Streamlit theme, check out the [plotly.streamlit.app](https://plotly.streamlit.app).\n\n","answer":"EMPTY 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{"question":"Can I create histograms with different bucket colors in Streamlit","document_title":"API reference","document_link":"https://docs.streamlit.io/1.8.0/library/api-reference/charts/st.plotly_chart#stplotly_chart","document_text":"ader(\"Define a custom colorscale\")\ndf = px.data.iris()\nfig = px.scatter(\n df,\n x=\"sepal_width\",\n y=\"sepal_length\",\n color=\"sepal_length\",\n color_continuous_scale=\"reds\",\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\n```\nNotice how the custom color scale is still reflected in the chart, even when the Streamlit theme is enabled 👇\n\nFor many more examples of Plotly charts with and without the Streamlit theme, check out the [plotly.streamlit.app](https://plotly.streamlit.app).\n\n","answer":"EMPTY MESSAGE","question_idx":0,"row_idx":4,"model":"gpt-3.5-turbo","idx":4,"Template":0,"persona":"bot","response":"```\nhist_values = np.histogram(data[DATE_COLUMN].dt.hour, bins=24, range=(0,24))[0]\nst.bar_chart(hist_values)\n```\n","experiment_id":0,"question_embeddings":[0.06357269,-0.0065760594,-0.020345902,-0.08352584,-0.047350194,0.036682703,0.03675301,-0.020481193,-0.023199504,-0.023003703,-0.08344998,-0.046929147,0.030856805,0.0040366957,0.055860724,-0.027778918,-0.08961629,0.0041082106,-0.090726905,-0.14028054,0.005671198,-0.04953355,-0.056541827,-0.07677412,-0.0054286676,0.046765037,0.028512418,0.05420102,0.068443455,-0.0604626,0.054457724,-0.07275235,0.049726702,-0.022302784,-0.0041490933,-0.02186213,-0.03887204,0.058403235,-0.08978373,0.037947502,0.038772896,0.015465372,-0.031523794,-0.051518813,-0.026647044,0.0863903,-0.07547597,0.013137831,0.012855303,0.022156958,-0.033148255,-0.07180802,0.036730874,0.022195915,0.015626686,-0.029947298,-0.04305715,-0.06709682,0.05954109,-0.08123926,-0.05617996,-0.008180384,0.022568718,-0.0036913706,0.09570576,0.03136336,-0.015436422,0.03444204,0.09311254,-0.02689361,0.03140673,0.06345534,0.08536748,0.048517168,-0.06511003,0.0054839347,-0.012848926,0.05942965,-0.06755942,-0.053685118,-0.027762018,0.008932237,0.040417593,0.022191966,0.011978196,0.054522794,-0.072129376,0.014587649,-0.04637386,0.02310457,-0.06725896,0.06178685,0.024150467,-0.049363486,-0.061521318,0.055563316,0.08960045,-0.01576581,0.057299186,-0.02973093,0.042051695,-0.06689739,0.007888104,-0.022333588,0.08404724,-0.021441972,-0.02634069,0.09471672,0.018893978,-0.03912352,0.0329555,-0.03708901,0.03689426,-0.09556095,-0.009662683,0.06899001,-0.11976706,0.0066234786,-0.06276309,0.017529482,0.064207785,-0.01157287,-0.040234894,-0.015450808,-0.0153679075,-0.052646134,-0.032788604,-2.7589148e-33,0.03576235,-0.10662839,-0.04067808,0.029993126,0.063296854,0.04668259,-0.012749555,0.005248918,-0.010436894,-0.07561844,-0.011633145,0.05444743,-0.048320852,0.014772509,-0.07199935,-0.014760617,0.021598626,-0.017174078,-0.05955723,-0.03472137,-0.07610088,-0.048029725,0.038275547,-0.024732482,0.02252993,-0.014710533,0.053196922,-0.01815156,0.046866003,0.038138613,0.023503724,0.07431182,-0.010030737,0.018859217,0.054400813,-0.051315624,-0.05778552,0.052278083,-0.04012966,0.07762834,0.07195341,0.011121125,-0.05060351,0.012136496,-0.07420707,0.04311224,0.07492402,-0.04081308,-0.018771872,-0.033988312,0.045980997,0.08672062,-0.005062198,-0.025109446,0.12977187,-0.016560083,0.029968856,0.042827725,0.067344815,0.04638003,-0.035595536,0.14303884,0.032466277,0.02497015,0.050941344,-0.024447702,0.10157372,0.0778076,0.00053819915,-0.031346135,-0.008758584,0.036722686,-0.0015840823,-0.020259231,-0.015971852,-0.04298156,0.07306846,0.022992812,-0.034721397,-0.030194966,-0.014201621,-0.043520536,0.010887479,0.03231367,-0.087124325,0.027420446,0.06266317,0.027834242,-0.12047557,-0.087669924,-0.020153027,0.031243222,0.027246276,-0.10769241,-0.0072499076,9.307464e-34,-0.080400184,0.08192685,-0.04577184,0.078311056,0.0642137,0.012169457,0.13736194,0.022015871,0.03278156,0.05398484,-0.035939127,-0.0022418867,-0.1290434,0.008012245,-0.017896941,-0.030848654,-0.012321777,0.024660239,-0.06502408,-0.03576453,-0.10739129,0.0059367563,-0.038558144,-0.0053904355,-0.029615968,0.0663225,-0.009698477,0.002204676,0.016577557,0.016558561,0.032411598,0.025009926,-0.023183554,-0.0548188,-0.013516646,-0.11561085,0.06011747,0.0032648896,-0.019577319,0.08061338,0.036386278,-0.06483969,-0.009423049,-0.067994475,-0.0059552514,0.07898494,-0.030586459,0.057788316,-0.011511716,-0.007741939,-0.02863135,0.03207052,-0.025858352,0.076669626,0.07364335,-0.0601048,0.078869574,0.049763173,0.0026653612,0.007474002,-0.052608352,-0.10268198,0.102147534,-0.019444479,0.051910717,-0.002900365,0.015770577,-0.067796655,-0.029883914,0.022909926,0.009268357,-0.121122375,0.067859925,-0.059911028,0.045639582,-0.009814225,0.014831371,0.059833657,-0.014894034,-0.0022807359,-0.027649293,-0.014831903,0.052625373,0.056469955,0.07557365,0.0031232166,-0.011547768,-0.05443782,0.06120629,0.07160346,0.032031905,0.059437387,-0.012607803,0.04696337,0.07722856,-1.6495452e-8,0.014486489,-0.048435584,0.003250121,0.028159982,0.031189898,0.0023627344,-0.070192665,0.056730375,0.03496575,0.011610652,0.06183044,-0.027920958,-0.0121314,-0.052380722,-0.020452451,-0.04563529,0.017542096,-0.03620699,0.0011459879,0.041698407,-0.028633622,0.03700075,-0.00061687466,0.021913622,-0.07560133,0.03271757,0.017450893,-0.07702778,0.020872569,-0.06213861,-0.0038546,0.04003318,0.069114655,-0.0065786745,-0.016454224,-0.09361585,-0.16091056,0.058383908,-0.052135747,0.010157994,0.016596014,-0.0043797004,-0.014434132,0.0061570127,0.0016335461,0.02599054,0.034217644,0.056406163,-0.020769285,0.08216932,-0.10429248,0.004765623,0.04851646,-0.022152325,0.04684329,-0.058515728,-0.017122269,-0.064585134,0.008293409,-0.034130603,0.024276521,-0.04850379,-0.00979301,-0.0031762286],"context_embeddings":[0.0701984,-0.0646178,-0.029987486,0.016560853,0.044384476,-0.028462013,0.015448952,0.01953124,-0.013943036,-0.048632134,-0.01622635,0.04575076,-0.08032061,-0.0057709767,0.033814777,-0.077715546,-0.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{"question":"How to use the sessionstate feature in Streamlit","document_title":"Widget updating for every second input when using session state","document_link":"https://docs.streamlit.io/knowledge-base/using-streamlit/widget-updating-session-state#overview","document_text":"# ","answer":"EMPTY MESSAGE","question_idx":2,"row_idx":5,"model":"gpt-3.5-turbo","idx":5,"Template":0,"persona":"bot","response":"\"[theme]\n\n# The preset Streamlit theme that your custom theme inherits from. One of \"light\" or \"dark\".\n# base =\n\n# Primary accent color for interactive elements.\n# primaryColor =\n\n# Background color for the main content area.\n# backgroundColor =\n\n# Background color used for the sidebar and most interactive widgets.\n# secondaryBackgroundColor =\n\n# Color used for almost all text.\n# textColor =\n\n# Font family for all text in the app, except code blocks. 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{"question":"How to use the sessionstate feature in Streamlit","document_title":"Configuration","document_link":"https://docs.streamlit.io/library/advanced-features/configuration#view-all-configuration-options","document_text":"## View all configuration options\n\nAs described in [Command-line options](https://docs.streamlit.io/library/advanced-features/cli), you can\nview all available configuration option using:\n\n\n```\nstreamlit config show\n\n```\nThe command above will print something like this:\n\n\n```\n# Streamlit version: 1.22.0\n\n[global]\n\n# By default, Streamlit checks if the Python watchdog module is available and, if not, prints a warning asking for you to install it. The watchdog module is not required, but highly recommended. It improves Streamlit's ability to detect changes to files in your filesystem.\n# If you'd like to turn off this warning, set this to True.\n# Default: false\ndisableWatchdogWarning = false\n\n# If True, will show a warning when you run a Streamlit-enabled script via \"python my_script.py\".\n# Default: true\nshowWarningOnDirectExecution = true\n\n# DataFrame serialization.\n# Acceptable values: - 'legacy': Serialize DataFrames using Streamlit's custom format. Slow but battle-tested. - 'arrow': Serialize DataFrames using Apache Arrow. Much faster and versatile.\n# Default: \"arrow\"\ndataFrameSerialization = \"arrow\"\n\n\n[logger]\n\n# Level of logging: 'error', 'warning', 'info', or 'debug'.\n# Default: 'info'\nlevel = \"info\"\n\n# String format for logging messages. If logger.datetimeFormat is set, logger messages will default to `%(asctime)s.%(msecs)03d %(message)s`. See [Python's documentation](https://docs.python.org/2.6/library/logging.html#formatter-objects) for available attributes.\n# Default: \"%(asctime)s %(message)s\"\nmessageFormat = \"%(asctime)s %(message)s\"\n\n\n[client]\n\n# Whether to enable st.cache.\n# Default: true\ncaching = true\n\n# If false, makes your Streamlit script not draw to a Streamlit app.\n# Default: true\ndisplayEnabled = true\n\n# Controls whether uncaught app exceptions are displayed in the browser. By default, this is set to True and Streamlit displays app exceptions and associated tracebacks in the browser.\n# If set to False, an exception will result in a generic message being shown in the browser, and exceptions and tracebacks will be printed to the console only.\n# Default: true\nshowErrorDetails = true\n\n# Change the visibility of items in the toolbar, options menu, and settings dialog (top right of the app).\n# Allowed values:\n# \"auto\" : Show the developer options if the app is accessed through localhost and hide them otherwise.\n# \"developer\" : Show the developer options.\n# \"viewer\" : Hide the developer options.\n# \"minimal\" : Show only options set externally (e.g. through Streamlit Community Cloud) or through st.set_page_config. If there are no options left, hide the menu.\n# Default: \"auto\"\ntoolbarMode = \"auto\"\n\n\n[runner]\n\n# Allows you to type a variable or string by itself in a single line of Python code to write it to the app.\n# Default: true\nmagicEnabled = true\n\n# Install a Python tracer to allow you to stop or pause your script at any point and introspect it. As a side-effect, this slows down your script's execution.\n# Default: false\ninstallTracer = false\n\n# Sets the MPLBACKEND environment variable to Agg inside Streamlit to prevent Python crashing.\n# Default: true\nfixMatplotlib = true\n\n# Run the Python Garbage Collector after each script execution. This can help avoid excess memory use in Streamlit apps, but could introduce delay in rerunning the app script for high-memory-use applications.\n# Default: true\npostScriptGC = true\n\n# Handle script rerun requests immediately, rather than waiting for script execution to reach a yield point. This makes Streamlit much more responsive to user interaction, but it can lead to race conditions in apps that mutate session_state data outside of explicit session_state assignment statements.\n# Default: true\nfastReruns = true\n\n# Raise an exception after adding unserializable data to Session State. Some execution environments may require serializing all data in Session State, so it may be useful to detect incompatibility during development, or when the execution environment will stop supporting it","answer":"EMPTY MESSAGE","question_idx":2,"row_idx":6,"model":"gpt-3.5-turbo","idx":6,"Template":0,"persona":"bot","response":"<EMPTY 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{"question":"How to use the sessionstate feature in Streamlit","document_title":"Configuration","document_link":"https://docs.streamlit.io/library/advanced-features/configuration#view-all-configuration-options","document_text":" in the future.\n# Default: false\nenforceSerializableSessionState = false\n\n[server]\n\n# List of folders that should not be watched for changes. This impacts both \"Run on Save\" and @st.cache.\n# Relative paths will be taken as relative to the current working directory.\n# Example: ['/home/user1/env', 'relative/path/to/folder']\n# Default: []\nfolderWatchBlacklist = []\n\n# Change the type of file watcher used by Streamlit, or turn it off completely.\n# Allowed values: * \"auto\" : Streamlit will attempt to use the watchdog module, and falls back to polling if watchdog is not available. * \"watchdog\" : Force Streamlit to use the watchdog module. * \"poll\" : Force Streamlit to always use polling. * \"none\" : Streamlit will not watch files.\n# Default: \"auto\"\nfileWatcherType = \"auto\"\n\n# Symmetric key used to produce signed cookies. If deploying on multiple replicas, this should be set to the same value across all replicas to ensure they all share the same secret.\n# Default: randomly generated secret key.\ncookieSecret =\n\n# If false, will attempt to open a browser window on start.\n# Default: false unless (1) we are on a Linux box where DISPLAY is unset, or (2) we are running in the Streamlit Atom plugin.\nheadless = false\n\n# Automatically rerun script when the file is modified on disk.\n# Default: false\nrunOnSave = false\n\n# The address where the server will listen for client and browser connections. Use this if you want to bind the server to a specific address. If set, the server will only be accessible from this address, and not from any aliases (like localhost).\n# Default: (unset)\n# address =\n\n# The port where the server will listen for browser connections.\n# Default: 8501\nport = 8501\n\n# The base path for the URL where Streamlit should be served from.\n# Default: \"\"\nbaseUrlPath = \"\"\n\n# Enables support for Cross-Origin Request Sharing (CORS) protection, for added security.\n# Due to conflicts between CORS and XSRF, if `server.enableXsrfProtection` is on and `server.enableCORS` is off at the same time, we will prioritize `server.enableXsrfProtection`.\n# Default: true\nenableCORS = true\n\n# Enables support for Cross-Site Request Forgery (XSRF) protection, for added security.\n# Due to conflicts between CORS and XSRF, if `server.enableXsrfProtection` is on and `server.enableCORS` is off at the same time, we will prioritize `server.enableXsrfProtection`.\n# Default: true\nenableXsrfProtection = true\n\n# Max size, in megabytes, for files uploaded with the file_uploader.\n# Default: 200\nmaxUploadSize = 200\n\n# Max size, in megabytes, of messages that can be sent via the WebSocket connection.\n# Default: 200\nmaxMessageSize = 200\n\n# Enables support for websocket compression.\n# Default: false\nenableWebsocketCompression = false\n\n# Enable serving files from a `static` directory in the running app's directory.\n# Default: false\nenableStaticServing = false\n\n# Server certificate file for connecting via HTTPS. Must be set at the same time as \"server.sslKeyFile\".\n# ['DO NOT USE THIS OPTION IN A PRODUCTION ENVIRONMENT. It has not gone through security audits or performance tests. For the production environment, we recommend performing SSL termination by the load balancer or the reverse proxy.']\n# sslCertFile =\n\n# Cryptographic key file for connecting via HTTPS. Must be set at the same time as \"server.sslCertFile\".\n# ['DO NOT USE THIS OPTION IN A PRODUCTION ENVIRONMENT. It has not gone through security audits or performance tests. For the production environment, we recommend performing SSL termination by the load balancer or the reverse proxy.']\n# sslKeyFile =\n\n[browser]\n\n# Internet address where users should point their browsers in order to connect to the app. Can be IP address or DNS name and path.\n# This is used to: - Set the correct URL for CORS and XSRF protection purposes. - Show the URL on the terminal - Open the browser\n# Default: 'localhost'\nserverAddress = \"localhost\"\n\n# Whether to send usage statistics to Streamlit.\n# Default: true\ngatherUsageStats = true\n\n# Port whe","answer":"EMPTY MESSAGE","question_idx":2,"row_idx":7,"model":"gpt-3.5-turbo","idx":7,"Template":0,"persona":"bot","response":"```\ndf = px.data.iris()\nfig = px.scatter(\n df,\n x=\"sepal_width\",\n y=\"sepal_length\",\n color=\"sepal_length\",\n color_continuous_scale=\"reds\",\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n st.plotly_chart(fig, theme=None, use_container_width=True)\n```\n```\nNotice how the custom color scale is still reflected in the chart, even when the Streamlit theme is enabled 👇\n\nFor many more examples of Plotly charts with and without the Streamlit theme, check out the [plotly.streamlit.app](https://plotly.streamlit.app).\n```","experiment_id":0,"question_embeddings":[-0.008069718,0.019030994,-0.04399113,-0.018124266,-0.022838099,0.06364004,0.09799271,0.028880155,-0.027881691,-0.0026304945,-0.093847126,-0.052826203,-0.0495291,0.050359074,0.057861276,-0.081056945,-0.043767277,-0.034344412,0.030334882,-0.054179147,0.081798576,-0.06108611,-0.027220473,0.016159661,0.045966722,0.043755453,0.04657097,-0.04207103,0.0606236,-0.010835065,0.01963093,0.023086326,-0.08611886,-0.09577034,-0.042422198,-0.031213628,-0.02303005,-0.012711064,-0.061771363,-0.032626864,0.04722137,-0.05833356,-0.024581093,-0.014408672,-0.043140084,0.043106694,-0.043605175,0.012564146,-0.0024074847,0.07467294,-0.026442008,0.024675488,0.06863068,0.05543007,-0.036845602,0.021533161,0.03818942,0.07087255,-0.014140007,0.012392753,-0.029511698,-0.03693794,0.0142641105,-0.0068583405,-0.021607645,0.032087505,-0.004642361,-0.00048144456,0.08657255,-0.091415726,-0.0654163,0.040753946,0.04778726,-0.07014419,-0.054056033,-0.13101906,0.0106581375,-0.033824015,-0.015706005,0.036165632,0.06448401,-0.027799198,-0.016320214,-0.030502934,0.044609677,-0.0064864736,-0.023485867,-0.02510403,-0.032146394,0.11691514,-0.093619,0.09026529,-0.04394514,-0.040745012,-0.074140415,0.07941597,-0.058178466,0.10143081,0.00082231086,0.034904383,0.021032574,0.02780719,0.020528773,0.07157437,0.015880924,-0.07901302,0.002658145,0.033562664,0.025330164,-0.0620102,0.00088657654,0.043670274,0.06292877,0.020624137,0.024602726,0.014736394,-0.012740257,0.024506299,-0.01692787,0.03850096,0.05740074,-0.048916616,-0.041654356,-0.016295029,0.06332491,0.007249942,0.1201618,-3.069891e-33,0.038632937,-0.07285959,-0.097846106,0.06889692,0.039875455,0.061407413,0.06816671,-0.021834662,-0.041231632,-0.06655201,-0.02681365,-0.00846934,0.0056336895,0.025145523,-0.07212278,-0.088356264,-0.06571071,0.034034792,0.022489915,-0.057755113,0.041024677,-0.0111023635,0.060905315,-0.03981662,0.025356166,0.003709564,0.039863884,-0.009520236,0.026838858,0.009208849,0.061858226,0.041652687,0.027003404,0.008471059,0.100978374,-0.07413808,0.02455753,-0.019793069,0.016882718,-0.06035224,0.005419944,0.030355176,-0.05040027,0.009402115,-0.09048009,-0.060497977,-0.034752905,0.026658474,-0.031877108,-0.019351725,-0.024361955,0.08411059,-0.051161606,-0.006133748,0.023922987,-0.03208829,-0.034828957,0.09694366,-0.023172703,-0.028460398,-0.02360395,0.011142688,-0.046996046,-0.07437975,-0.024909688,0.03751471,0.051979627,0.02110711,-0.016065998,-0.15068954,-0.0536162,-0.027345277,-0.012201718,0.024762029,-0.0059242416,-0.0022329595,0.042477656,0.07530215,-0.06591605,-0.00408647,0.020814484,-0.032786287,-0.022626853,0.12286805,0.0066859704,-0.022303088,0.002724913,-0.03851183,-0.032818407,-0.057483967,-0.054443043,-0.0041463273,0.16144624,0.007332825,0.054585196,1.2820273e-33,0.022542262,-0.020859636,-0.052710604,0.001758398,0.052588698,0.025964668,0.10388966,0.014702435,0.0043939003,-0.041091733,-0.0074163736,0.035646103,-0.11103489,0.03836938,-0.030325333,0.013828032,0.03198602,0.0045473897,-0.03992809,-0.023974352,-0.0017821189,0.008392904,-0.05047325,0.012730342,0.06085425,-0.056332808,0.07645324,-0.0226349,0.015513832,0.030792732,0.090231426,0.015368832,-0.074278586,0.012956486,0.045075648,-0.013657695,0.091199115,0.010006847,-0.12094287,0.11235369,0.09024848,-0.03860437,-0.07123643,-0.045214918,0.019595131,0.07379895,-0.09251951,0.008591872,-0.13025522,0.061584905,0.007761197,-0.10383422,-0.009915873,-0.025119737,0.009733272,-0.06666904,0.06700916,-0.02102678,-0.04229344,-0.11801866,0.009725576,-0.0668771,0.0069729257,-0.019669157,0.07609675,0.03374921,0.026979292,0.07371696,0.09338998,-0.022135435,0.00040826626,-0.09352545,0.054446653,0.032927696,0.08484965,0.036018204,-0.017780457,-0.044531226,-0.0012620412,0.009875729,-0.04044144,0.020187803,-0.041872904,-0.07363746,0.0780202,0.040785998,0.0111372005,0.07780356,-0.011045198,-0.014636242,-0.057807446,0.051122837,-0.08242229,0.031930815,0.08355099,-1.4805702e-8,-0.051469665,-0.033614144,0.018845683,0.06451867,0.0058652232,0.0007405246,-0.027512264,-0.023120081,-0.024361122,-0.061715182,-0.009631923,-0.035585366,0.14869612,-0.082732216,0.024393944,-0.035837397,-0.00039809948,0.044956114,-0.02445103,0.024959521,0.021514298,-0.026425743,0.0038626466,0.100734875,-0.05428898,0.008292243,0.08542635,0.0042307405,0.014428068,-0.031963438,0.0071916976,0.07829516,0.058305006,-0.007757116,-0.008674596,0.07569885,-0.032974575,0.028838512,-0.023347737,0.023153437,-0.002992033,-0.008270725,0.02424749,-0.02757731,-0.028802924,0.05631192,-0.0530676,0.079994015,0.046310086,0.004630426,-0.021416683,0.05256077,0.008517852,0.07715209,0.018514486,-0.023122005,0.04937923,-0.07301177,0.007907248,-0.09448888,0.02026514,0.03812597,-0.05387038,-0.011038521],"context_embeddings":[-0.027450047,-0.055739854,-0.088104494,0.016431704,0.13177769,-0.025336778,0.021939218,-0.0372217,0.03749185,0.014046368,0.00398038,0.038273536,-0.03862615,0.033957433,-0.04356877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{"question":"How can I create histograms with different bucket colors in Streamlit","document_title":"API reference","document_link":"https://docs.streamlit.io/1.7.0/library/api-reference/charts/st.plotly_chart#stplotly_chart","document_text":"ader(\"Define a custom colorscale\")\ndf = px.data.iris()\nfig = px.scatter(\n df,\n x=\"sepal_width\",\n y=\"sepal_length\",\n color=\"sepal_length\",\n color_continuous_scale=\"reds\",\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\n```\nNotice how the custom color scale is still reflected in the chart, even when the Streamlit theme is enabled 👇\n\nFor many more examples of Plotly charts with and without the Streamlit theme, check out the [plotly.streamlit.app](https://plotly.streamlit.app).\n\n","answer":"EMPTY MESSAGE","question_idx":1,"row_idx":8,"model":"gpt-3.5-turbo","idx":8,"Template":0,"persona":"bot","response":"Function signature:\n```\nst.plotly_chart(figure_or_data, use_container_width=False, sharing=\"streamlit\", **kwargs)\n```\n\nExample usage:\n```\nimport streamlit as st\nimport plotly.figure_factory as ff\nimport numpy as np\n\n# Add histogram data\nx1 = np.random.randn(200) - 2\nx2 = np.random.randn(200)\nx3 = np.random.randn(200) + 2\n\n# Group data together\nhist_data = [x1, x2, x3]\n\ngroup_labels = ['Group 1', 'Group 2', 'Group 3']\n\n# Create distplot with custom bin_size\nfig = ff.create_distplot(\n hist_data, group_labels, bin_size=[.1, .25, .5])\n\n# Plot!\nst.plotly_chart(fig, use_container_width=True)\n```\n\nTheming:\n```\nst.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nst.plotly_chart(fig, theme=None, use_container_width=True)\n```","experiment_id":0,"question_embeddings":[0.088330105,0.011396006,-0.017542858,-0.08434498,-0.047787853,0.03425188,0.048996642,0.0034383428,-0.022393193,-0.023409048,-0.07357438,-0.077896774,0.026116539,-0.00085928355,0.039049085,-0.026642563,-0.097047776,-0.022016235,-0.08539825,-0.17395513,0.010976068,-0.05704131,-0.03725233,-0.06842565,-0.0044478704,0.0649463,0.031023948,0.040923957,0.07282005,-0.049106944,0.059667658,-0.0753585,0.062485617,-0.02494093,-0.007864315,-0.019300802,-0.036084615,0.051608577,-0.09109866,0.033572853,0.042465758,0.01174127,-0.019712325,-0.065684274,-0.017155608,0.08364792,-0.073342375,0.01874716,0.037283268,0.025831383,-0.043462474,-0.073857106,0.029871376,0.017697562,0.009775645,-0.036767107,-0.04120292,-0.06703686,0.07610773,-0.10925221,-0.04442994,-0.0074998676,0.022256946,-0.014896059,0.06088412,0.016017038,-0.012465867,0.049446587,0.08847953,-0.018837655,0.019807337,0.06478816,0.06848112,0.055087257,-0.07049523,-0.020874226,-0.011705072,0.048881352,-0.059627306,-0.05197535,-0.027297586,0.014144446,0.037603576,0.040695284,0.017761882,0.06532191,-0.06894137,0.013939522,-0.04712859,0.024932921,-0.062471792,0.066132456,0.002363949,-0.03655384,-0.052409384,0.07198713,0.09174018,-0.006315629,0.06124142,-0.023097236,0.040439002,-0.07812325,0.016205361,-0.014299262,0.07228006,-0.003125131,-0.02446053,0.09691148,0.025791425,-0.037827283,0.048649594,-0.042109657,0.016840104,-0.086937375,-0.017265989,0.075562194,-0.10699093,0.01211867,-0.06403345,0.018178374,0.061768565,-0.002032798,-0.05675274,-0.010576633,-0.034583665,-0.039890874,-0.029935757,-3.2848764e-33,0.0378979,-0.106998086,-0.040995043,0.04149618,0.065572456,0.039515913,-0.008075179,0.003411869,-0.02091417,-0.05122435,-0.005777524,0.037594054,-0.055417888,0.010974505,-0.08005184,-0.052646156,0.007957076,-0.024725603,-0.06924275,-0.037430324,-0.08051367,-0.023205118,0.052269068,-0.012416274,0.016556906,-0.020465432,0.04609017,-0.027405446,0.037574787,0.03561955,0.03827268,0.08577126,0.0042460887,0.014051184,0.05974666,-0.058780804,-0.048364103,0.040574744,-0.043581553,0.07378104,0.061412837,0.0014289903,-0.052190572,-0.00078052504,-0.057369288,0.04606968,0.06747937,-0.030284451,0.009257126,-0.025518835,0.04138671,0.08106319,0.0042691617,-0.014420229,0.11329392,-0.022430757,0.032329742,0.047505144,0.040817976,0.04313649,-0.024551831,0.15228917,0.034013808,0.01941502,0.06144809,-0.036756065,0.10396538,0.070308425,-0.006481227,-0.03454383,-0.00991815,0.037999697,0.016863624,-0.016421068,-0.025025293,-0.04278919,0.066235885,0.010628494,-0.052254688,-0.03445316,-0.01905931,-0.052874748,0.010571877,0.026651157,-0.089318834,0.03158032,0.05560046,0.031757142,-0.11445971,-0.09785465,-0.027041305,0.025731953,0.03934218,-0.10917421,0.0022965784,9.564032e-34,-0.06313915,0.09419001,-0.04081826,0.07181917,0.066276036,0.0030092914,0.13137865,0.035464074,0.045764312,0.051538132,-0.055806544,-0.0046785898,-0.124816924,0.017279215,-0.015864715,-0.040863328,0.0009500781,0.018876879,-0.05487937,-0.037517846,-0.08503278,0.03304914,-0.034198888,0.002668823,-0.04557246,0.050836373,-0.013927419,-0.005447964,0.017712409,0.019973949,0.027383726,0.037844945,-0.014945877,-0.04143812,-0.01959012,-0.105157845,0.06470922,0.013278265,-0.013803623,0.067147404,0.04178529,-0.0632891,-0.010079848,-0.08619708,-0.008960702,0.096153274,-0.035347067,0.06595369,-0.020878192,-0.016643418,-0.019682482,0.013243405,-0.032486048,0.08356432,0.07674347,-0.06361975,0.080223106,0.03534406,0.0060911328,0.0065864087,-0.060241528,-0.10307839,0.10199058,0.00088820775,0.030220982,-0.0011668602,0.0099102575,-0.060083468,-0.042249147,0.017135648,-0.0036030465,-0.0972523,0.07683787,-0.06330369,0.03142023,-0.0026465172,-0.008431761,0.06634554,-0.0038314487,0.010890359,-0.018100841,-0.015494008,0.036994852,0.060362976,0.057365444,0.003517775,-0.0029040098,-0.0502847,0.050799564,0.07383564,0.023432627,0.055715792,-0.02273529,0.058175955,0.08986104,-1.720074e-8,0.022305466,-0.070501976,-0.016909117,0.014119327,0.055804323,0.02039817,-0.06730445,0.059458356,0.035946358,-0.014027031,0.071772315,-0.022881763,-0.003811465,-0.057003707,-0.018651411,-0.04579891,-0.015629753,-0.020469574,0.013314239,0.035074934,-0.026234025,0.0120668635,0.0072116307,0.01317788,-0.08294273,0.02837273,0.017769746,-0.073891856,0.021844728,-0.05221814,-0.0060682157,0.030079223,0.063992664,-0.02636329,-0.026866086,-0.07240491,-0.15313517,0.049820986,-0.04309975,0.0044540553,0.008091409,0.01155717,-0.011134993,-0.015595453,-0.0044206656,0.031132616,0.021964429,0.08499096,-0.029608035,0.09432952,-0.10045928,-0.0016386824,0.045343123,-0.027784642,0.04225195,-0.077244245,-0.025754198,-0.062053796,0.017611738,-0.031203467,0.01756977,-0.025270505,-0.02455264,0.0032717404],"context_embeddings":[0.07019842,-0.06461782,-0.029987501,0.016560858,0.044384483,-0.028462037,0.0154489735,0.01953127,-0.013943043,-0.048632137,-0.01622638,0.04575075,-0.08032064,-0.0057710116,0.03381475,-0.07771555,-0.05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{"question":"How can I create histograms with different bucket colors in Streamlit","document_title":"API reference","document_link":"https://docs.streamlit.io/1.5.0/library/api-reference/charts/st.plotly_chart#stplotly_chart","document_text":"ader(\"Define a custom colorscale\")\ndf = px.data.iris()\nfig = px.scatter(\n df,\n x=\"sepal_width\",\n y=\"sepal_length\",\n color=\"sepal_length\",\n color_continuous_scale=\"reds\",\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\n```\nNotice how the custom color scale is still reflected in the chart, even when the Streamlit theme is enabled 👇\n\nFor many more examples of Plotly charts with and without the Streamlit theme, check out the [plotly.streamlit.app](https://plotly.streamlit.app).\n\n","answer":"EMPTY MESSAGE","question_idx":1,"row_idx":9,"model":"gpt-3.5-turbo","idx":9,"Template":0,"persona":"bot","response":"* Session State is not persisted. If the Streamlit server crashes, then everything stored in Session State gets wiped\n* For caveats and limitations with the Session State API, please see the [API limitations](https://docs.streamlit.io/library/api-reference/session-state#caveats-and-limitations).","experiment_id":0,"question_embeddings":[0.088330105,0.011396006,-0.017542858,-0.08434498,-0.047787853,0.03425188,0.048996642,0.0034383428,-0.022393193,-0.023409048,-0.07357438,-0.077896774,0.026116539,-0.00085928355,0.039049085,-0.026642563,-0.097047776,-0.022016235,-0.08539825,-0.17395513,0.010976068,-0.05704131,-0.03725233,-0.06842565,-0.0044478704,0.0649463,0.031023948,0.040923957,0.07282005,-0.049106944,0.059667658,-0.0753585,0.062485617,-0.02494093,-0.007864315,-0.019300802,-0.036084615,0.051608577,-0.09109866,0.033572853,0.042465758,0.01174127,-0.019712325,-0.065684274,-0.017155608,0.08364792,-0.073342375,0.01874716,0.037283268,0.025831383,-0.043462474,-0.073857106,0.029871376,0.017697562,0.009775645,-0.036767107,-0.04120292,-0.06703686,0.07610773,-0.10925221,-0.04442994,-0.0074998676,0.022256946,-0.014896059,0.06088412,0.016017038,-0.012465867,0.049446587,0.08847953,-0.018837655,0.019807337,0.06478816,0.06848112,0.055087257,-0.07049523,-0.020874226,-0.011705072,0.048881352,-0.059627306,-0.05197535,-0.027297586,0.014144446,0.037603576,0.040695284,0.017761882,0.06532191,-0.06894137,0.013939522,-0.04712859,0.024932921,-0.062471792,0.066132456,0.002363949,-0.03655384,-0.052409384,0.07198713,0.09174018,-0.006315629,0.06124142,-0.023097236,0.040439002,-0.07812325,0.016205361,-0.014299262,0.07228006,-0.003125131,-0.02446053,0.09691148,0.025791425,-0.037827283,0.048649594,-0.042109657,0.016840104,-0.086937375,-0.017265989,0.075562194,-0.10699093,0.01211867,-0.06403345,0.018178374,0.061768565,-0.002032798,-0.05675274,-0.010576633,-0.034583665,-0.039890874,-0.029935757,-3.2848764e-33,0.0378979,-0.106998086,-0.040995043,0.04149618,0.065572456,0.039515913,-0.008075179,0.003411869,-0.02091417,-0.05122435,-0.005777524,0.037594054,-0.055417888,0.010974505,-0.08005184,-0.052646156,0.007957076,-0.024725603,-0.06924275,-0.037430324,-0.08051367,-0.023205118,0.052269068,-0.012416274,0.016556906,-0.020465432,0.04609017,-0.027405446,0.037574787,0.03561955,0.03827268,0.08577126,0.0042460887,0.014051184,0.05974666,-0.058780804,-0.048364103,0.040574744,-0.043581553,0.07378104,0.061412837,0.0014289903,-0.052190572,-0.00078052504,-0.057369288,0.04606968,0.06747937,-0.030284451,0.009257126,-0.025518835,0.04138671,0.08106319,0.0042691617,-0.014420229,0.11329392,-0.022430757,0.032329742,0.047505144,0.040817976,0.04313649,-0.024551831,0.15228917,0.034013808,0.01941502,0.06144809,-0.036756065,0.10396538,0.070308425,-0.006481227,-0.03454383,-0.00991815,0.037999697,0.016863624,-0.016421068,-0.025025293,-0.04278919,0.066235885,0.010628494,-0.052254688,-0.03445316,-0.01905931,-0.052874748,0.010571877,0.026651157,-0.089318834,0.03158032,0.05560046,0.031757142,-0.11445971,-0.09785465,-0.027041305,0.025731953,0.03934218,-0.10917421,0.0022965784,9.564032e-34,-0.06313915,0.09419001,-0.04081826,0.07181917,0.066276036,0.0030092914,0.13137865,0.035464074,0.045764312,0.051538132,-0.055806544,-0.0046785898,-0.124816924,0.017279215,-0.015864715,-0.040863328,0.0009500781,0.018876879,-0.05487937,-0.037517846,-0.08503278,0.03304914,-0.034198888,0.002668823,-0.04557246,0.050836373,-0.013927419,-0.005447964,0.017712409,0.019973949,0.027383726,0.037844945,-0.014945877,-0.04143812,-0.01959012,-0.105157845,0.06470922,0.013278265,-0.013803623,0.067147404,0.04178529,-0.0632891,-0.010079848,-0.08619708,-0.008960702,0.096153274,-0.035347067,0.06595369,-0.020878192,-0.016643418,-0.019682482,0.013243405,-0.032486048,0.08356432,0.07674347,-0.06361975,0.080223106,0.03534406,0.0060911328,0.0065864087,-0.060241528,-0.10307839,0.10199058,0.00088820775,0.030220982,-0.0011668602,0.0099102575,-0.060083468,-0.042249147,0.017135648,-0.0036030465,-0.0972523,0.07683787,-0.06330369,0.03142023,-0.0026465172,-0.008431761,0.06634554,-0.0038314487,0.010890359,-0.018100841,-0.015494008,0.036994852,0.060362976,0.057365444,0.003517775,-0.0029040098,-0.0502847,0.050799564,0.07383564,0.023432627,0.055715792,-0.02273529,0.058175955,0.08986104,-1.720074e-8,0.022305466,-0.070501976,-0.016909117,0.014119327,0.055804323,0.02039817,-0.06730445,0.059458356,0.035946358,-0.014027031,0.071772315,-0.022881763,-0.003811465,-0.057003707,-0.018651411,-0.04579891,-0.015629753,-0.020469574,0.013314239,0.035074934,-0.026234025,0.0120668635,0.0072116307,0.01317788,-0.08294273,0.02837273,0.017769746,-0.073891856,0.021844728,-0.05221814,-0.0060682157,0.030079223,0.063992664,-0.02636329,-0.026866086,-0.07240491,-0.15313517,0.049820986,-0.04309975,0.0044540553,0.008091409,0.01155717,-0.011134993,-0.015595453,-0.0044206656,0.031132616,0.021964429,0.08499096,-0.029608035,0.09432952,-0.10045928,-0.0016386824,0.045343123,-0.027784642,0.04225195,-0.077244245,-0.025754198,-0.062053796,0.017611738,-0.031203467,0.01756977,-0.025270505,-0.02455264,0.0032717404],"context_embeddings":[0.07019842,-0.06461782,-0.029987501,0.016560858,0.044384483,-0.028462037,0.0154489735,0.01953127,-0.013943043,-0.048632137,-0.0162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{"question":"How to use the sessionstate feature in Streamlit","document_title":"Add statefulness to apps","document_link":"https://docs.streamlit.io/library/advanced-features/session-state#caveats-and-limitations","document_text":"## Advanced concepts\n\n### Session State and Widget State association\n\nSession State provides the functionality to store variables across reruns. Widget state (i.e. the value of a widget) is also stored in a session.\n\nFor simplicity, we have *unified* this information in one place. i.e. the Session State. This convenience feature makes it super easy to read or write to the widget's state anywhere in the app's code. Session State variables mirror the widget value using the `key` argument.\n\nWe illustrate this with the following example. Let's say we have an app with a slider to represent temperature in Celsius. We can **set** and **get** the value of the temperature widget by using the Session State API, as follows:\n\n\n```\nimport streamlit as st\n\nif \"celsius\" not in st.session_state:\n # set the initial default value of the slider widget\n st.session_state.celsius = 50.0\n\nst.slider(\n \"Temperature in Celsius\",\n min_value=-100.0,\n max_value=100.0,\n key=\"celsius\"\n)\n\n# This will get the value of the slider widget\nst.write(st.session_state.celsius)\n\n```\nThere is a limitation to setting widget values using the Session State API.\n\nThe following example will raise a `StreamlitAPIException` on trying to set the state of `st.button` via the Session State API:\n\n\n```\nimport streamlit as st\n\nif 'my_button' not in st.session_state:\n st.session_state.my_button = True\n # Streamlit will raise an Exception on trying to set the state of button\n\nst.button('Submit', key='my_button')\n\n```\n![state-button-exception](https://docs.streamlit.io/images/state_button_exception.png)### Serializable Session State\n\nSerialization refers to the process of converting an object or data structure into a format that can be persisted and shared, and allowing you to recover the data’s original structure. Python’s built-in [pickle](https://docs.python.org/3/library/pickle.html) module serializes Python objects to a byte stream (\"pickling\") and deserializes the stream into an object (\"unpickling\").\n\nBy default, Streamlit’s [Session State](https://docs.streamlit.io/library/advanced-features/session-state) allows you to persist any Python object for the duration of the session, irrespective of the object’s pickle-serializability. This property lets you store Python primitives such as integers, floating-point numbers, complex numbers and booleans, dataframes, and even [lambdas](https://docs.python.org/3/reference/expressions.html#lambda) returned by functions. However, some execution environments may require serializing all data in Session State, so it may be useful to detect incompatibility during development, or when the execution environment will stop supporting it in the future.\n\nTo that end, Streamlit provides a `runner.enforceSerializableSessionState` [configuration option](https://docs.streamlit.io/library/advanced-features/configuration) that, when set to `true`, only allows pickle-serializable objects in Session State. To enable the option, either create a global or project config file with the following or use it as a command-line flag:\n\n\n```\n# .streamlit/config.toml\n[runner]\nenforceSerializableSessionState = true\n\n```\nBy \"*pickle-serializable*\", we mean calling `pickle.dumps(obj)` should not raise a [`PicklingError`](https://docs.python.org/3/library/pickle.html#pickle.PicklingError) exception. When the config option is enabled, adding unserializable data to session state should result in an exception. E.g.,\n\n\n```\nimport streamlit as st\n\ndef unserializable_data():\n return lambda x: x\n\n#👇 results in an exception when enforceSerializableSessionState is on\nst.session_state.unserializable = unserializable_data()\n\n```\n![UnserializableSessionStateError](https://docs.streamlit.io/images/unserializable-session-state-error.png)### Caveats and limitations\n\nHere are some limitations to keep in mind when using Session State:\n\n* Session State exists for as long as the tab is open and connected to the Streamlit server. As soon as you close the tab, e","answer":"ession State provides the functionality to store variables across reruns. Widget state (i.e. the value of a widget) is also stored in a session. \n\nSession State variables mirror the widget value using the `key` argument.\n\nBy default, Streamlit’s Session State allows you to persist any Python object for the duration of the session, irrespective of the object’s pickle-serializability. \n\nStreamlit provides a `runner.enforceSerializableSessionState` configuration option that, when set to `true`, only allows pickle-serializable objects in Session State.\n\nHere are some limitations to keep in mind when using Session State:\n\n* Session State exists for as long as the tab is open and connected to the Streamlit server","question_idx":2,"row_idx":10,"model":"gpt-3.5-turbo","idx":10,"Template":0,"persona":"bot","response":"Serialization refers to the process of converting an object or data structure into a format that can be persisted and shared, and allowing you to recover the data’s original structure. Python’s built-in [pickle](https://docs.python.org/3/library/pickle.html) module serializes Python objects to a byte stream (\"pickling\") and deserializes the stream into an object (\"unpickling\").\n\nBy default, Streamlit’s [Session State](https://docs.streamlit.io/library/advanced-features/session-state) allows you to persist any Python object for the duration of the session, irrespective of the object’s pickle-serializability. This property lets you store Python primitives such as integers, floating-point numbers, complex numbers and booleans, dataframes, and even [lambdas](https://docs.python.org/3/reference/expressions.html#lambda) returned by functions. However, some execution environments may require serializing all data in Session State, so it may be useful to detect incompatibility during development, or when the execution environment will stop supporting it in the future.\n\nTo that end, Streamlit provides a `runner.enforceSerializableSessionState` [configuration option](https://docs.streamlit.io/library/advanced-features/configuration) that, when set to `true`, only allows pickle-serializable objects in Session State. To enable the option, either create a global or project config file with the following or use it as a command-line flag:\n\n```\n# .streamlit/config.toml\n[runner]\nenforceSerializableSessionState = true\n```\n\nBy \"*pickle-serializable*\", we mean calling `pickle.dumps(obj)` should not raise a [`PicklingError`](https://docs.python.org/3/library/pickle.html#pickle.PicklingError) exception. When the config option is enabled, adding unserializable data to session state should result in an 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{"question":"Can I create histograms with different bucket colors in Streamlit","document_title":"Create an app","document_link":"https://docs.streamlit.io/library/get-started/create-an-app#share-your-app","document_text":"## Let's put it all together\n\nThat's it, you've made it to the end. Here's the complete script for our interactive app.\n\n\n```\nimport streamlit as st\nimport pandas as pd\nimport numpy as np\n\nst.title('Uber pickups in NYC')\n\nDATE_COLUMN = 'date/time'\nDATA_URL = ('https://s3-us-west-2.amazonaws.com/'\n 'streamlit-demo-data/uber-raw-data-sep14.csv.gz')\n\n@st.cache_data\ndef load_data(nrows):\n data = pd.read_csv(DATA_URL, nrows=nrows)\n lowercase = lambda x: str(x).lower()\n data.rename(lowercase, axis='columns', inplace=True)\n data[DATE_COLUMN] = pd.to_datetime(data[DATE_COLUMN])\n return data\n\ndata_load_state = st.text('Loading data...')\ndata = load_data(10000)\ndata_load_state.text(\"Done! (using st.cache_data)\")\n\nif st.checkbox('Show raw data'):\n st.subheader('Raw data')\n st.write(data)\n\nst.subheader('Number of pickups by hour')\nhist_values = np.histogram(data[DATE_COLUMN].dt.hour, bins=24, range=(0,24))[0]\nst.bar_chart(hist_values)\n\n# Some number in the range 0-23\nhour_to_filter = st.slider('hour', 0, 23, 17)\nfiltered_data = data[data[DATE_COLUMN].dt.hour == hour_to_filter]\n\nst.subheader('Map of all pickups at %s:00' % hour_to_filter)\nst.map(filtered_data)\n\n```\n","answer":"``\nst.title('Uber pickups in NYC')\n\n@st.cache_data\ndef load_data(nrows):\n data = pd.read_csv(DATA_URL, nrows=nrows)\n lowercase = lambda x: str(x).lower()\n data.rename(lowercase, axis='columns', inplace=True)\n data[DATE_COLUMN] = pd.to_datetime(data[DATE_COLUMN])\n return data\n\nhist_values = np.histogram(data[DATE_COLUMN].dt.hour, bins=24, range=(0,24))[0]\nst.bar_chart(hist_values)\n\nhour_to_filter = st.slider('hour', 0, 23, 17)\n``","question_idx":0,"row_idx":11,"model":"gpt-3.5-turbo","idx":11,"Template":0,"persona":"bot","response":"```\nimport streamlit as st\nimport plotly.figure_factory as ff\nimport numpy as np\n\n# Add histogram data\nx1 = np.random.randn(200) - 2\nx2 = np.random.randn(200)\nx3 = np.random.randn(200) + 2\n\n# Group data together\nhist_data = [x1, x2, x3]\n\ngroup_labels = ['Group 1', 'Group 2', 'Group 3']\n\n# Create distplot with custom bin_size\nfig = ff.create_distplot(\n hist_data, group_labels, bin_size=[.1, .25, .5])\n\n# Plot!\nst.plotly_chart(fig, use_container_width=True)\n```\n\n```\nPlotly charts are displayed using the Streamlit theme by default. This theme is sleek, user-friendly, and incorporates Streamlit's color palette. The added benefit is that your charts better integrate with the rest of your app's design.\n\nThe Streamlit theme is available from Streamlit 1.16.0 through the `theme=\"streamlit\"` keyword argument. To disable it, and use Plotly's native theme, use `theme=None` instead.\n\nLet's look at an example of charts with the Streamlit theme and the native Plotly theme:\n\n\nimport plotly.express as px\nimport streamlit as st\n\ndf = px.data.gapminder()\n\nfig = px.scatter(\n df.query(\"year==2007\"),\n x=\"gdpPercap\",\n y=\"lifeExp\",\n size=\"pop\",\n color=\"continent\",\n hover_name=\"country\",\n log_x=True,\n size_max=60,\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n # Use the Streamlit theme.\n # This is the default. So you can also omit the theme argument.\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n # Use the native Plotly theme.\n st.plotly_chart(fig, theme=None, use_container_width=True)\n```","experiment_id":0,"question_embeddings":[0.06357269,-0.0065760594,-0.020345902,-0.08352584,-0.047350194,0.036682703,0.03675301,-0.020481193,-0.023199504,-0.023003703,-0.08344998,-0.046929147,0.030856805,0.0040366957,0.055860724,-0.027778918,-0.08961629,0.0041082106,-0.090726905,-0.14028054,0.005671198,-0.04953355,-0.056541827,-0.07677412,-0.0054286676,0.046765037,0.028512418,0.05420102,0.068443455,-0.0604626,0.054457724,-0.07275235,0.049726702,-0.022302784,-0.0041490933,-0.02186213,-0.03887204,0.058403235,-0.08978373,0.037947502,0.038772896,0.015465372,-0.031523794,-0.051518813,-0.026647044,0.0863903,-0.07547597,0.013137831,0.012855303,0.022156958,-0.033148255,-0.07180802,0.036730874,0.022195915,0.015626686,-0.029947298,-0.04305715,-0.06709682,0.05954109,-0.08123926,-0.05617996,-0.008180384,0.022568718,-0.0036913706,0.09570576,0.03136336,-0.015436422,0.03444204,0.09311254,-0.02689361,0.03140673,0.06345534,0.08536748,0.048517168,-0.06511003,0.0054839347,-0.012848926,0.05942965,-0.06755942,-0.053685118,-0.027762018,0.008932237,0.040417593,0.022191966,0.011978196,0.054522794,-0.072129376,0.014587649,-0.04637386,0.02310457,-0.06725896,0.06178685,0.024150467,-0.049363486,-0.061521318,0.055563316,0.08960045,-0.01576581,0.057299186,-0.02973093,0.042051695,-0.06689739,0.007888104,-0.022333588,0.08404724,-0.021441972,-0.02634069,0.09471672,0.018893978,-0.03912352,0.0329555,-0.03708901,0.03689426,-0.09556095,-0.009662683,0.06899001,-0.11976706,0.0066234786,-0.06276309,0.017529482,0.064207785,-0.01157287,-0.040234894,-0.015450808,-0.0153679075,-0.052646134,-0.032788604,-2.7589148e-33,0.03576235,-0.10662839,-0.04067808,0.029993126,0.063296854,0.04668259,-0.012749555,0.005248918,-0.010436894,-0.07561844,-0.011633145,0.05444743,-0.048320852,0.014772509,-0.07199935,-0.014760617,0.021598626,-0.017174078,-0.05955723,-0.03472137,-0.07610088,-0.048029725,0.038275547,-0.024732482,0.02252993,-0.014710533,0.053196922,-0.01815156,0.046866003,0.038138613,0.023503724,0.07431182,-0.010030737,0.018859217,0.054400813,-0.051315624,-0.05778552,0.052278083,-0.04012966,0.07762834,0.07195341,0.011121125,-0.05060351,0.012136496,-0.07420707,0.04311224,0.07492402,-0.04081308,-0.018771872,-0.033988312,0.045980997,0.08672062,-0.005062198,-0.025109446,0.12977187,-0.016560083,0.029968856,0.042827725,0.067344815,0.04638003,-0.035595536,0.14303884,0.032466277,0.02497015,0.050941344,-0.024447702,0.10157372,0.0778076,0.00053819915,-0.031346135,-0.008758584,0.036722686,-0.0015840823,-0.020259231,-0.015971852,-0.04298156,0.07306846,0.022992812,-0.034721397,-0.030194966,-0.014201621,-0.043520536,0.010887479,0.03231367,-0.087124325,0.027420446,0.06266317,0.027834242,-0.12047557,-0.087669924,-0.020153027,0.031243222,0.027246276,-0.10769241,-0.0072499076,9.307464e-34,-0.080400184,0.08192685,-0.04577184,0.078311056,0.0642137,0.012169457,0.13736194,0.022015871,0.03278156,0.05398484,-0.035939127,-0.0022418867,-0.1290434,0.008012245,-0.017896941,-0.030848654,-0.012321777,0.024660239,-0.06502408,-0.03576453,-0.10739129,0.0059367563,-0.038558144,-0.0053904355,-0.029615968,0.0663225,-0.009698477,0.002204676,0.016577557,0.016558561,0.032411598,0.025009926,-0.023183554,-0.0548188,-0.013516646,-0.11561085,0.06011747,0.0032648896,-0.019577319,0.08061338,0.036386278,-0.06483969,-0.009423049,-0.067994475,-0.0059552514,0.07898494,-0.030586459,0.057788316,-0.011511716,-0.007741939,-0.02863135,0.03207052,-0.025858352,0.076669626,0.07364335,-0.0601048,0.078869574,0.049763173,0.0026653612,0.007474002,-0.052608352,-0.10268198,0.102147534,-0.019444479,0.051910717,-0.002900365,0.015770577,-0.067796655,-0.029883914,0.022909926,0.009268357,-0.121122375,0.067859925,-0.059911028,0.045639582,-0.009814225,0.014831371,0.059833657,-0.014894034,-0.0022807359,-0.027649293,-0.014831903,0.052625373,0.056469955,0.07557365,0.0031232166,-0.011547768,-0.05443782,0.06120629,0.07160346,0.032031905,0.059437387,-0.012607803,0.04696337,0.07722856,-1.6495452e-8,0.014486489,-0.048435584,0.003250121,0.028159982,0.031189898,0.0023627344,-0.070192665,0.056730375,0.03496575,0.011610652,0.06183044,-0.027920958,-0.0121314,-0.052380722,-0.020452451,-0.04563529,0.017542096,-0.03620699,0.0011459879,0.041698407,-0.028633622,0.03700075,-0.00061687466,0.021913622,-0.07560133,0.03271757,0.017450893,-0.07702778,0.020872569,-0.06213861,-0.0038546,0.04003318,0.069114655,-0.0065786745,-0.016454224,-0.09361585,-0.16091056,0.058383908,-0.052135747,0.010157994,0.016596014,-0.0043797004,-0.014434132,0.0061570127,0.0016335461,0.02599054,0.034217644,0.056406163,-0.020769285,0.08216932,-0.10429248,0.004765623,0.04851646,-0.022152325,0.04684329,-0.058515728,-0.017122269,-0.064585134,0.008293409,-0.034130603,0.024276521,-0.04850379,-0.00979301,-0.0031762286],"context_embeddings":[0.023324272,-0.0026033735,-0.04369806,0.035365675,-0.0105658695,-0.055870328,-0.045687888,-0.011237764,-0.010941869,0.0036085031,-0.005628347,-0.040258553,-0.060725905,-0.07620291,0.016274776,-0.020856416,-0.047445014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{"question":"Can I create histograms with different bucket colors in Streamlit","document_title":"API reference","document_link":"https://docs.streamlit.io/1.4.0/library/api-reference/charts/st.plotly_chart#stplotly_chart","document_text":"m colorscale\")\ndf = px.data.iris()\nfig = px.scatter(\n df,\n x=\"sepal_width\",\n y=\"sepal_length\",\n color=\"sepal_length\",\n color_continuous_scale=\"reds\",\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\n```\nNotice how the custom color scale is still reflected in the chart, even when the Streamlit theme is enabled 👇\n\nFor many more examples of Plotly charts with and without the Streamlit theme, check out the [plotly.streamlit.app](https://plotly.streamlit.app).\n\n","answer":"``\ndf = px.data.iris()\nfig = px.scatter(\n df,\n x=\"sepal_width\",\n y=\"sepal_length\",\n color=\"sepal_length\",\n color_continuous_scale=\"reds\",\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n st.plotly_chart(fig, theme=None, use_container_width=True)\n``","question_idx":0,"row_idx":12,"model":"gpt-3.5-turbo","idx":12,"Template":0,"persona":"bot","response":"Function signature:\nst.plotly\\_chart(figure\\_or\\_data, use\\_container\\_width=False, sharing=\"streamlit\", \\*\\*kwargs)\n\nParameters:\n- figure\\_or\\_data (plotly.graph\\_objs.Figure, plotly.graph\\_objs.Data, dict/list of plotly.graph\\_objs.Figure/Data): See <https://plot.ly/python/> for examples of graph descriptions.\n- use\\_container\\_width (bool): If True, set the chart width to the column width. This takes precedence over the figure's native width value.\n- sharing ({'streamlit', 'private', 'secret', 'public'}): Use 'streamlit' to insert the plot and all its dependencies directly in the Streamlit app using plotly's offline mode (default). Use any other sharing mode to send the chart to Plotly chart studio, which requires an account. See <https://plotly.com/chart-studio/> for more information.\n\nExample:\n```\nimport streamlit as st\nimport plotly.figure_factory as ff\nimport numpy as np\n\n# Add histogram data\nx1 = np.random.randn(200) - 2\nx2 = np.random.randn(200)\nx3 = np.random.randn(200) + 2\n\n# Group data together\nhist_data = [x1, x2, x3]\n\ngroup_labels = ['Group 1', 'Group 2', 'Group 3']\n\n# Create distplot with custom bin_size\nfig = ff.create_distplot(\n hist_data, group_labels, bin_size=[.1, .25, .5])\n\n# Plot!\nst.plotly_chart(fig, use_container_width=True)\n```\n\nTheming:\nPlotly charts are displayed using the Streamlit theme by default. This theme is sleek, user-friendly, and incorporates Streamlit's color palette. The added benefit is that your charts better integrate with the rest of your app's design. The Streamlit theme is available from Streamlit 1.16.0 through the `theme=\"streamlit\"` keyword argument. To disable it, and use Plotly's native theme, use `theme=None` 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{"question":"Can I create histograms with different bucket colors in Streamlit","document_title":"API reference","document_link":"https://docs.streamlit.io/1.8.0/library/api-reference/charts/st.plotly_chart#stplotly_chart","document_text":"## st.plotly\\_chart\n\nDisplay an interactive Plotly chart.\n\n\nPlotly is a charting library for Python. The arguments to this function\nclosely follow the ones for Plotly's plot() function. You can find\nmore about Plotly at <https://plot.ly/python>.\n\n\nTo show Plotly charts in Streamlit, call st.plotly\\_chart wherever you\nwould call Plotly's py.plot or py.iplot.\n\n\n\n\n| Function signature[[source]](https://github.com/streamlit/streamlit/blob/1.8.0/lib/streamlit/elements/plotly_chart.py#L42 \"View st.plotly_chart source code on GitHub\") |\n| --- |\n| st.plotly\\_chart(figure\\_or\\_data, use\\_container\\_width=False, sharing=\"streamlit\", \\*\\*kwargs) |\n| Parameters |\n| \n\nfigure\\_or\\_data\n(plotly.graph\\_objs.Figure, plotly.graph\\_objs.Data,)\n | \ndict/list of plotly.graph\\_objs.Figure/Data\nSee <https://plot.ly/python/> for examples of graph descriptions.\n |\n| \n\nuse\\_container\\_width\n(bool)\n | \nIf True, set the chart width to the column width. This takes\nprecedence over the figure's native width value.\n |\n| \n\nsharing\n({'streamlit', 'private', 'secret', 'public'})\n | \nUse 'streamlit' to insert the plot and all its dependencies\ndirectly in the Streamlit app using plotly's offline mode (default).\nUse any other sharing mode to send the chart to Plotly chart studio, which\nrequires an account. See <https://plotly.com/chart-studio/> for more information.\n |\n| \n\n\\*\\*kwargs\n(null)\n | \nAny argument accepted by Plotly's plot() function.\n |\n\n#### Example\n\n\n> \n> The example below comes straight from the examples at\n> <https://plot.ly/python>:\n> \n> \n> \n> ```\n> \n> import streamlit as st\n> import plotly.figure_factory as ff\n> import numpy as np\n> \n> # Add histogram data\n> x1 = np.random.randn(200) - 2\n> x2 = np.random.randn(200)\n> x3 = np.random.randn(200) + 2\n> \n> # Group data together\n> hist_data = [x1, x2, x3]\n> \n> group_labels = ['Group 1', 'Group 2', 'Group 3']\n> \n> # Create distplot with custom bin_size\n> fig = ff.create_distplot(\n> hist_data, group_labels, bin_size=[.1, .25, .5])\n> \n> # Plot!\n> st.plotly_chart(fig, use_container_width=True)\n> \n> ```\n> \n> \n> [(view standalone Streamlit app)](https://share.streamlit.io/streamlit/docs/main/python/api-examples-source/charts.plotly_chart.py) \n> \n\n\n### Theming\n\nPlotly charts are displayed using the Streamlit theme by default. This theme is sleek, user-friendly, and incorporates Streamlit's color palette. The added benefit is that your charts better integrate with the rest of your app's design.\n\nThe Streamlit theme is available from Streamlit 1.16.0 through the `theme=\"streamlit\"` keyword argument. To disable it, and use Plotly's native theme, use `theme=None` instead.\n\nLet's look at an example of charts with the Streamlit theme and the native Plotly theme:\n\n\n```\nimport plotly.express as px\nimport streamlit as st\n\ndf = px.data.gapminder()\n\nfig = px.scatter(\n df.query(\"year==2007\"),\n x=\"gdpPercap\",\n y=\"lifeExp\",\n size=\"pop\",\n color=\"continent\",\n hover_name=\"country\",\n log_x=True,\n size_max=60,\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n # Use the Streamlit theme.\n # This is the default. So you can also omit the theme argument.\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n # Use the native Plotly theme.\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\n```\nClick the tabs in the interactive app below to see the charts with the Streamlit theme enabled and disabled.\n\nIf you're wondering if your own customizations will still be taken into account, don't worry! You can still make changes to your chart configurations. In other words, although we now enable the Streamlit theme by default, you can overwrite it with custom colors or fonts. For example, if you want a chart line to be green instead of the default red, you can do it!\n\nHere's an example of an Plotly chart where a custom color scale is defined and reflected:\n\n\n```\nimport plotly.express as px\nimport streamlit as st\n\nst.subhe","answer":"es, you can create histograms with different bucket colors in Streamlit using Plotly. Here's an example:\n\n```\nimport streamlit as st\nimport plotly.figure_factory as ff\nimport numpy as np\n\n# Add histogram data\nx1 = np.random.randn(200) - 2\nx2 = np.random.randn(200)\nx3 = np.random.randn(200) + 2\n\n# Group data together\nhist_data = [x1, x2, x3]\n\ngroup_labels = ['Group 1', 'Group 2', 'Group 3']\n\n# Create distplot with custom bin_size\nfig = ff.create_distplot(\n hist_data, group_labels, bin_size=[.1, .25, .5])\n\n# Plot!\nst.plotly_chart(fig, use_container_width=True)\n\n```\n\nPlotly charts are displayed using the Streamlit theme by default. This theme is sleek, user-friendly, and incorporates Streamlit's color palette. The added benefit is that your charts better integrate with the rest of your app's design","question_idx":0,"row_idx":13,"model":"gpt-3.5-turbo","idx":13,"Template":0,"persona":"bot","response":"Function signature:\n```\nst.plotly_chart(figure_or_data, use_container_width=False, sharing=\"streamlit\", **kwargs)\n```\n\nExample usage:\n```\nimport streamlit as st\nimport plotly.figure_factory as ff\nimport numpy as np\n\n# Add histogram data\nx1 = np.random.randn(200) - 2\nx2 = np.random.randn(200)\nx3 = np.random.randn(200) + 2\n\n# Group data together\nhist_data = [x1, x2, x3]\n\ngroup_labels = ['Group 1', 'Group 2', 'Group 3']\n\n# Create distplot with custom bin_size\nfig = ff.create_distplot(\n hist_data, group_labels, bin_size=[.1, .25, .5])\n\n# Plot!\nst.plotly_chart(fig, use_container_width=True)\n```\n\nTheming:\n```\nPlotly charts are displayed using the Streamlit theme by default. This theme is sleek, user-friendly, and incorporates Streamlit's color palette. The added benefit is that your charts better integrate with the rest of your app's design.\n\nThe Streamlit theme is available from Streamlit 1.16.0 through the `theme=\"streamlit\"` keyword argument. To disable it, and use Plotly's native theme, use `theme=None` instead.\n\nLet's look at an example of charts with the Streamlit theme and the native Plotly theme:\n\nimport plotly.express as px\nimport streamlit as st\n\ndf = px.data.gapminder()\n\nfig = px.scatter(\n df.query(\"year==2007\"),\n x=\"gdpPercap\",\n y=\"lifeExp\",\n size=\"pop\",\n color=\"continent\",\n hover_name=\"country\",\n log_x=True,\n size_max=60,\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n # Use the Streamlit theme.\n # This is the default. So you can also omit the theme argument.\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n # Use the native Plotly theme.\n st.plotly_chart(fig, theme=None, use_container_width=True)\n```","experiment_id":0,"question_embeddings":[0.06357269,-0.0065760594,-0.020345902,-0.08352584,-0.047350194,0.036682703,0.03675301,-0.020481193,-0.023199504,-0.023003703,-0.08344998,-0.046929147,0.030856805,0.0040366957,0.055860724,-0.027778918,-0.08961629,0.0041082106,-0.090726905,-0.14028054,0.005671198,-0.04953355,-0.056541827,-0.07677412,-0.0054286676,0.046765037,0.028512418,0.05420102,0.068443455,-0.0604626,0.054457724,-0.07275235,0.049726702,-0.022302784,-0.0041490933,-0.02186213,-0.03887204,0.058403235,-0.08978373,0.037947502,0.038772896,0.015465372,-0.031523794,-0.051518813,-0.026647044,0.0863903,-0.07547597,0.013137831,0.012855303,0.022156958,-0.033148255,-0.07180802,0.036730874,0.022195915,0.015626686,-0.029947298,-0.04305715,-0.06709682,0.05954109,-0.08123926,-0.05617996,-0.008180384,0.022568718,-0.0036913706,0.09570576,0.03136336,-0.015436422,0.03444204,0.09311254,-0.02689361,0.03140673,0.06345534,0.08536748,0.048517168,-0.06511003,0.0054839347,-0.012848926,0.05942965,-0.06755942,-0.053685118,-0.027762018,0.008932237,0.040417593,0.022191966,0.011978196,0.054522794,-0.072129376,0.014587649,-0.04637386,0.02310457,-0.06725896,0.06178685,0.024150467,-0.049363486,-0.061521318,0.055563316,0.08960045,-0.01576581,0.057299186,-0.02973093,0.042051695,-0.06689739,0.007888104,-0.022333588,0.08404724,-0.021441972,-0.02634069,0.09471672,0.018893978,-0.03912352,0.0329555,-0.03708901,0.03689426,-0.09556095,-0.009662683,0.06899001,-0.11976706,0.0066234786,-0.06276309,0.017529482,0.064207785,-0.01157287,-0.040234894,-0.015450808,-0.0153679075,-0.052646134,-0.032788604,-2.7589148e-33,0.03576235,-0.10662839,-0.04067808,0.029993126,0.063296854,0.04668259,-0.012749555,0.005248918,-0.010436894,-0.07561844,-0.011633145,0.05444743,-0.048320852,0.014772509,-0.07199935,-0.014760617,0.021598626,-0.017174078,-0.05955723,-0.03472137,-0.07610088,-0.048029725,0.038275547,-0.024732482,0.02252993,-0.014710533,0.053196922,-0.01815156,0.046866003,0.038138613,0.023503724,0.07431182,-0.010030737,0.018859217,0.054400813,-0.051315624,-0.05778552,0.052278083,-0.04012966,0.07762834,0.07195341,0.011121125,-0.05060351,0.012136496,-0.07420707,0.04311224,0.07492402,-0.04081308,-0.018771872,-0.033988312,0.045980997,0.08672062,-0.005062198,-0.025109446,0.12977187,-0.016560083,0.029968856,0.042827725,0.067344815,0.04638003,-0.035595536,0.14303884,0.032466277,0.02497015,0.050941344,-0.024447702,0.10157372,0.0778076,0.00053819915,-0.031346135,-0.008758584,0.036722686,-0.0015840823,-0.020259231,-0.015971852,-0.04298156,0.07306846,0.022992812,-0.034721397,-0.030194966,-0.014201621,-0.043520536,0.010887479,0.03231367,-0.087124325,0.027420446,0.06266317,0.027834242,-0.12047557,-0.087669924,-0.020153027,0.031243222,0.027246276,-0.10769241,-0.0072499076,9.307464e-34,-0.080400184,0.08192685,-0.04577184,0.078311056,0.0642137,0.012169457,0.13736194,0.022015871,0.03278156,0.05398484,-0.035939127,-0.0022418867,-0.1290434,0.008012245,-0.017896941,-0.030848654,-0.012321777,0.024660239,-0.06502408,-0.03576453,-0.10739129,0.0059367563,-0.038558144,-0.0053904355,-0.029615968,0.0663225,-0.009698477,0.002204676,0.016577557,0.016558561,0.032411598,0.025009926,-0.023183554,-0.0548188,-0.013516646,-0.11561085,0.06011747,0.0032648896,-0.019577319,0.08061338,0.036386278,-0.06483969,-0.009423049,-0.067994475,-0.0059552514,0.07898494,-0.030586459,0.057788316,-0.011511716,-0.007741939,-0.02863135,0.03207052,-0.025858352,0.076669626,0.07364335,-0.0601048,0.078869574,0.049763173,0.0026653612,0.007474002,-0.052608352,-0.10268198,0.102147534,-0.019444479,0.051910717,-0.002900365,0.015770577,-0.067796655,-0.029883914,0.022909926,0.009268357,-0.121122375,0.067859925,-0.059911028,0.045639582,-0.009814225,0.014831371,0.059833657,-0.014894034,-0.0022807359,-0.027649293,-0.014831903,0.052625373,0.056469955,0.07557365,0.0031232166,-0.011547768,-0.05443782,0.06120629,0.07160346,0.032031905,0.059437387,-0.012607803,0.04696337,0.07722856,-1.6495452e-8,0.014486489,-0.048435584,0.003250121,0.028159982,0.031189898,0.0023627344,-0.070192665,0.056730375,0.03496575,0.011610652,0.06183044,-0.027920958,-0.0121314,-0.052380722,-0.020452451,-0.04563529,0.017542096,-0.03620699,0.0011459879,0.041698407,-0.028633622,0.03700075,-0.00061687466,0.021913622,-0.07560133,0.03271757,0.017450893,-0.07702778,0.020872569,-0.06213861,-0.0038546,0.04003318,0.069114655,-0.0065786745,-0.016454224,-0.09361585,-0.16091056,0.058383908,-0.052135747,0.010157994,0.016596014,-0.0043797004,-0.014434132,0.0061570127,0.0016335461,0.02599054,0.034217644,0.056406163,-0.020769285,0.08216932,-0.10429248,0.004765623,0.04851646,-0.022152325,0.04684329,-0.058515728,-0.017122269,-0.064585134,0.008293409,-0.034130603,0.024276521,-0.04850379,-0.00979301,-0.0031762286],"context_embeddings":[0.016836602,-0.024833752,-0.04874534,0.030244675,0.026997447,-0.037571423,-0.03422766,0.05049981,-0.059796426,-0.09261812,-0.021075118,0.013716684,-0.06988178,-0.008868084,0.020776361,-0.0782737,0.006179299,-0.0760981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{"question":"How can I create histograms with different bucket colors in Streamlit","document_title":"Create an app","document_link":"https://docs.streamlit.io/library/get-started/create-an-app#share-your-app","document_text":"## Let's put it all together\n\nThat's it, you've made it to the end. Here's the complete script for our interactive app.\n\n\n```\nimport streamlit as st\nimport pandas as pd\nimport numpy as np\n\nst.title('Uber pickups in NYC')\n\nDATE_COLUMN = 'date/time'\nDATA_URL = ('https://s3-us-west-2.amazonaws.com/'\n 'streamlit-demo-data/uber-raw-data-sep14.csv.gz')\n\n@st.cache_data\ndef load_data(nrows):\n data = pd.read_csv(DATA_URL, nrows=nrows)\n lowercase = lambda x: str(x).lower()\n data.rename(lowercase, axis='columns', inplace=True)\n data[DATE_COLUMN] = pd.to_datetime(data[DATE_COLUMN])\n return data\n\ndata_load_state = st.text('Loading data...')\ndata = load_data(10000)\ndata_load_state.text(\"Done! (using st.cache_data)\")\n\nif st.checkbox('Show raw data'):\n st.subheader('Raw data')\n st.write(data)\n\nst.subheader('Number of pickups by hour')\nhist_values = np.histogram(data[DATE_COLUMN].dt.hour, bins=24, range=(0,24))[0]\nst.bar_chart(hist_values)\n\n# Some number in the range 0-23\nhour_to_filter = st.slider('hour', 0, 23, 17)\nfiltered_data = data[data[DATE_COLUMN].dt.hour == hour_to_filter]\n\nst.subheader('Map of all pickups at %s:00' % hour_to_filter)\nst.map(filtered_data)\n\n```\n","answer":"``\nst.subheader('Number of pickups by hour')\nhist_values = np.histogram(data[DATE_COLUMN].dt.hour, bins=24, range=(0,24))[0]\nst.bar_chart(hist_values)\n\n# Some number in the range 0-23\nhour_to_filter = st.slider('hour', 0, 23, 17)\nfiltered_data = data[data[DATE_COLUMN].dt.hour == hour_to_filter]\n``","question_idx":1,"row_idx":14,"model":"gpt-3.5-turbo","idx":14,"Template":0,"persona":"bot","response":"<EMPTY 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{"question":"How can I create histograms with different bucket colors in Streamlit","document_title":"API reference","document_link":"https://docs.streamlit.io/1.9.0/library/api-reference/charts/st.plotly_chart#stplotly_chart","document_text":"## st.plotly\\_chart\n\nDisplay an interactive Plotly chart.\n\n\nPlotly is a charting library for Python. The arguments to this function\nclosely follow the ones for Plotly's plot() function. You can find\nmore about Plotly at <https://plot.ly/python>.\n\n\nTo show Plotly charts in Streamlit, call st.plotly\\_chart wherever you\nwould call Plotly's py.plot or py.iplot.\n\n\n\n\n| Function signature[[source]](https://github.com/streamlit/streamlit/blob/1.9.0/lib/streamlit/elements/plotly_chart.py#L42 \"View st.plotly_chart source code on GitHub\") |\n| --- |\n| st.plotly\\_chart(figure\\_or\\_data, use\\_container\\_width=False, sharing=\"streamlit\", \\*\\*kwargs) |\n| Parameters |\n| \n\nfigure\\_or\\_data\n(plotly.graph\\_objs.Figure, plotly.graph\\_objs.Data,)\n | \ndict/list of plotly.graph\\_objs.Figure/Data\nSee <https://plot.ly/python/> for examples of graph descriptions.\n |\n| \n\nuse\\_container\\_width\n(bool)\n | \nIf True, set the chart width to the column width. This takes\nprecedence over the figure's native width value.\n |\n| \n\nsharing\n({'streamlit', 'private', 'secret', 'public'})\n | \nUse 'streamlit' to insert the plot and all its dependencies\ndirectly in the Streamlit app using plotly's offline mode (default).\nUse any other sharing mode to send the chart to Plotly chart studio, which\nrequires an account. See <https://plotly.com/chart-studio/> for more information.\n |\n| \n\n\\*\\*kwargs\n(null)\n | \nAny argument accepted by Plotly's plot() function.\n |\n\n#### Example\n\n\n> \n> The example below comes straight from the examples at\n> <https://plot.ly/python>:\n> \n> \n> \n> ```\n> \n> import streamlit as st\n> import plotly.figure_factory as ff\n> import numpy as np\n> \n> # Add histogram data\n> x1 = np.random.randn(200) - 2\n> x2 = np.random.randn(200)\n> x3 = np.random.randn(200) + 2\n> \n> # Group data together\n> hist_data = [x1, x2, x3]\n> \n> group_labels = ['Group 1', 'Group 2', 'Group 3']\n> \n> # Create distplot with custom bin_size\n> fig = ff.create_distplot(\n> hist_data, group_labels, bin_size=[.1, .25, .5])\n> \n> # Plot!\n> st.plotly_chart(fig, use_container_width=True)\n> \n> ```\n> \n> \n> [(view standalone Streamlit app)](https://share.streamlit.io/streamlit/docs/main/python/api-examples-source/charts.plotly_chart.py) \n> \n\n\n### Theming\n\nPlotly charts are displayed using the Streamlit theme by default. This theme is sleek, user-friendly, and incorporates Streamlit's color palette. The added benefit is that your charts better integrate with the rest of your app's design.\n\nThe Streamlit theme is available from Streamlit 1.16.0 through the `theme=\"streamlit\"` keyword argument. To disable it, and use Plotly's native theme, use `theme=None` instead.\n\nLet's look at an example of charts with the Streamlit theme and the native Plotly theme:\n\n\n```\nimport plotly.express as px\nimport streamlit as st\n\ndf = px.data.gapminder()\n\nfig = px.scatter(\n df.query(\"year==2007\"),\n x=\"gdpPercap\",\n y=\"lifeExp\",\n size=\"pop\",\n color=\"continent\",\n hover_name=\"country\",\n log_x=True,\n size_max=60,\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n # Use the Streamlit theme.\n # This is the default. So you can also omit the theme argument.\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n # Use the native Plotly theme.\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\n```\nClick the tabs in the interactive app below to see the charts with the Streamlit theme enabled and disabled.\n\nIf you're wondering if your own customizations will still be taken into account, don't worry! You can still make changes to your chart configurations. In other words, although we now enable the Streamlit theme by default, you can overwrite it with custom colors or fonts. For example, if you want a chart line to be green instead of the default red, you can do it!\n\nHere's an example of an Plotly chart where a custom color scale is defined and reflected:\n\n\n```\nimport plotly.express as px\nimport streamlit as st\n\nst.subhe","answer":"here is an example in the documentation that creates histograms with different bucket colors:\n> \n> ```\n> \n> import streamlit as st\n> import plotly.figure_factory as ff\n> import numpy as np\n> \n> # Add histogram data\n> x1 = np.random.randn(200) - 2\n> x2 = np.random.randn(200)\n> x3 = np.random.randn(200) + 2\n> \n> # Group data together\n> hist_data = [x1, x2, x3]\n> \n> group_labels = ['Group 1', 'Group 2', 'Group 3']\n> \n> # Create distplot with custom bin_size\n> fig = ff.create_distplot(\n> hist_data, group_labels, bin_size=[.1, .25, .5])\n> \n> # Plot!\n> st.plotly_chart(fig, use_container_width=True)\n> \n> ```\n> \n> \n","question_idx":1,"row_idx":15,"model":"gpt-3.5-turbo","idx":15,"Template":0,"persona":"bot","response":"| Function signature[[source]](https://github.com/streamlit/streamlit/blob/1.4.0/lib/streamlit/elements/plotly_chart.py#L42 \"View st.plotly_chart source code on GitHub\") |\n| --- |\n| st.plotly\\_chart(figure\\_or\\_data, use\\_container\\_width=False, sharing=\"streamlit\", \\*\\*kwargs) |\n| Parameters |\n| \n\nfigure\\_or\\_data\n(plotly.graph\\_objs.Figure, plotly.graph\\_objs.Data,)\n | \ndict/list of plotly.graph\\_objs.Figure/Data\nSee <https://plot.ly/python/> for examples of graph descriptions.\n |\n| \n\nuse\\_container\\_width\n(bool)\n | \nIf True, set the chart width to the column width. This takes\nprecedence over the figure's native width value.\n |\n| \n\nsharing\n({'streamlit', 'private', 'secret', 'public'})\n | \nUse 'streamlit' to insert the plot and all its dependencies\ndirectly in the Streamlit app using plotly's offline mode (default).\nUse any other sharing mode to send the chart to Plotly chart studio, which\nrequires an account. See <https://plotly.com/chart-studio/> for more information.\n |\n| \n\n\\*\\*kwargs\n(null)\n | \nAny argument accepted by Plotly's plot() function.\n |\n\n> ```\n> \n> import streamlit as st\n> import plotly.figure_factory as ff\n> import numpy as np\n> \n> # Add histogram data\n> x1 = np.random.randn(200) - 2\n> x2 = np.random.randn(200)\n> x3 = np.random.randn(200) + 2\n> \n> # Group data together\n> hist_data = [x1, x2, x3]\n> \n> group_labels = ['Group 1', 'Group 2', 'Group 3']\n> \n> # Create distplot with custom bin_size\n> fig = ff.create_distplot(\n> hist_data, group_labels, bin_size=[.1, .25, .5])\n> \n> # Plot!\n> st.plotly_chart(fig, use_container_width=True)\n> \n> ```\n> \n> \n> [(view standalone Streamlit app)](https://static.streamlit.io/0.56.0-xTAd/index.html?id=TuP96xX8JnsoQeUGAPjkGQ) \n\n<EMPTY 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{"question":"How to use the sessionstate feature in Streamlit","document_title":"Configuration","document_link":"https://docs.streamlit.io/library/advanced-features/configuration#view-all-configuration-options","document_text":"re users should point their browsers in order to connect to the app.\n# This is used to: - Set the correct URL for CORS and XSRF protection purposes. - Show the URL on the terminal - Open the browser\n# Default: whatever value is set in server.port.\nserverPort = 8501\n\n\n[mapbox]\n\n# Configure Streamlit to use a custom Mapbox token for elements like st.pydeck_chart and st.map. To get a token for yourself, create an account at https://mapbox.com. It's free (for moderate usage levels)!\n# Default: \"\"\ntoken = \"\"\n\n\n[deprecation]\n\n# Set to false to disable the deprecation warning for the file uploader encoding.\n# Default: true\nshowfileUploaderEncoding = true\n\n# Set to false to disable the deprecation warning for using the global pyplot instance.\n# Default: true\nshowPyplotGlobalUse = true\n\n\n[theme]\n\n# The preset Streamlit theme that your custom theme inherits from. One of \"light\" or \"dark\".\n# base =\n\n# Primary accent color for interactive elements.\n# primaryColor =\n\n# Background color for the main content area.\n# backgroundColor =\n\n# Background color used for the sidebar and most interactive widgets.\n# secondaryBackgroundColor =\n\n# Color used for almost all text.\n# textColor =\n\n# Font family for all text in the app, except code blocks. One of \"sans serif\", \"serif\", or \"monospace\".\n# font =\n\n```\n","answer":"session]\n\n# Enable session state for Streamlit.\n# Warning: this introduces a potential security vulnerability, so use this option with caution and make sure you understand the implications.\n# Default: false\n# enableCORS = true\n<EMPTY MESSAGE","question_idx":2,"row_idx":16,"model":"gpt-3.5-turbo","idx":16,"Template":0,"persona":"bot","response":"Function signature:\nst.plotly\\_chart(figure\\_or\\_data, use\\_container\\_width=False, sharing=\"streamlit\", \\*\\*kwargs)\n\nParameters:\n- figure\\_or\\_data (plotly.graph\\_objs.Figure, plotly.graph\\_objs.Data, dict/list of plotly.graph\\_objs.Figure/Data): See <https://plot.ly/python/> for examples of graph descriptions.\n- use\\_container\\_width (bool): If True, set the chart width to the column width. This takes precedence over the figure's native width value.\n- sharing ({'streamlit', 'private', 'secret', 'public'}): Use 'streamlit' to insert the plot and all its dependencies directly in the Streamlit app using plotly's offline mode (default). Use any other sharing mode to send the chart to Plotly chart studio, which requires an account. See <https://plotly.com/chart-studio/> for more information.\n- \\*\\*kwargs (null): Any argument accepted by Plotly's plot() function.\n\nExample:\n```\nimport streamlit as st\nimport plotly.figure_factory as ff\nimport numpy as np\n\n# Add histogram data\nx1 = np.random.randn(200) - 2\nx2 = np.random.randn(200)\nx3 = np.random.randn(200) + 2\n\n# Group data together\nhist_data = [x1, x2, x3]\n\ngroup_labels = ['Group 1', 'Group 2', 'Group 3']\n\n# Create distplot with custom bin_size\nfig = ff.create_distplot(\n hist_data, group_labels, bin_size=[.1, .25, .5])\n\n# Plot!\nst.plotly_chart(fig, use_container_width=True)\n```\n\nTheming:\nPlotly charts are displayed using the Streamlit theme by default. This theme is sleek, user-friendly, and incorporates Streamlit's color palette. The added benefit is that your charts better integrate with the rest of your app's design. The Streamlit theme is available from Streamlit 1.16.0 through the `theme=\"streamlit\"` keyword argument. To disable it, and use Plotly's native theme, use `theme=None` 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{"question":"How can I create histograms with different bucket colors in Streamlit","document_title":"API reference","document_link":"https://docs.streamlit.io/1.11.0/library/api-reference/charts/st.plotly_chart#stplotly_chart","document_text":"ig = px.scatter(\n df,\n x=\"sepal_width\",\n y=\"sepal_length\",\n color=\"sepal_length\",\n color_continuous_scale=\"reds\",\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\n```\nNotice how the custom color scale is still reflected in the chart, even when the Streamlit theme is enabled 👇\n\nFor many more examples of Plotly charts with and without the Streamlit theme, check out the [plotly.streamlit.app](https://plotly.streamlit.app).\n\n","answer":"g = px.scatter(\n df,\n x=\"sepal_width\",\n y=\"sepal_length\",\n color=\"sepal_length\",\n color_continuous_scale=\"reds\",\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n st.plotly_chart(fig, theme=None, use_container_width=True","question_idx":1,"row_idx":17,"model":"gpt-3.5-turbo","idx":17,"Template":0,"persona":"bot","response":"* [What is Session State?](https://docs.streamlit.io/library/advanced-features/session-state#what-is-state)\n* [How to initialize Session State items?](https://docs.streamlit.io/library/advanced-features/session-state#initialization)\n* [How to read and update Session State items?](https://docs.streamlit.io/library/advanced-features/session-state#reads-and-updates)\n* [How to use callbacks in Session State?](https://docs.streamlit.io/library/advanced-features/session-state#example-2-session-state-and-callbacks)\n* [How to use `args` and `kwargs` in callbacks?](https://docs.streamlit.io/library/advanced-features/session-state#example-3-use-args-and-kwargs-in-callbacks)\n* [How to use callbacks in forms?](https://docs.streamlit.io/library/advanced-features/session-state#example-4-forms-and-callbacks)\n* [How is Session State related to Widget State?](https://docs.streamlit.io/library/advanced-features/session-state#session-state-and-widget-state-association)\n* [Caveats and limitations](https://docs.streamlit.io/library/advanced-features/session-state#caveats-and-limitations)\n* [Overview](https://docs.streamlit.io/library/advanced-features/timezone-handling#working-with-timezones)\n* [How Streamlit handles timezones](https://docs.streamlit.io/library/advanced-features/timezone-handling#how-streamlit-handles-timezones)\n* [`datetime` instance without a timezone (naive)](https://docs.streamlit.io/library/advanced-features/timezone-handling#datetime-instance-without-a-timezone-naive)\n* [`datetime` instance with a timezone](https://docs.streamlit.io/library/advanced-features/timezone-handling#datetime-instance-with-a-timezone)\n* [Widgets are magical and often work how you want. But they can have surprising behavior in some situations. This section provides is a high-level, abstract description of widget behavior, including some common edge-cases.](https://docs.streamlit.io/library/advanced-features/widget-semantics)","experiment_id":0,"question_embeddings":[0.088330105,0.011396006,-0.017542858,-0.08434498,-0.047787853,0.03425188,0.048996642,0.0034383428,-0.022393193,-0.023409048,-0.07357438,-0.077896774,0.026116539,-0.00085928355,0.039049085,-0.026642563,-0.097047776,-0.022016235,-0.08539825,-0.17395513,0.010976068,-0.05704131,-0.03725233,-0.06842565,-0.0044478704,0.0649463,0.031023948,0.040923957,0.07282005,-0.049106944,0.059667658,-0.0753585,0.062485617,-0.02494093,-0.007864315,-0.019300802,-0.036084615,0.051608577,-0.09109866,0.033572853,0.042465758,0.01174127,-0.019712325,-0.065684274,-0.017155608,0.08364792,-0.073342375,0.01874716,0.037283268,0.025831383,-0.043462474,-0.073857106,0.029871376,0.017697562,0.009775645,-0.036767107,-0.04120292,-0.06703686,0.07610773,-0.10925221,-0.04442994,-0.0074998676,0.022256946,-0.014896059,0.06088412,0.016017038,-0.012465867,0.049446587,0.08847953,-0.018837655,0.019807337,0.06478816,0.06848112,0.055087257,-0.07049523,-0.020874226,-0.011705072,0.048881352,-0.059627306,-0.05197535,-0.027297586,0.014144446,0.037603576,0.040695284,0.017761882,0.06532191,-0.06894137,0.013939522,-0.04712859,0.024932921,-0.062471792,0.066132456,0.002363949,-0.03655384,-0.052409384,0.07198713,0.09174018,-0.006315629,0.06124142,-0.023097236,0.040439002,-0.07812325,0.016205361,-0.014299262,0.07228006,-0.003125131,-0.02446053,0.09691148,0.025791425,-0.037827283,0.048649594,-0.042109657,0.016840104,-0.086937375,-0.017265989,0.075562194,-0.10699093,0.01211867,-0.06403345,0.018178374,0.061768565,-0.002032798,-0.05675274,-0.010576633,-0.034583665,-0.039890874,-0.029935757,-3.2848764e-33,0.0378979,-0.106998086,-0.040995043,0.04149618,0.065572456,0.039515913,-0.008075179,0.003411869,-0.02091417,-0.05122435,-0.005777524,0.037594054,-0.055417888,0.010974505,-0.08005184,-0.052646156,0.007957076,-0.024725603,-0.06924275,-0.037430324,-0.08051367,-0.023205118,0.052269068,-0.012416274,0.016556906,-0.020465432,0.04609017,-0.027405446,0.037574787,0.03561955,0.03827268,0.08577126,0.0042460887,0.014051184,0.05974666,-0.058780804,-0.048364103,0.040574744,-0.043581553,0.07378104,0.061412837,0.0014289903,-0.052190572,-0.00078052504,-0.057369288,0.04606968,0.06747937,-0.030284451,0.009257126,-0.025518835,0.04138671,0.08106319,0.0042691617,-0.014420229,0.11329392,-0.022430757,0.032329742,0.047505144,0.040817976,0.04313649,-0.024551831,0.15228917,0.034013808,0.01941502,0.06144809,-0.036756065,0.10396538,0.070308425,-0.006481227,-0.03454383,-0.00991815,0.037999697,0.016863624,-0.016421068,-0.025025293,-0.04278919,0.066235885,0.010628494,-0.052254688,-0.03445316,-0.01905931,-0.052874748,0.010571877,0.026651157,-0.089318834,0.03158032,0.05560046,0.031757142,-0.11445971,-0.09785465,-0.027041305,0.025731953,0.03934218,-0.10917421,0.0022965784,9.564032e-34,-0.06313915,0.09419001,-0.04081826,0.07181917,0.066276036,0.0030092914,0.13137865,0.035464074,0.045764312,0.051538132,-0.055806544,-0.0046785898,-0.124816924,0.017279215,-0.015864715,-0.040863328,0.0009500781,0.018876879,-0.05487937,-0.037517846,-0.08503278,0.03304914,-0.034198888,0.002668823,-0.04557246,0.050836373,-0.013927419,-0.005447964,0.017712409,0.019973949,0.027383726,0.037844945,-0.014945877,-0.04143812,-0.01959012,-0.105157845,0.06470922,0.013278265,-0.013803623,0.067147404,0.04178529,-0.0632891,-0.010079848,-0.08619708,-0.008960702,0.096153274,-0.035347067,0.06595369,-0.020878192,-0.016643418,-0.019682482,0.013243405,-0.032486048,0.08356432,0.07674347,-0.06361975,0.080223106,0.03534406,0.0060911328,0.0065864087,-0.060241528,-0.10307839,0.10199058,0.00088820775,0.030220982,-0.0011668602,0.0099102575,-0.060083468,-0.042249147,0.017135648,-0.0036030465,-0.0972523,0.07683787,-0.06330369,0.03142023,-0.0026465172,-0.008431761,0.06634554,-0.0038314487,0.010890359,-0.018100841,-0.015494008,0.036994852,0.060362976,0.057365444,0.003517775,-0.0029040098,-0.0502847,0.050799564,0.07383564,0.023432627,0.055715792,-0.02273529,0.058175955,0.08986104,-1.720074e-8,0.022305466,-0.070501976,-0.016909117,0.014119327,0.055804323,0.02039817,-0.06730445,0.059458356,0.035946358,-0.014027031,0.071772315,-0.022881763,-0.003811465,-0.057003707,-0.018651411,-0.04579891,-0.015629753,-0.020469574,0.013314239,0.035074934,-0.026234025,0.0120668635,0.0072116307,0.01317788,-0.08294273,0.02837273,0.017769746,-0.073891856,0.021844728,-0.05221814,-0.0060682157,0.030079223,0.063992664,-0.02636329,-0.026866086,-0.07240491,-0.15313517,0.049820986,-0.04309975,0.0044540553,0.008091409,0.01155717,-0.011134993,-0.015595453,-0.0044206656,0.031132616,0.021964429,0.08499096,-0.029608035,0.09432952,-0.10045928,-0.0016386824,0.045343123,-0.027784642,0.04225195,-0.077244245,-0.025754198,-0.062053796,0.017611738,-0.031203467,0.01756977,-0.025270505,-0.02455264,0.0032717404],"context_embeddings":[0.10312815,-0.075470366,-0.003319214,0.012652912,0.073125444,-0.013450781,0.009499983,0.0018798977,-0.0067407163,-0.058898125,-0.04201945,0.06186118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{"question":"How to use the sessionstate feature in Streamlit","document_title":"Add statefulness to apps","document_link":"https://docs.streamlit.io/library/advanced-features/session-state#caveats-and-limitations","document_text":"verything stored in Session State is lost.\n* Session State is not persisted. If the Streamlit server crashes, then everything stored in Session State gets wiped\n* For caveats and limitations with the Session State API, please see the [API limitations](https://docs.streamlit.io/library/api-reference/session-state#caveats-and-limitations).\n","answer":" Session State is not persisted. If the Streamlit server crashes, then everything stored in Session State gets wiped\n* For caveats and limitations with the Session State API, please see the [API limitations](https://docs.streamlit.io/library/api-reference/session-state#caveats-and-limitations)","question_idx":2,"row_idx":18,"model":"gpt-3.5-turbo","idx":18,"Template":0,"persona":"bot","response":"2. Use NumPy to generate a histogram that breaks down pickup times binned by\nhour:\n\n\n```\nhist_values = np.histogram(\n data[DATE_COLUMN].dt.hour, bins=24, range=(0,24))[0]\n\n```\n3. Now, let's use Streamlit's\n[`st.bar_chart()`](https://docs.streamlit.io/library/api-reference/charts/st.bar_chart) method to draw this\nhistogram.\n\n\n```\nst.bar_chart(hist_values)\n\n```","experiment_id":0,"question_embeddings":[-0.008069718,0.019030994,-0.04399113,-0.018124266,-0.022838099,0.06364004,0.09799271,0.028880155,-0.027881691,-0.0026304945,-0.093847126,-0.052826203,-0.0495291,0.050359074,0.057861276,-0.081056945,-0.043767277,-0.034344412,0.030334882,-0.054179147,0.081798576,-0.06108611,-0.027220473,0.016159661,0.045966722,0.043755453,0.04657097,-0.04207103,0.0606236,-0.010835065,0.01963093,0.023086326,-0.08611886,-0.09577034,-0.042422198,-0.031213628,-0.02303005,-0.012711064,-0.061771363,-0.032626864,0.04722137,-0.05833356,-0.024581093,-0.014408672,-0.043140084,0.043106694,-0.043605175,0.012564146,-0.0024074847,0.07467294,-0.026442008,0.024675488,0.06863068,0.05543007,-0.036845602,0.021533161,0.03818942,0.07087255,-0.014140007,0.012392753,-0.029511698,-0.03693794,0.0142641105,-0.0068583405,-0.021607645,0.032087505,-0.004642361,-0.00048144456,0.08657255,-0.091415726,-0.0654163,0.040753946,0.04778726,-0.07014419,-0.054056033,-0.13101906,0.0106581375,-0.033824015,-0.015706005,0.036165632,0.06448401,-0.027799198,-0.016320214,-0.030502934,0.044609677,-0.0064864736,-0.023485867,-0.02510403,-0.032146394,0.11691514,-0.093619,0.09026529,-0.04394514,-0.040745012,-0.074140415,0.07941597,-0.058178466,0.10143081,0.00082231086,0.034904383,0.021032574,0.02780719,0.020528773,0.07157437,0.015880924,-0.07901302,0.002658145,0.033562664,0.025330164,-0.0620102,0.00088657654,0.043670274,0.06292877,0.020624137,0.024602726,0.014736394,-0.012740257,0.024506299,-0.01692787,0.03850096,0.05740074,-0.048916616,-0.041654356,-0.016295029,0.06332491,0.007249942,0.1201618,-3.069891e-33,0.038632937,-0.07285959,-0.097846106,0.06889692,0.039875455,0.061407413,0.06816671,-0.021834662,-0.041231632,-0.06655201,-0.02681365,-0.00846934,0.0056336895,0.025145523,-0.07212278,-0.088356264,-0.06571071,0.034034792,0.022489915,-0.057755113,0.041024677,-0.0111023635,0.060905315,-0.03981662,0.025356166,0.003709564,0.039863884,-0.009520236,0.026838858,0.009208849,0.061858226,0.041652687,0.027003404,0.008471059,0.100978374,-0.07413808,0.02455753,-0.019793069,0.016882718,-0.06035224,0.005419944,0.030355176,-0.05040027,0.009402115,-0.09048009,-0.060497977,-0.034752905,0.026658474,-0.031877108,-0.019351725,-0.024361955,0.08411059,-0.051161606,-0.006133748,0.023922987,-0.03208829,-0.034828957,0.09694366,-0.023172703,-0.028460398,-0.02360395,0.011142688,-0.046996046,-0.07437975,-0.024909688,0.03751471,0.051979627,0.02110711,-0.016065998,-0.15068954,-0.0536162,-0.027345277,-0.012201718,0.024762029,-0.0059242416,-0.0022329595,0.042477656,0.07530215,-0.06591605,-0.00408647,0.020814484,-0.032786287,-0.022626853,0.12286805,0.0066859704,-0.022303088,0.002724913,-0.03851183,-0.032818407,-0.057483967,-0.054443043,-0.0041463273,0.16144624,0.007332825,0.054585196,1.2820273e-33,0.022542262,-0.020859636,-0.052710604,0.001758398,0.052588698,0.025964668,0.10388966,0.014702435,0.0043939003,-0.041091733,-0.0074163736,0.035646103,-0.11103489,0.03836938,-0.030325333,0.013828032,0.03198602,0.0045473897,-0.03992809,-0.023974352,-0.0017821189,0.008392904,-0.05047325,0.012730342,0.06085425,-0.056332808,0.07645324,-0.0226349,0.015513832,0.030792732,0.090231426,0.015368832,-0.074278586,0.012956486,0.045075648,-0.013657695,0.091199115,0.010006847,-0.12094287,0.11235369,0.09024848,-0.03860437,-0.07123643,-0.045214918,0.019595131,0.07379895,-0.09251951,0.008591872,-0.13025522,0.061584905,0.007761197,-0.10383422,-0.009915873,-0.025119737,0.009733272,-0.06666904,0.06700916,-0.02102678,-0.04229344,-0.11801866,0.009725576,-0.0668771,0.0069729257,-0.019669157,0.07609675,0.03374921,0.026979292,0.07371696,0.09338998,-0.022135435,0.00040826626,-0.09352545,0.054446653,0.032927696,0.08484965,0.036018204,-0.017780457,-0.044531226,-0.0012620412,0.009875729,-0.04044144,0.020187803,-0.041872904,-0.07363746,0.0780202,0.040785998,0.0111372005,0.07780356,-0.011045198,-0.014636242,-0.057807446,0.051122837,-0.08242229,0.031930815,0.08355099,-1.4805702e-8,-0.051469665,-0.033614144,0.018845683,0.06451867,0.0058652232,0.0007405246,-0.027512264,-0.023120081,-0.024361122,-0.061715182,-0.009631923,-0.035585366,0.14869612,-0.082732216,0.024393944,-0.035837397,-0.00039809948,0.044956114,-0.02445103,0.024959521,0.021514298,-0.026425743,0.0038626466,0.100734875,-0.05428898,0.008292243,0.08542635,0.0042307405,0.014428068,-0.031963438,0.0071916976,0.07829516,0.058305006,-0.007757116,-0.008674596,0.07569885,-0.032974575,0.028838512,-0.023347737,0.023153437,-0.002992033,-0.008270725,0.02424749,-0.02757731,-0.028802924,0.05631192,-0.0530676,0.079994015,0.046310086,0.004630426,-0.021416683,0.05256077,0.008517852,0.07715209,0.018514486,-0.023122005,0.04937923,-0.07301177,0.007907248,-0.09448888,0.02026514,0.03812597,-0.05387038,-0.011038521],"context_embeddings":[-0.0022214153,0.0016528014,-0.026427494,0.017557003,0.026351837,0.02518229,0.031103931,-0.009360115,0.01796459,0.029653855,-0.059408244,0.024138797,-0.046856917,0.006939195,0.027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{"question":"How can I create histograms with different bucket colors in Streamlit","document_title":"API reference","document_link":"https://docs.streamlit.io/1.11.0/library/api-reference/charts/st.plotly_chart#stplotly_chart","document_text":"## st.plotly\\_chart\n\nDisplay an interactive Plotly chart.\n\n\nPlotly is a charting library for Python. The arguments to this function\nclosely follow the ones for Plotly's plot() function. You can find\nmore about Plotly at <https://plot.ly/python>.\n\n\nTo show Plotly charts in Streamlit, call st.plotly\\_chart wherever you\nwould call Plotly's py.plot or py.iplot.\n\n\n\n\n| Function signature[[source]](https://github.com/streamlit/streamlit/blob/1.11.0/lib/streamlit/elements/plotly_chart.py#L67 \"View st.plotly_chart source code on GitHub\") |\n| --- |\n| st.plotly\\_chart(figure\\_or\\_data, use\\_container\\_width=False, sharing=\"streamlit\", \\*\\*kwargs) |\n| Parameters |\n| \n\nfigure\\_or\\_data\n(plotly.graph\\_objs.Figure, plotly.graph\\_objs.Data,)\n | \ndict/list of plotly.graph\\_objs.Figure/Data\nSee <https://plot.ly/python/> for examples of graph descriptions.\n |\n| \n\nuse\\_container\\_width\n(bool)\n | \nIf True, set the chart width to the column width. This takes\nprecedence over the figure's native width value.\n |\n| \n\nsharing\n({'streamlit', 'private', 'secret', 'public'})\n | \nUse 'streamlit' to insert the plot and all its dependencies\ndirectly in the Streamlit app using plotly's offline mode (default).\nUse any other sharing mode to send the chart to Plotly chart studio, which\nrequires an account. See <https://plotly.com/chart-studio/> for more information.\n |\n| \n\n\\*\\*kwargs\n(null)\n | \nAny argument accepted by Plotly's plot() function.\n |\n\n#### Example\n\n\n> \n> The example below comes straight from the examples at\n> <https://plot.ly/python>:\n> \n> \n> \n> ```\n> \n> import streamlit as st\n> import plotly.figure_factory as ff\n> import numpy as np\n> \n> # Add histogram data\n> x1 = np.random.randn(200) - 2\n> x2 = np.random.randn(200)\n> x3 = np.random.randn(200) + 2\n> \n> # Group data together\n> hist_data = [x1, x2, x3]\n> \n> group_labels = ['Group 1', 'Group 2', 'Group 3']\n> \n> # Create distplot with custom bin_size\n> fig = ff.create_distplot(\n> hist_data, group_labels, bin_size=[.1, .25, .5])\n> \n> # Plot!\n> st.plotly_chart(fig, use_container_width=True)\n> \n> ```\n> \n> \n> [(view standalone Streamlit app)](https://doc-plotly-chart.streamlit.app/) \n> \n\n\n### Theming\n\nPlotly charts are displayed using the Streamlit theme by default. This theme is sleek, user-friendly, and incorporates Streamlit's color palette. The added benefit is that your charts better integrate with the rest of your app's design.\n\nThe Streamlit theme is available from Streamlit 1.16.0 through the `theme=\"streamlit\"` keyword argument. To disable it, and use Plotly's native theme, use `theme=None` instead.\n\nLet's look at an example of charts with the Streamlit theme and the native Plotly theme:\n\n\n```\nimport plotly.express as px\nimport streamlit as st\n\ndf = px.data.gapminder()\n\nfig = px.scatter(\n df.query(\"year==2007\"),\n x=\"gdpPercap\",\n y=\"lifeExp\",\n size=\"pop\",\n color=\"continent\",\n hover_name=\"country\",\n log_x=True,\n size_max=60,\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n # Use the Streamlit theme.\n # This is the default. So you can also omit the theme argument.\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n # Use the native Plotly theme.\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\n```\nClick the tabs in the interactive app below to see the charts with the Streamlit theme enabled and disabled.\n\nIf you're wondering if your own customizations will still be taken into account, don't worry! You can still make changes to your chart configurations. In other words, although we now enable the Streamlit theme by default, you can overwrite it with custom colors or fonts. For example, if you want a chart line to be green instead of the default red, you can do it!\n\nHere's an example of an Plotly chart where a custom color scale is defined and reflected:\n\n\n```\nimport plotly.express as px\nimport streamlit as st\n\nst.subheader(\"Define a custom colorscale\")\ndf = px.data.iris()\nf","answer":"Display an interactive Plotly chart.\"\n\n\"Plotly is a charting library for Python.\"\n\n\"The arguments to this function closely follow the ones for Plotly's plot() function.\"\n\n\"import streamlit as st\"\n\n\"The example below comes straight from the examples at <https://plot.ly/python>\"\n\n\"st.plotly_chart(figure\\_or\\_data, use\\_container\\_width=False, sharing=\"streamlit\", \\*\\*kwargs)\"\n\n\"The Streamlit theme is available from Streamlit 1.16.0 through the `theme=\"streamlit\"` keyword argument. To disable it, and use Plotly's native theme, use `theme=None` instead.\"\n\n\"In other words, although we now enable the Streamlit theme by default, you can overwrite it with custom colors or fonts.","question_idx":1,"row_idx":19,"model":"gpt-3.5-turbo","idx":19,"Template":0,"persona":"bot","response":"<EMPTY 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{"question":"How can I create histograms with different bucket colors in Streamlit","document_title":"API reference","document_link":"https://docs.streamlit.io/1.7.0/library/api-reference/charts/st.plotly_chart#stplotly_chart","document_text":"## st.plotly\\_chart\n\nDisplay an interactive Plotly chart.\n\n\nPlotly is a charting library for Python. The arguments to this function\nclosely follow the ones for Plotly's plot() function. You can find\nmore about Plotly at <https://plot.ly/python>.\n\n\nTo show Plotly charts in Streamlit, call st.plotly\\_chart wherever you\nwould call Plotly's py.plot or py.iplot.\n\n\n\n\n| Function signature[[source]](https://github.com/streamlit/streamlit/blob/1.7.0/lib/streamlit/elements/plotly_chart.py#L42 \"View st.plotly_chart source code on GitHub\") |\n| --- |\n| st.plotly\\_chart(figure\\_or\\_data, use\\_container\\_width=False, sharing=\"streamlit\", \\*\\*kwargs) |\n| Parameters |\n| \n\nfigure\\_or\\_data\n(plotly.graph\\_objs.Figure, plotly.graph\\_objs.Data,)\n | \ndict/list of plotly.graph\\_objs.Figure/Data\nSee <https://plot.ly/python/> for examples of graph descriptions.\n |\n| \n\nuse\\_container\\_width\n(bool)\n | \nIf True, set the chart width to the column width. This takes\nprecedence over the figure's native width value.\n |\n| \n\nsharing\n({'streamlit', 'private', 'secret', 'public'})\n | \nUse 'streamlit' to insert the plot and all its dependencies\ndirectly in the Streamlit app using plotly's offline mode (default).\nUse any other sharing mode to send the chart to Plotly chart studio, which\nrequires an account. See <https://plotly.com/chart-studio/> for more information.\n |\n| \n\n\\*\\*kwargs\n(null)\n | \nAny argument accepted by Plotly's plot() function.\n |\n\n#### Example\n\n\n> \n> The example below comes straight from the examples at\n> <https://plot.ly/python>:\n> \n> \n> \n> ```\n> \n> import streamlit as st\n> import plotly.figure_factory as ff\n> import numpy as np\n> \n> # Add histogram data\n> x1 = np.random.randn(200) - 2\n> x2 = np.random.randn(200)\n> x3 = np.random.randn(200) + 2\n> \n> # Group data together\n> hist_data = [x1, x2, x3]\n> \n> group_labels = ['Group 1', 'Group 2', 'Group 3']\n> \n> # Create distplot with custom bin_size\n> fig = ff.create_distplot(\n> hist_data, group_labels, bin_size=[.1, .25, .5])\n> \n> # Plot!\n> st.plotly_chart(fig, use_container_width=True)\n> \n> ```\n> \n> \n> [(view standalone Streamlit app)](https://share.streamlit.io/streamlit/docs/main/python/api-examples-source/charts.plotly_chart.py) \n> \n\n\n### Theming\n\nPlotly charts are displayed using the Streamlit theme by default. This theme is sleek, user-friendly, and incorporates Streamlit's color palette. The added benefit is that your charts better integrate with the rest of your app's design.\n\nThe Streamlit theme is available from Streamlit 1.16.0 through the `theme=\"streamlit\"` keyword argument. To disable it, and use Plotly's native theme, use `theme=None` instead.\n\nLet's look at an example of charts with the Streamlit theme and the native Plotly theme:\n\n\n```\nimport plotly.express as px\nimport streamlit as st\n\ndf = px.data.gapminder()\n\nfig = px.scatter(\n df.query(\"year==2007\"),\n x=\"gdpPercap\",\n y=\"lifeExp\",\n size=\"pop\",\n color=\"continent\",\n hover_name=\"country\",\n log_x=True,\n size_max=60,\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n # Use the Streamlit theme.\n # This is the default. So you can also omit the theme argument.\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n # Use the native Plotly theme.\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\n```\nClick the tabs in the interactive app below to see the charts with the Streamlit theme enabled and disabled.\n\nIf you're wondering if your own customizations will still be taken into account, don't worry! You can still make changes to your chart configurations. In other words, although we now enable the Streamlit theme by default, you can overwrite it with custom colors or fonts. For example, if you want a chart line to be green instead of the default red, you can do it!\n\nHere's an example of an Plotly chart where a custom color scale is defined and reflected:\n\n\n```\nimport plotly.express as px\nimport streamlit as st\n\nst.subhe","answer":"unction signature:\nst.plotly\\_chart(figure\\_or\\_data, use\\_container\\_width=False, sharing=\"streamlit\", \\*\\*kwargs)\n\nParameters:\nfigure\\_or\\_data\n(plotly.graph\\_objs.Figure, plotly.graph\\_objs.Data,)\n | \ndict/list of plotly.graph\\_objs.Figure/Data\nSee <https://plot.ly/python/> for examples of graph descriptions.\n\nuse\\_container\\_width\n(bool)\n | \nIf True, set the chart width to the column width. This takes\nprecedence over the figure's native width value.\n\n\\*\\*kwargs\n(null)\n | \nAny argument accepted by Plotly's plot() function.\n\n#### Example:\n```\n\nimport streamlit as st\nimport plotly.figure_factory as ff\nimport numpy as np\n\n# Add histogram data\nx1 = np.random.randn(200) - 2\nx2 = np.random.randn(200)\nx3 = np.random.randn(200) + 2\n\n# Group data together\nhist_data = [x1, x2, x3]\n\ngroup_labels = ['Group 1', 'Group 2', 'Group 3']\n\n# Create distplot with custom bin_size\nfig = ff.create_distplot(\n hist_data, group_labels, bin_size=[.1, .25, .5])\n\n# Plot!\nst.plotly_chart(fig, use_container_width=True)\n\n```\nTheming:\nPlotly charts are displayed using the Streamlit theme by default. This theme is sleek, user-friendly, and incorporates Streamlit's color palette. The added benefit is that your charts better integrate with the rest of your app's design","question_idx":1,"row_idx":20,"model":"gpt-3.5-turbo","idx":20,"Template":0,"persona":"bot","response":"```\nig = px.scatter(\ndf,\nx=\"sepal_width\",\ny=\"sepal_length\",\ncolor=\"sepal_length\",\ncolor_continuous_scale=\"reds\",\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\nNotice how the custom color scale is still reflected in the chart, even when the Streamlit theme is enabled 👇\n\nFor many more examples of Plotly charts with and without the Streamlit theme, check out the [plotly.streamlit.app](https://plotly.streamlit.app).\n```","experiment_id":0,"question_embeddings":[0.088330105,0.011396006,-0.017542858,-0.08434498,-0.047787853,0.03425188,0.048996642,0.0034383428,-0.022393193,-0.023409048,-0.07357438,-0.077896774,0.026116539,-0.00085928355,0.039049085,-0.026642563,-0.097047776,-0.022016235,-0.08539825,-0.17395513,0.010976068,-0.05704131,-0.03725233,-0.06842565,-0.0044478704,0.0649463,0.031023948,0.040923957,0.07282005,-0.049106944,0.059667658,-0.0753585,0.062485617,-0.02494093,-0.007864315,-0.019300802,-0.036084615,0.051608577,-0.09109866,0.033572853,0.042465758,0.01174127,-0.019712325,-0.065684274,-0.017155608,0.08364792,-0.073342375,0.01874716,0.037283268,0.025831383,-0.043462474,-0.073857106,0.029871376,0.017697562,0.009775645,-0.036767107,-0.04120292,-0.06703686,0.07610773,-0.10925221,-0.04442994,-0.0074998676,0.022256946,-0.014896059,0.06088412,0.016017038,-0.012465867,0.049446587,0.08847953,-0.018837655,0.019807337,0.06478816,0.06848112,0.055087257,-0.07049523,-0.020874226,-0.011705072,0.048881352,-0.059627306,-0.05197535,-0.027297586,0.014144446,0.037603576,0.040695284,0.017761882,0.06532191,-0.06894137,0.013939522,-0.04712859,0.024932921,-0.062471792,0.066132456,0.002363949,-0.03655384,-0.052409384,0.07198713,0.09174018,-0.006315629,0.06124142,-0.023097236,0.040439002,-0.07812325,0.016205361,-0.014299262,0.07228006,-0.003125131,-0.02446053,0.09691148,0.025791425,-0.037827283,0.048649594,-0.042109657,0.016840104,-0.086937375,-0.017265989,0.075562194,-0.10699093,0.01211867,-0.06403345,0.018178374,0.061768565,-0.002032798,-0.05675274,-0.010576633,-0.034583665,-0.039890874,-0.029935757,-3.2848764e-33,0.0378979,-0.106998086,-0.040995043,0.04149618,0.065572456,0.039515913,-0.008075179,0.003411869,-0.02091417,-0.05122435,-0.005777524,0.037594054,-0.055417888,0.010974505,-0.08005184,-0.052646156,0.007957076,-0.024725603,-0.06924275,-0.037430324,-0.08051367,-0.023205118,0.052269068,-0.012416274,0.016556906,-0.020465432,0.04609017,-0.027405446,0.037574787,0.03561955,0.03827268,0.08577126,0.0042460887,0.014051184,0.05974666,-0.058780804,-0.048364103,0.040574744,-0.043581553,0.07378104,0.061412837,0.0014289903,-0.052190572,-0.00078052504,-0.057369288,0.04606968,0.06747937,-0.030284451,0.009257126,-0.025518835,0.04138671,0.08106319,0.0042691617,-0.014420229,0.11329392,-0.022430757,0.032329742,0.047505144,0.040817976,0.04313649,-0.024551831,0.15228917,0.034013808,0.01941502,0.06144809,-0.036756065,0.10396538,0.070308425,-0.006481227,-0.03454383,-0.00991815,0.037999697,0.016863624,-0.016421068,-0.025025293,-0.04278919,0.066235885,0.010628494,-0.052254688,-0.03445316,-0.01905931,-0.052874748,0.010571877,0.026651157,-0.089318834,0.03158032,0.05560046,0.031757142,-0.11445971,-0.09785465,-0.027041305,0.025731953,0.03934218,-0.10917421,0.0022965784,9.564032e-34,-0.06313915,0.09419001,-0.04081826,0.07181917,0.066276036,0.0030092914,0.13137865,0.035464074,0.045764312,0.051538132,-0.055806544,-0.0046785898,-0.124816924,0.017279215,-0.015864715,-0.040863328,0.0009500781,0.018876879,-0.05487937,-0.037517846,-0.08503278,0.03304914,-0.034198888,0.002668823,-0.04557246,0.050836373,-0.013927419,-0.005447964,0.017712409,0.019973949,0.027383726,0.037844945,-0.014945877,-0.04143812,-0.01959012,-0.105157845,0.06470922,0.013278265,-0.013803623,0.067147404,0.04178529,-0.0632891,-0.010079848,-0.08619708,-0.008960702,0.096153274,-0.035347067,0.06595369,-0.020878192,-0.016643418,-0.019682482,0.013243405,-0.032486048,0.08356432,0.07674347,-0.06361975,0.080223106,0.03534406,0.0060911328,0.0065864087,-0.060241528,-0.10307839,0.10199058,0.00088820775,0.030220982,-0.0011668602,0.0099102575,-0.060083468,-0.042249147,0.017135648,-0.0036030465,-0.0972523,0.07683787,-0.06330369,0.03142023,-0.0026465172,-0.008431761,0.06634554,-0.0038314487,0.010890359,-0.018100841,-0.015494008,0.036994852,0.060362976,0.057365444,0.003517775,-0.0029040098,-0.0502847,0.050799564,0.07383564,0.023432627,0.055715792,-0.02273529,0.058175955,0.08986104,-1.720074e-8,0.022305466,-0.070501976,-0.016909117,0.014119327,0.055804323,0.02039817,-0.06730445,0.059458356,0.035946358,-0.014027031,0.071772315,-0.022881763,-0.003811465,-0.057003707,-0.018651411,-0.04579891,-0.015629753,-0.020469574,0.013314239,0.035074934,-0.026234025,0.0120668635,0.0072116307,0.01317788,-0.08294273,0.02837273,0.017769746,-0.073891856,0.021844728,-0.05221814,-0.0060682157,0.030079223,0.063992664,-0.02636329,-0.026866086,-0.07240491,-0.15313517,0.049820986,-0.04309975,0.0044540553,0.008091409,0.01155717,-0.011134993,-0.015595453,-0.0044206656,0.031132616,0.021964429,0.08499096,-0.029608035,0.09432952,-0.10045928,-0.0016386824,0.045343123,-0.027784642,0.04225195,-0.077244245,-0.025754198,-0.062053796,0.017611738,-0.031203467,0.01756977,-0.025270505,-0.02455264,0.0032717404],"context_embeddings":[0.016879551,-0.025130803,-0.04894951,0.03052548,0.027412113,-0.037724186,-0.033633586,0.04956943,-0.05980706,-0.09265756,-0.021175044,0.014036697,-0.07034784,-0.008631171,0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{"question":"Can I create histograms with different bucket colors in Streamlit","document_title":"API reference","document_link":"https://docs.streamlit.io/1.6.0/library/api-reference/charts/st.plotly_chart#stplotly_chart","document_text":"## st.plotly\\_chart\n\nDisplay an interactive Plotly chart.\n\n\nPlotly is a charting library for Python. The arguments to this function\nclosely follow the ones for Plotly's plot() function. You can find\nmore about Plotly at <https://plot.ly/python>.\n\n\nTo show Plotly charts in Streamlit, call st.plotly\\_chart wherever you\nwould call Plotly's py.plot or py.iplot.\n\n\n\n\n| Function signature[[source]](https://github.com/streamlit/streamlit/blob/1.6.0/lib/streamlit/elements/plotly_chart.py#L42 \"View st.plotly_chart source code on GitHub\") |\n| --- |\n| st.plotly\\_chart(figure\\_or\\_data, use\\_container\\_width=False, sharing=\"streamlit\", \\*\\*kwargs) |\n| Parameters |\n| \n\nfigure\\_or\\_data\n(plotly.graph\\_objs.Figure, plotly.graph\\_objs.Data,)\n | \ndict/list of plotly.graph\\_objs.Figure/Data\nSee <https://plot.ly/python/> for examples of graph descriptions.\n |\n| \n\nuse\\_container\\_width\n(bool)\n | \nIf True, set the chart width to the column width. This takes\nprecedence over the figure's native width value.\n |\n| \n\nsharing\n({'streamlit', 'private', 'secret', 'public'})\n | \nUse 'streamlit' to insert the plot and all its dependencies\ndirectly in the Streamlit app using plotly's offline mode (default).\nUse any other sharing mode to send the chart to Plotly chart studio, which\nrequires an account. See <https://plotly.com/chart-studio/> for more information.\n |\n| \n\n\\*\\*kwargs\n(null)\n | \nAny argument accepted by Plotly's plot() function.\n |\n\n#### Example\n\n\n> \n> The example below comes straight from the examples at\n> <https://plot.ly/python>:\n> \n> \n> \n> ```\n> \n> import streamlit as st\n> import plotly.figure_factory as ff\n> import numpy as np\n> \n> # Add histogram data\n> x1 = np.random.randn(200) - 2\n> x2 = np.random.randn(200)\n> x3 = np.random.randn(200) + 2\n> \n> # Group data together\n> hist_data = [x1, x2, x3]\n> \n> group_labels = ['Group 1', 'Group 2', 'Group 3']\n> \n> # Create distplot with custom bin_size\n> fig = ff.create_distplot(\n> hist_data, group_labels, bin_size=[.1, .25, .5])\n> \n> # Plot!\n> st.plotly_chart(fig, use_container_width=True)\n> \n> ```\n> \n> \n> [(view standalone Streamlit app)](https://share.streamlit.io/streamlit/docs/main/python/api-examples-source/charts.plotly_chart.py) \n> \n\n\n### Theming\n\nPlotly charts are displayed using the Streamlit theme by default. This theme is sleek, user-friendly, and incorporates Streamlit's color palette. The added benefit is that your charts better integrate with the rest of your app's design.\n\nThe Streamlit theme is available from Streamlit 1.16.0 through the `theme=\"streamlit\"` keyword argument. To disable it, and use Plotly's native theme, use `theme=None` instead.\n\nLet's look at an example of charts with the Streamlit theme and the native Plotly theme:\n\n\n```\nimport plotly.express as px\nimport streamlit as st\n\ndf = px.data.gapminder()\n\nfig = px.scatter(\n df.query(\"year==2007\"),\n x=\"gdpPercap\",\n y=\"lifeExp\",\n size=\"pop\",\n color=\"continent\",\n hover_name=\"country\",\n log_x=True,\n size_max=60,\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n # Use the Streamlit theme.\n # This is the default. So you can also omit the theme argument.\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n # Use the native Plotly theme.\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\n```\nClick the tabs in the interactive app below to see the charts with the Streamlit theme enabled and disabled.\n\nIf you're wondering if your own customizations will still be taken into account, don't worry! You can still make changes to your chart configurations. In other words, although we now enable the Streamlit theme by default, you can overwrite it with custom colors or fonts. For example, if you want a chart line to be green instead of the default red, you can do it!\n\nHere's an example of an Plotly chart where a custom color scale is defined and reflected:\n\n\n```\nimport plotly.express as px\nimport streamlit as st\n\nst.subhe","answer":"unction signature:\n\n st.plotly_chart(figure_or_data, use_container_width=False, sharing=\"streamlit\", **kwargs)\n\nParameters:\n\nfigure_or_data\n(plotly.graph_objs.Figure, plotly.graph_objs.Data,)\n | \ndict/list of plotly.graph_objs.Figure/Data\nSee <https://plot.ly/python/> for examples of graph descriptions.\n\nuse_container_width\n(bool)\n | \nIf True, set the chart width to the column width. This takes\nprecedence over the figure's native width value.\n\nsharing\n({'streamlit', 'private', 'secret', 'public'})\n | \nUse 'streamlit' to insert the plot and all its dependencies\ndirectly in the Streamlit app using plotly's offline mode (default).\nUse any other sharing mode to send the chart to Plotly chart studio, which requires an account. See <https://plotly.com/chart-studio/> for more information.\n\n### Theming\n\nPlotly charts are displayed using the Streamlit theme by default. This theme is sleek, user-friendly, and incorporates Streamlit's color palette. The added benefit is that your charts better integrate with the rest of your app's design.\n\nThe Streamlit theme is available from Streamlit 1.16.0 through the `theme=\"streamlit\"` keyword argument. To disable it, and use Plotly's native theme, use `theme=None` instead","question_idx":0,"row_idx":21,"model":"gpt-3.5-turbo","idx":21,"Template":0,"persona":"bot","response":"2. Use NumPy to generate a histogram that breaks down pickup times binned by\nhour:\n\n\n```\nhist_values = np.histogram(\n data[DATE_COLUMN].dt.hour, bins=24, range=(0,24))[0]\n\n```\n3. Now, let's use Streamlit's\n[`st.bar_chart()`](https://docs.streamlit.io/library/api-reference/charts/st.bar_chart) method to draw this\nhistogram.\n\n\n```\nst.bar_chart(hist_values)\n\n```","experiment_id":0,"question_embeddings":[0.06357269,-0.0065760594,-0.020345902,-0.08352584,-0.047350194,0.036682703,0.03675301,-0.020481193,-0.023199504,-0.023003703,-0.08344998,-0.046929147,0.030856805,0.0040366957,0.055860724,-0.027778918,-0.08961629,0.0041082106,-0.090726905,-0.14028054,0.005671198,-0.04953355,-0.056541827,-0.07677412,-0.0054286676,0.046765037,0.028512418,0.05420102,0.068443455,-0.0604626,0.054457724,-0.07275235,0.049726702,-0.022302784,-0.0041490933,-0.02186213,-0.03887204,0.058403235,-0.08978373,0.037947502,0.038772896,0.015465372,-0.031523794,-0.051518813,-0.026647044,0.0863903,-0.07547597,0.013137831,0.012855303,0.022156958,-0.033148255,-0.07180802,0.036730874,0.022195915,0.015626686,-0.029947298,-0.04305715,-0.06709682,0.05954109,-0.08123926,-0.05617996,-0.008180384,0.022568718,-0.0036913706,0.09570576,0.03136336,-0.015436422,0.03444204,0.09311254,-0.02689361,0.03140673,0.06345534,0.08536748,0.048517168,-0.06511003,0.0054839347,-0.012848926,0.05942965,-0.06755942,-0.053685118,-0.027762018,0.008932237,0.040417593,0.022191966,0.011978196,0.054522794,-0.072129376,0.014587649,-0.04637386,0.02310457,-0.06725896,0.06178685,0.024150467,-0.049363486,-0.061521318,0.055563316,0.08960045,-0.01576581,0.057299186,-0.02973093,0.042051695,-0.06689739,0.007888104,-0.022333588,0.08404724,-0.021441972,-0.02634069,0.09471672,0.018893978,-0.03912352,0.0329555,-0.03708901,0.03689426,-0.09556095,-0.009662683,0.06899001,-0.11976706,0.0066234786,-0.06276309,0.017529482,0.064207785,-0.01157287,-0.040234894,-0.015450808,-0.0153679075,-0.052646134,-0.032788604,-2.7589148e-33,0.03576235,-0.10662839,-0.04067808,0.029993126,0.063296854,0.04668259,-0.012749555,0.005248918,-0.010436894,-0.07561844,-0.011633145,0.05444743,-0.048320852,0.014772509,-0.07199935,-0.014760617,0.021598626,-0.017174078,-0.05955723,-0.03472137,-0.07610088,-0.048029725,0.038275547,-0.024732482,0.02252993,-0.014710533,0.053196922,-0.01815156,0.046866003,0.038138613,0.023503724,0.07431182,-0.010030737,0.018859217,0.054400813,-0.051315624,-0.05778552,0.052278083,-0.04012966,0.07762834,0.07195341,0.011121125,-0.05060351,0.012136496,-0.07420707,0.04311224,0.07492402,-0.04081308,-0.018771872,-0.033988312,0.045980997,0.08672062,-0.005062198,-0.025109446,0.12977187,-0.016560083,0.029968856,0.042827725,0.067344815,0.04638003,-0.035595536,0.14303884,0.032466277,0.02497015,0.050941344,-0.024447702,0.10157372,0.0778076,0.00053819915,-0.031346135,-0.008758584,0.036722686,-0.0015840823,-0.020259231,-0.015971852,-0.04298156,0.07306846,0.022992812,-0.034721397,-0.030194966,-0.014201621,-0.043520536,0.010887479,0.03231367,-0.087124325,0.027420446,0.06266317,0.027834242,-0.12047557,-0.087669924,-0.020153027,0.031243222,0.027246276,-0.10769241,-0.0072499076,9.307464e-34,-0.080400184,0.08192685,-0.04577184,0.078311056,0.0642137,0.012169457,0.13736194,0.022015871,0.03278156,0.05398484,-0.035939127,-0.0022418867,-0.1290434,0.008012245,-0.017896941,-0.030848654,-0.012321777,0.024660239,-0.06502408,-0.03576453,-0.10739129,0.0059367563,-0.038558144,-0.0053904355,-0.029615968,0.0663225,-0.009698477,0.002204676,0.016577557,0.016558561,0.032411598,0.025009926,-0.023183554,-0.0548188,-0.013516646,-0.11561085,0.06011747,0.0032648896,-0.019577319,0.08061338,0.036386278,-0.06483969,-0.009423049,-0.067994475,-0.0059552514,0.07898494,-0.030586459,0.057788316,-0.011511716,-0.007741939,-0.02863135,0.03207052,-0.025858352,0.076669626,0.07364335,-0.0601048,0.078869574,0.049763173,0.0026653612,0.007474002,-0.052608352,-0.10268198,0.102147534,-0.019444479,0.051910717,-0.002900365,0.015770577,-0.067796655,-0.029883914,0.022909926,0.009268357,-0.121122375,0.067859925,-0.059911028,0.045639582,-0.009814225,0.014831371,0.059833657,-0.014894034,-0.0022807359,-0.027649293,-0.014831903,0.052625373,0.056469955,0.07557365,0.0031232166,-0.011547768,-0.05443782,0.06120629,0.07160346,0.032031905,0.059437387,-0.012607803,0.04696337,0.07722856,-1.6495452e-8,0.014486489,-0.048435584,0.003250121,0.028159982,0.031189898,0.0023627344,-0.070192665,0.056730375,0.03496575,0.011610652,0.06183044,-0.027920958,-0.0121314,-0.052380722,-0.020452451,-0.04563529,0.017542096,-0.03620699,0.0011459879,0.041698407,-0.028633622,0.03700075,-0.00061687466,0.021913622,-0.07560133,0.03271757,0.017450893,-0.07702778,0.020872569,-0.06213861,-0.0038546,0.04003318,0.069114655,-0.0065786745,-0.016454224,-0.09361585,-0.16091056,0.058383908,-0.052135747,0.010157994,0.016596014,-0.0043797004,-0.014434132,0.0061570127,0.0016335461,0.02599054,0.034217644,0.056406163,-0.020769285,0.08216932,-0.10429248,0.004765623,0.04851646,-0.022152325,0.04684329,-0.058515728,-0.017122269,-0.064585134,0.008293409,-0.034130603,0.024276521,-0.04850379,-0.00979301,-0.0031762286],"context_embeddings":[0.016576745,-0.025266241,-0.04868586,0.030512491,0.02720513,-0.037916716,-0.034587722,0.04976421,-0.059679825,-0.09256117,-0.0213575,0.014031294,-0.07039518,-0.009107959,0.021184571,-0.078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{"question":"How to use the sessionstate feature in Streamlit","document_title":"Advanced features","document_link":"https://docs.streamlit.io/library/advanced-features#advanced-notes-on-widget-behavior","document_text":"mlit.io/library/advanced-features/caching)[##### Add statefulness to apps\n\nSession State is a way to share variables between reruns, for each user session. In addition to the ability to store and persist state, Streamlit also exposes the ability to manipulate state using Callbacks.\n\n* [What is Session State?](https://docs.streamlit.io/library/advanced-features/session-state#what-is-state)\n* [How to initialize Session State items?](https://docs.streamlit.io/library/advanced-features/session-state#initialization)\n* [How to read and update Session State items?](https://docs.streamlit.io/library/advanced-features/session-state#reads-and-updates)\n* [How to use callbacks in Session State?](https://docs.streamlit.io/library/advanced-features/session-state#example-2-session-state-and-callbacks)\n* [How to use `args` and `kwargs` in callbacks?](https://docs.streamlit.io/library/advanced-features/session-state#example-3-use-args-and-kwargs-in-callbacks)\n* [How to use callbacks in forms?](https://docs.streamlit.io/library/advanced-features/session-state#example-4-forms-and-callbacks)\n* [How is Session State related to Widget State?](https://docs.streamlit.io/library/advanced-features/session-state#session-state-and-widget-state-association)\n* [Caveats and limitations](https://docs.streamlit.io/library/advanced-features/session-state#caveats-and-limitations)](https://docs.streamlit.io/library/advanced-features/session-state)[##### Pre-release features\n\nAt Streamlit, we like to move quick while keeping things stable. In our latest effort to move even faster without sacrificing stability, we're offering our bold and fearless users two ways to try out Streamlit's bleeding-edge features.\n\n* [Experimental features](https://docs.streamlit.io/library/advanced-features/prerelease#experimental-features)\n* [Nightly releases](https://docs.streamlit.io/library/advanced-features/prerelease#nightly-releases)](https://docs.streamlit.io/library/advanced-features/prerelease)[##### Secrets management\n\nThis section provides examples of how to use secrets management to store and retrieve sensitive information in your Streamlit app.\n\n* [Develop locally and set up secrets](https://docs.streamlit.io/library/advanced-features/secrets-management#develop-locally-and-set-up-secrets)\n* [Use secrets in your app](https://docs.streamlit.io/library/advanced-features/secrets-management#use-secrets-in-your-app)\n* [Error handling](https://docs.streamlit.io/library/advanced-features/secrets-management#error-handling)\n* [Use secrets on Streamlit Community Cloud](https://docs.streamlit.io/library/advanced-features/secrets-management#use-secrets-on-streamlit-community-cloud)](https://docs.streamlit.io/library/advanced-features/secrets-management)[##### Working with timezones\n\nWorking with timezones can be tricky. This section provides a high-level description of how to handle timezones in Streamlit to avoid unexpected behavior.\n\n* [Overview](https://docs.streamlit.io/library/advanced-features/timezone-handling#working-with-timezones)\n* [How Streamlit handles timezones](https://docs.streamlit.io/library/advanced-features/timezone-handling#how-streamlit-handles-timezones)\n* [`datetime` instance without a timezone (naive)](https://docs.streamlit.io/library/advanced-features/timezone-handling#datetime-instance-without-a-timezone-naive)\n* [`datetime` instance with a timezone](https://docs.streamlit.io/library/advanced-features/timezone-handling#datetime-instance-with-a-timezone)](https://docs.streamlit.io/library/advanced-features/timezone-handling)[##### Advanced notes on widget behavior\n\nWidgets are magical and often work how you want. But they can have surprising behavior in some situations. This section provides is a high-level, abstract description of widget behavior, including some common edge-cases.](https://docs.streamlit.io/library/advanced-features/widget-semantics)","answer":" [What is Session State?](https://docs.streamlit.io/library/advanced-features/session-state#what-is-state)\n* [How to initialize Session State items?](https://docs.streamlit.io/library/advanced-features/session-state#initialization)\n* [How to read and update Session State items?](https://docs.streamlit.io/library/advanced-features/session-state#reads-and-updates)\n* [How to use callbacks in Session State?](https://docs.streamlit.io/library/advanced-features/session-state#example-2-session-state-and-callbacks)\n* [How to use `args` and `kwargs` in callbacks?](https://docs.streamlit.io/library/advanced-features/session-state#example-3-use-args-and-kwargs-in-callbacks)\n* [How to use callbacks in forms?](https://docs.streamlit.io/library/advanced-features/session-state#example-4-forms-and-callbacks)\n* [How is Session State related to Widget State?](https://docs.streamlit.io/library/advanced-features/session-state#session-state-and-widget-state-association)\n* [Caveats and limitations](https://docs.streamlit.io/library/advanced-features/session-state#caveats-and-limitations)\n\n<EMPTY MESSAGE","question_idx":2,"row_idx":22,"model":"gpt-3.5-turbo","idx":22,"Template":0,"persona":"bot","response":"```\ndf = px.data.iris()\nfig = px.scatter(\n df,\n x=\"sepal_width\",\n y=\"sepal_length\",\n color=\"sepal_length\",\n color_continuous_scale=\"reds\",\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n st.plotly_chart(fig, theme=None, use_container_width=True)\n```\n```\nNotice how the custom color scale is still reflected in the chart, even when the Streamlit theme is enabled 👇\n\nFor many more examples of Plotly charts with and without the Streamlit theme, check out the [plotly.streamlit.app](https://plotly.streamlit.app).\n```","experiment_id":0,"question_embeddings":[-0.008069718,0.019030994,-0.04399113,-0.018124266,-0.022838099,0.06364004,0.09799271,0.028880155,-0.027881691,-0.0026304945,-0.093847126,-0.052826203,-0.0495291,0.050359074,0.057861276,-0.081056945,-0.043767277,-0.034344412,0.030334882,-0.054179147,0.081798576,-0.06108611,-0.027220473,0.016159661,0.045966722,0.043755453,0.04657097,-0.04207103,0.0606236,-0.010835065,0.01963093,0.023086326,-0.08611886,-0.09577034,-0.042422198,-0.031213628,-0.02303005,-0.012711064,-0.061771363,-0.032626864,0.04722137,-0.05833356,-0.024581093,-0.014408672,-0.043140084,0.043106694,-0.043605175,0.012564146,-0.0024074847,0.07467294,-0.026442008,0.024675488,0.06863068,0.05543007,-0.036845602,0.021533161,0.03818942,0.07087255,-0.014140007,0.012392753,-0.029511698,-0.03693794,0.0142641105,-0.0068583405,-0.021607645,0.032087505,-0.004642361,-0.00048144456,0.08657255,-0.091415726,-0.0654163,0.040753946,0.04778726,-0.07014419,-0.054056033,-0.13101906,0.0106581375,-0.033824015,-0.015706005,0.036165632,0.06448401,-0.027799198,-0.016320214,-0.030502934,0.044609677,-0.0064864736,-0.023485867,-0.02510403,-0.032146394,0.11691514,-0.093619,0.09026529,-0.04394514,-0.040745012,-0.074140415,0.07941597,-0.058178466,0.10143081,0.00082231086,0.034904383,0.021032574,0.02780719,0.020528773,0.07157437,0.015880924,-0.07901302,0.002658145,0.033562664,0.025330164,-0.0620102,0.00088657654,0.043670274,0.06292877,0.020624137,0.024602726,0.014736394,-0.012740257,0.024506299,-0.01692787,0.03850096,0.05740074,-0.048916616,-0.041654356,-0.016295029,0.06332491,0.007249942,0.1201618,-3.069891e-33,0.038632937,-0.07285959,-0.097846106,0.06889692,0.039875455,0.061407413,0.06816671,-0.021834662,-0.041231632,-0.06655201,-0.02681365,-0.00846934,0.0056336895,0.025145523,-0.07212278,-0.088356264,-0.06571071,0.034034792,0.022489915,-0.057755113,0.041024677,-0.0111023635,0.060905315,-0.03981662,0.025356166,0.003709564,0.039863884,-0.009520236,0.026838858,0.009208849,0.061858226,0.041652687,0.027003404,0.008471059,0.100978374,-0.07413808,0.02455753,-0.019793069,0.016882718,-0.06035224,0.005419944,0.030355176,-0.05040027,0.009402115,-0.09048009,-0.060497977,-0.034752905,0.026658474,-0.031877108,-0.019351725,-0.024361955,0.08411059,-0.051161606,-0.006133748,0.023922987,-0.03208829,-0.034828957,0.09694366,-0.023172703,-0.028460398,-0.02360395,0.011142688,-0.046996046,-0.07437975,-0.024909688,0.03751471,0.051979627,0.02110711,-0.016065998,-0.15068954,-0.0536162,-0.027345277,-0.012201718,0.024762029,-0.0059242416,-0.0022329595,0.042477656,0.07530215,-0.06591605,-0.00408647,0.020814484,-0.032786287,-0.022626853,0.12286805,0.0066859704,-0.022303088,0.002724913,-0.03851183,-0.032818407,-0.057483967,-0.054443043,-0.0041463273,0.16144624,0.007332825,0.054585196,1.2820273e-33,0.022542262,-0.020859636,-0.052710604,0.001758398,0.052588698,0.025964668,0.10388966,0.014702435,0.0043939003,-0.041091733,-0.0074163736,0.035646103,-0.11103489,0.03836938,-0.030325333,0.013828032,0.03198602,0.0045473897,-0.03992809,-0.023974352,-0.0017821189,0.008392904,-0.05047325,0.012730342,0.06085425,-0.056332808,0.07645324,-0.0226349,0.015513832,0.030792732,0.090231426,0.015368832,-0.074278586,0.012956486,0.045075648,-0.013657695,0.091199115,0.010006847,-0.12094287,0.11235369,0.09024848,-0.03860437,-0.07123643,-0.045214918,0.019595131,0.07379895,-0.09251951,0.008591872,-0.13025522,0.061584905,0.007761197,-0.10383422,-0.009915873,-0.025119737,0.009733272,-0.06666904,0.06700916,-0.02102678,-0.04229344,-0.11801866,0.009725576,-0.0668771,0.0069729257,-0.019669157,0.07609675,0.03374921,0.026979292,0.07371696,0.09338998,-0.022135435,0.00040826626,-0.09352545,0.054446653,0.032927696,0.08484965,0.036018204,-0.017780457,-0.044531226,-0.0012620412,0.009875729,-0.04044144,0.020187803,-0.041872904,-0.07363746,0.0780202,0.040785998,0.0111372005,0.07780356,-0.011045198,-0.014636242,-0.057807446,0.051122837,-0.08242229,0.031930815,0.08355099,-1.4805702e-8,-0.051469665,-0.033614144,0.018845683,0.06451867,0.0058652232,0.0007405246,-0.027512264,-0.023120081,-0.024361122,-0.061715182,-0.009631923,-0.035585366,0.14869612,-0.082732216,0.024393944,-0.035837397,-0.00039809948,0.044956114,-0.02445103,0.024959521,0.021514298,-0.026425743,0.0038626466,0.100734875,-0.05428898,0.008292243,0.08542635,0.0042307405,0.014428068,-0.031963438,0.0071916976,0.07829516,0.058305006,-0.007757116,-0.008674596,0.07569885,-0.032974575,0.028838512,-0.023347737,0.023153437,-0.002992033,-0.008270725,0.02424749,-0.02757731,-0.028802924,0.05631192,-0.0530676,0.079994015,0.046310086,0.004630426,-0.021416683,0.05256077,0.008517852,0.07715209,0.018514486,-0.023122005,0.04937923,-0.07301177,0.007907248,-0.09448888,0.02026514,0.03812597,-0.05387038,-0.011038521],"context_embeddings":[-0.081959456,-0.003604318,-0.074795805,0.010582859,-0.028259337,0.003969305,0.07611417,0.01851152,-0.035770096,-0.033666965,-0.032247033,0.0011627594,-0.07307246,-0.003459143,0.02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{"question":"How to use the sessionstate feature in Streamlit","document_title":"Advanced features","document_link":"https://docs.streamlit.io/library/advanced-features#advanced-notes-on-widget-behavior","document_text":"## ","answer":"##### Caching\n\nThe Streamlit cache allows your app to stay performant even when loading data from the web, manipulating large datasets, or performing expensive computations. To cache a function in Streamlit, you need to decorate it with one of two decorators: `st.cache_data` and `st.cache_resource`.\n\n* [Minimal example](https://docs.streamlit.io/library/advanced-features/caching#minimal-example)\n* [Basic usage](https://docs.streamlit.io/library/advanced-features/caching#basic-usage)\n\t+ [st.cache\\_data](https://docs.streamlit.io/library/advanced-features/caching#stcache_data)\n\t+ [st.cache\\_resource](https://docs.streamlit.io/library/advanced-features/caching#stcache_resource)\n\t+ [Deciding which caching decorator to use](https://docs.streamlit.io/library/advanced-features/caching#deciding-which-caching-decorator-to-use)\n* [Advanced usage](https://docs.streamlit.io/library/advanced-features/caching#advanced-usage)\n\t+ [Excluding input parameters](https://docs.streamlit.io/library/advanced-features/caching#excluding-input-parameters)\n\t+ [Controlling cache size and duration](https://docs.streamlit.io/library/advanced-features/caching#controlling-cache-size-and-duration)\n\t+ [Customizing the spinner](https://docs.streamlit.io/library/advanced-features/caching#customizing-the-spinner)\n\t+ [Using Streamlit commands in cached functions](https://docs.streamlit.io/library/advanced-features/caching#using-streamlit-commands-in-cached-functions)\n\t+ [Mutation and concurrency issues](https://docs.streamlit.io/library/advanced-features/caching#mutation-and-concurrency-issues)\n* [Migrating from st.cache](https://docs.streamlit.io/library/advanced-features/caching#migrating-from-stcache)](https://docs.stre","question_idx":2,"row_idx":23,"model":"gpt-3.5-turbo","idx":23,"Template":0,"persona":"bot","response":"Function signature:\n```\nst.plotly_chart(figure_or_data, use_container_width=False, sharing=\"streamlit\", **kwargs)\n```\n\nExample usage:\n```\nimport streamlit as st\nimport plotly.figure_factory as ff\nimport numpy as np\n\n# Add histogram data\nx1 = np.random.randn(200) - 2\nx2 = np.random.randn(200)\nx3 = np.random.randn(200) + 2\n\n# Group data together\nhist_data = [x1, x2, x3]\n\ngroup_labels = ['Group 1', 'Group 2', 'Group 3']\n\n# Create distplot with custom bin_size\nfig = ff.create_distplot(\n hist_data, group_labels, bin_size=[.1, .25, .5])\n\n# Plot!\nst.plotly_chart(fig, use_container_width=True)\n```\n\nTheming:\n```\nPlotly charts are displayed using the Streamlit theme by default. This theme is sleek, user-friendly, and incorporates Streamlit's color palette. The added benefit is that your charts better integrate with the rest of your app's design.\n\nThe Streamlit theme is available from Streamlit 1.16.0 through the `theme=\"streamlit\"` keyword argument. To disable it, and use Plotly's native theme, use `theme=None` instead.\n\nLet's look at an example of charts with the Streamlit theme and the native Plotly theme:\n\nimport plotly.express as px\nimport streamlit as st\n\ndf = px.data.gapminder()\n\nfig = px.scatter(\n df.query(\"year==2007\"),\n x=\"gdpPercap\",\n y=\"lifeExp\",\n size=\"pop\",\n color=\"continent\",\n hover_name=\"country\",\n log_x=True,\n size_max=60,\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n # Use the Streamlit theme.\n # This is the default. So you can also omit the theme argument.\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n # Use the native Plotly theme.\n st.plotly_chart(fig, theme=None, use_container_width=True)\n```","experiment_id":0,"question_embeddings":[-0.008069718,0.019030994,-0.04399113,-0.018124266,-0.022838099,0.06364004,0.09799271,0.028880155,-0.027881691,-0.0026304945,-0.093847126,-0.052826203,-0.0495291,0.050359074,0.057861276,-0.081056945,-0.043767277,-0.034344412,0.030334882,-0.054179147,0.081798576,-0.06108611,-0.027220473,0.016159661,0.045966722,0.043755453,0.04657097,-0.04207103,0.0606236,-0.010835065,0.01963093,0.023086326,-0.08611886,-0.09577034,-0.042422198,-0.031213628,-0.02303005,-0.012711064,-0.061771363,-0.032626864,0.04722137,-0.05833356,-0.024581093,-0.014408672,-0.043140084,0.043106694,-0.043605175,0.012564146,-0.0024074847,0.07467294,-0.026442008,0.024675488,0.06863068,0.05543007,-0.036845602,0.021533161,0.03818942,0.07087255,-0.014140007,0.012392753,-0.029511698,-0.03693794,0.0142641105,-0.0068583405,-0.021607645,0.032087505,-0.004642361,-0.00048144456,0.08657255,-0.091415726,-0.0654163,0.040753946,0.04778726,-0.07014419,-0.054056033,-0.13101906,0.0106581375,-0.033824015,-0.015706005,0.036165632,0.06448401,-0.027799198,-0.016320214,-0.030502934,0.044609677,-0.0064864736,-0.023485867,-0.02510403,-0.032146394,0.11691514,-0.093619,0.09026529,-0.04394514,-0.040745012,-0.074140415,0.07941597,-0.058178466,0.10143081,0.00082231086,0.034904383,0.021032574,0.02780719,0.020528773,0.07157437,0.015880924,-0.07901302,0.002658145,0.033562664,0.025330164,-0.0620102,0.00088657654,0.043670274,0.06292877,0.020624137,0.024602726,0.014736394,-0.012740257,0.024506299,-0.01692787,0.03850096,0.05740074,-0.048916616,-0.041654356,-0.016295029,0.06332491,0.007249942,0.1201618,-3.069891e-33,0.038632937,-0.07285959,-0.097846106,0.06889692,0.039875455,0.061407413,0.06816671,-0.021834662,-0.041231632,-0.06655201,-0.02681365,-0.00846934,0.0056336895,0.025145523,-0.07212278,-0.088356264,-0.06571071,0.034034792,0.022489915,-0.057755113,0.041024677,-0.0111023635,0.060905315,-0.03981662,0.025356166,0.003709564,0.039863884,-0.009520236,0.026838858,0.009208849,0.061858226,0.041652687,0.027003404,0.008471059,0.100978374,-0.07413808,0.02455753,-0.019793069,0.016882718,-0.06035224,0.005419944,0.030355176,-0.05040027,0.009402115,-0.09048009,-0.060497977,-0.034752905,0.026658474,-0.031877108,-0.019351725,-0.024361955,0.08411059,-0.051161606,-0.006133748,0.023922987,-0.03208829,-0.034828957,0.09694366,-0.023172703,-0.028460398,-0.02360395,0.011142688,-0.046996046,-0.07437975,-0.024909688,0.03751471,0.051979627,0.02110711,-0.016065998,-0.15068954,-0.0536162,-0.027345277,-0.012201718,0.024762029,-0.0059242416,-0.0022329595,0.042477656,0.07530215,-0.06591605,-0.00408647,0.020814484,-0.032786287,-0.022626853,0.12286805,0.0066859704,-0.022303088,0.002724913,-0.03851183,-0.032818407,-0.057483967,-0.054443043,-0.0041463273,0.16144624,0.007332825,0.054585196,1.2820273e-33,0.022542262,-0.020859636,-0.052710604,0.001758398,0.052588698,0.025964668,0.10388966,0.014702435,0.0043939003,-0.041091733,-0.0074163736,0.035646103,-0.11103489,0.03836938,-0.030325333,0.013828032,0.03198602,0.0045473897,-0.03992809,-0.023974352,-0.0017821189,0.008392904,-0.05047325,0.012730342,0.06085425,-0.056332808,0.07645324,-0.0226349,0.015513832,0.030792732,0.090231426,0.015368832,-0.074278586,0.012956486,0.045075648,-0.013657695,0.091199115,0.010006847,-0.12094287,0.11235369,0.09024848,-0.03860437,-0.07123643,-0.045214918,0.019595131,0.07379895,-0.09251951,0.008591872,-0.13025522,0.061584905,0.007761197,-0.10383422,-0.009915873,-0.025119737,0.009733272,-0.06666904,0.06700916,-0.02102678,-0.04229344,-0.11801866,0.009725576,-0.0668771,0.0069729257,-0.019669157,0.07609675,0.03374921,0.026979292,0.07371696,0.09338998,-0.022135435,0.00040826626,-0.09352545,0.054446653,0.032927696,0.08484965,0.036018204,-0.017780457,-0.044531226,-0.0012620412,0.009875729,-0.04044144,0.020187803,-0.041872904,-0.07363746,0.0780202,0.040785998,0.0111372005,0.07780356,-0.011045198,-0.014636242,-0.057807446,0.051122837,-0.08242229,0.031930815,0.08355099,-1.4805702e-8,-0.051469665,-0.033614144,0.018845683,0.06451867,0.0058652232,0.0007405246,-0.027512264,-0.023120081,-0.024361122,-0.061715182,-0.009631923,-0.035585366,0.14869612,-0.082732216,0.024393944,-0.035837397,-0.00039809948,0.044956114,-0.02445103,0.024959521,0.021514298,-0.026425743,0.0038626466,0.100734875,-0.05428898,0.008292243,0.08542635,0.0042307405,0.014428068,-0.031963438,0.0071916976,0.07829516,0.058305006,-0.007757116,-0.008674596,0.07569885,-0.032974575,0.028838512,-0.023347737,0.023153437,-0.002992033,-0.008270725,0.02424749,-0.02757731,-0.028802924,0.05631192,-0.0530676,0.079994015,0.046310086,0.004630426,-0.021416683,0.05256077,0.008517852,0.07715209,0.018514486,-0.023122005,0.04937923,-0.07301177,0.007907248,-0.09448888,0.02026514,0.03812597,-0.05387038,-0.011038521],"context_embeddings":[-0.03463325,-0.016433293,0.059964098,0.008273938,0.031791538,0.0052614175,0.12840705,0.0059840265,0.050174482,-0.052266374,-0.04056925,0.046247832,-0.028065091,-0.026850248,-0.0012414873,0.035591546,0.003901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{"question":"How to use the sessionstate feature in Streamlit","document_title":"Widget updating for every second input when using session state","document_link":"https://docs.streamlit.io/knowledge-base/using-streamlit/widget-updating-session-state#relevant-resources","document_text":"## Solution\n\nWhen using session state to update widgets or values in your script, you need to use the unique key you assigned to the widget, **not** the variable that you assigned your widget to. In the example code block below, the unique *key* assigned to the slider widget is `slider`, and the *variable* the widget is assigned to is `slide_val`.\n\nLet's see this in an example. Say you want a user to click a button that resets a slider.\n\nTo have the slider's value update on the button click, you need to use a [callback function](https://docs.streamlit.io/library/api-reference/session-state#use-callbacks-to-update-session-state) with the `on_click` parameter of [`st.button`](https://docs.streamlit.io/library/api-reference/widgets/st.button):\n\n\n```\n# the callback function for the button will add 1 to the\n# slider value up to 10\ndef plus_one():\n if st.session_state[\"slider\"] < 10:\n st.session_state.slider += 1\n else:\n pass\n return\n\n# when creating the button, assign the name of your callback\n# function to the on_click parameter\nadd_one = st.button(\"Add one to the slider\", on_click=plus_one, key=\"add_one\")\n\n# create the slider\nslide_val = st.slider(\"Pick a number\", 0, 10, key=\"slider\")\n\n```\n","answer":"hen using session state to update widgets or values in your script, you need to use the unique key you assigned to the widget, **not** the variable that you assigned your widget to.\n\nTo have the slider's value update on the button click, you need to use a [callback function](https://docs.streamlit.io/library/api-reference/session-state#use-callbacks-to-update-session-state) with the `on_click` parameter of [`st.button`](https://docs.streamlit.io/library/api-reference/widgets/st.button):\n``","question_idx":2,"row_idx":24,"model":"gpt-3.5-turbo","idx":24,"Template":0,"persona":"bot","response":"```\ndf = px.data.iris()\nfig = px.scatter(\n df,\n x=\"sepal_width\",\n y=\"sepal_length\",\n color=\"sepal_length\",\n color_continuous_scale=\"reds\",\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n st.plotly_chart(fig, theme=None, use_container_width=True)\n```\n```\nNotice how the custom color scale is still reflected in the chart, even when the Streamlit theme is enabled 👇\n\nFor many more examples of Plotly charts with and without the Streamlit theme, check out the [plotly.streamlit.app](https://plotly.streamlit.app).\n```","experiment_id":0,"question_embeddings":[-0.008069718,0.019030994,-0.04399113,-0.018124266,-0.022838099,0.06364004,0.09799271,0.028880155,-0.027881691,-0.0026304945,-0.093847126,-0.052826203,-0.0495291,0.050359074,0.057861276,-0.081056945,-0.043767277,-0.034344412,0.030334882,-0.054179147,0.081798576,-0.06108611,-0.027220473,0.016159661,0.045966722,0.043755453,0.04657097,-0.04207103,0.0606236,-0.010835065,0.01963093,0.023086326,-0.08611886,-0.09577034,-0.042422198,-0.031213628,-0.02303005,-0.012711064,-0.061771363,-0.032626864,0.04722137,-0.05833356,-0.024581093,-0.014408672,-0.043140084,0.043106694,-0.043605175,0.012564146,-0.0024074847,0.07467294,-0.026442008,0.024675488,0.06863068,0.05543007,-0.036845602,0.021533161,0.03818942,0.07087255,-0.014140007,0.012392753,-0.029511698,-0.03693794,0.0142641105,-0.0068583405,-0.021607645,0.032087505,-0.004642361,-0.00048144456,0.08657255,-0.091415726,-0.0654163,0.040753946,0.04778726,-0.07014419,-0.054056033,-0.13101906,0.0106581375,-0.033824015,-0.015706005,0.036165632,0.06448401,-0.027799198,-0.016320214,-0.030502934,0.044609677,-0.0064864736,-0.023485867,-0.02510403,-0.032146394,0.11691514,-0.093619,0.09026529,-0.04394514,-0.040745012,-0.074140415,0.07941597,-0.058178466,0.10143081,0.00082231086,0.034904383,0.021032574,0.02780719,0.020528773,0.07157437,0.015880924,-0.07901302,0.002658145,0.033562664,0.025330164,-0.0620102,0.00088657654,0.043670274,0.06292877,0.020624137,0.024602726,0.014736394,-0.012740257,0.024506299,-0.01692787,0.03850096,0.05740074,-0.048916616,-0.041654356,-0.016295029,0.06332491,0.007249942,0.1201618,-3.069891e-33,0.038632937,-0.07285959,-0.097846106,0.06889692,0.039875455,0.061407413,0.06816671,-0.021834662,-0.041231632,-0.06655201,-0.02681365,-0.00846934,0.0056336895,0.025145523,-0.07212278,-0.088356264,-0.06571071,0.034034792,0.022489915,-0.057755113,0.041024677,-0.0111023635,0.060905315,-0.03981662,0.025356166,0.003709564,0.039863884,-0.009520236,0.026838858,0.009208849,0.061858226,0.041652687,0.027003404,0.008471059,0.100978374,-0.07413808,0.02455753,-0.019793069,0.016882718,-0.06035224,0.005419944,0.030355176,-0.05040027,0.009402115,-0.09048009,-0.060497977,-0.034752905,0.026658474,-0.031877108,-0.019351725,-0.024361955,0.08411059,-0.051161606,-0.006133748,0.023922987,-0.03208829,-0.034828957,0.09694366,-0.023172703,-0.028460398,-0.02360395,0.011142688,-0.046996046,-0.07437975,-0.024909688,0.03751471,0.051979627,0.02110711,-0.016065998,-0.15068954,-0.0536162,-0.027345277,-0.012201718,0.024762029,-0.0059242416,-0.0022329595,0.042477656,0.07530215,-0.06591605,-0.00408647,0.020814484,-0.032786287,-0.022626853,0.12286805,0.0066859704,-0.022303088,0.002724913,-0.03851183,-0.032818407,-0.057483967,-0.054443043,-0.0041463273,0.16144624,0.007332825,0.054585196,1.2820273e-33,0.022542262,-0.020859636,-0.052710604,0.001758398,0.052588698,0.025964668,0.10388966,0.014702435,0.0043939003,-0.041091733,-0.0074163736,0.035646103,-0.11103489,0.03836938,-0.030325333,0.013828032,0.03198602,0.0045473897,-0.03992809,-0.023974352,-0.0017821189,0.008392904,-0.05047325,0.012730342,0.06085425,-0.056332808,0.07645324,-0.0226349,0.015513832,0.030792732,0.090231426,0.015368832,-0.074278586,0.012956486,0.045075648,-0.013657695,0.091199115,0.010006847,-0.12094287,0.11235369,0.09024848,-0.03860437,-0.07123643,-0.045214918,0.019595131,0.07379895,-0.09251951,0.008591872,-0.13025522,0.061584905,0.007761197,-0.10383422,-0.009915873,-0.025119737,0.009733272,-0.06666904,0.06700916,-0.02102678,-0.04229344,-0.11801866,0.009725576,-0.0668771,0.0069729257,-0.019669157,0.07609675,0.03374921,0.026979292,0.07371696,0.09338998,-0.022135435,0.00040826626,-0.09352545,0.054446653,0.032927696,0.08484965,0.036018204,-0.017780457,-0.044531226,-0.0012620412,0.009875729,-0.04044144,0.020187803,-0.041872904,-0.07363746,0.0780202,0.040785998,0.0111372005,0.07780356,-0.011045198,-0.014636242,-0.057807446,0.051122837,-0.08242229,0.031930815,0.08355099,-1.4805702e-8,-0.051469665,-0.033614144,0.018845683,0.06451867,0.0058652232,0.0007405246,-0.027512264,-0.023120081,-0.024361122,-0.061715182,-0.009631923,-0.035585366,0.14869612,-0.082732216,0.024393944,-0.035837397,-0.00039809948,0.044956114,-0.02445103,0.024959521,0.021514298,-0.026425743,0.0038626466,0.100734875,-0.05428898,0.008292243,0.08542635,0.0042307405,0.014428068,-0.031963438,0.0071916976,0.07829516,0.058305006,-0.007757116,-0.008674596,0.07569885,-0.032974575,0.028838512,-0.023347737,0.023153437,-0.002992033,-0.008270725,0.02424749,-0.02757731,-0.028802924,0.05631192,-0.0530676,0.079994015,0.046310086,0.004630426,-0.021416683,0.05256077,0.008517852,0.07715209,0.018514486,-0.023122005,0.04937923,-0.07301177,0.007907248,-0.09448888,0.02026514,0.03812597,-0.05387038,-0.011038521],"context_embeddings":[-0.078710295,-0.006898886,-0.03479986,-0.00075508753,-0.03787331,0.030370975,0.102086045,0.008949185,0.034775473,-0.03200145,-0.047709,-0.004116688,-0.026146162,0.027038442,0.0782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{"question":"How can I create histograms with different bucket colors in Streamlit","document_title":"API reference","document_link":"https://docs.streamlit.io/1.5.0/library/api-reference/charts/st.plotly_chart#stplotly_chart","document_text":"## st.plotly\\_chart\n\nDisplay an interactive Plotly chart.\n\n\nPlotly is a charting library for Python. The arguments to this function\nclosely follow the ones for Plotly's plot() function. You can find\nmore about Plotly at <https://plot.ly/python>.\n\n\nTo show Plotly charts in Streamlit, call st.plotly\\_chart wherever you\nwould call Plotly's py.plot or py.iplot.\n\n\n\n\n| Function signature[[source]](https://github.com/streamlit/streamlit/blob/1.5.0/lib/streamlit/elements/plotly_chart.py#L42 \"View st.plotly_chart source code on GitHub\") |\n| --- |\n| st.plotly\\_chart(figure\\_or\\_data, use\\_container\\_width=False, sharing=\"streamlit\", \\*\\*kwargs) |\n| Parameters |\n| \n\nfigure\\_or\\_data\n(plotly.graph\\_objs.Figure, plotly.graph\\_objs.Data,)\n | \ndict/list of plotly.graph\\_objs.Figure/Data\nSee <https://plot.ly/python/> for examples of graph descriptions.\n |\n| \n\nuse\\_container\\_width\n(bool)\n | \nIf True, set the chart width to the column width. This takes\nprecedence over the figure's native width value.\n |\n| \n\nsharing\n({'streamlit', 'private', 'secret', 'public'})\n | \nUse 'streamlit' to insert the plot and all its dependencies\ndirectly in the Streamlit app using plotly's offline mode (default).\nUse any other sharing mode to send the chart to Plotly chart studio, which\nrequires an account. See <https://plotly.com/chart-studio/> for more information.\n |\n| \n\n\\*\\*kwargs\n(null)\n | \nAny argument accepted by Plotly's plot() function.\n |\n\n#### Example\n\n\n> \n> The example below comes straight from the examples at\n> <https://plot.ly/python>:\n> \n> \n> \n> ```\n> \n> import streamlit as st\n> import plotly.figure_factory as ff\n> import numpy as np\n> \n> # Add histogram data\n> x1 = np.random.randn(200) - 2\n> x2 = np.random.randn(200)\n> x3 = np.random.randn(200) + 2\n> \n> # Group data together\n> hist_data = [x1, x2, x3]\n> \n> group_labels = ['Group 1', 'Group 2', 'Group 3']\n> \n> # Create distplot with custom bin_size\n> fig = ff.create_distplot(\n> hist_data, group_labels, bin_size=[.1, .25, .5])\n> \n> # Plot!\n> st.plotly_chart(fig, use_container_width=True)\n> \n> ```\n> \n> \n> [(view standalone Streamlit app)](https://share.streamlit.io/streamlit/docs/main/python/api-examples-source/charts.plotly_chart.py) \n> \n\n\n### Theming\n\nPlotly charts are displayed using the Streamlit theme by default. This theme is sleek, user-friendly, and incorporates Streamlit's color palette. The added benefit is that your charts better integrate with the rest of your app's design.\n\nThe Streamlit theme is available from Streamlit 1.16.0 through the `theme=\"streamlit\"` keyword argument. To disable it, and use Plotly's native theme, use `theme=None` instead.\n\nLet's look at an example of charts with the Streamlit theme and the native Plotly theme:\n\n\n```\nimport plotly.express as px\nimport streamlit as st\n\ndf = px.data.gapminder()\n\nfig = px.scatter(\n df.query(\"year==2007\"),\n x=\"gdpPercap\",\n y=\"lifeExp\",\n size=\"pop\",\n color=\"continent\",\n hover_name=\"country\",\n log_x=True,\n size_max=60,\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n # Use the Streamlit theme.\n # This is the default. So you can also omit the theme argument.\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n # Use the native Plotly theme.\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\n```\nClick the tabs in the interactive app below to see the charts with the Streamlit theme enabled and disabled.\n\nIf you're wondering if your own customizations will still be taken into account, don't worry! You can still make changes to your chart configurations. In other words, although we now enable the Streamlit theme by default, you can overwrite it with custom colors or fonts. For example, if you want a chart line to be green instead of the default red, you can do it!\n\nHere's an example of an Plotly chart where a custom color scale is defined and reflected:\n\n\n```\nimport plotly.express as px\nimport streamlit as st\n\nst.subhe","answer":"unction signature:\nst.plotly\\_chart(figure\\_or\\_data, use\\_container\\_width=False, sharing=\"streamlit\", \\*\\*kwargs)\n\nExample:\n```\nimport streamlit as st\nimport plotly.figure_factory as ff\nimport numpy as np\n\n# Add histogram data\nx1 = np.random.randn(200) - 2\nx2 = np.random.randn(200)\nx3 = np.random.randn(200) + 2\n\n# Group data together\nhist_data = [x1, x2, x3]\n\ngroup_labels = ['Group 1', 'Group 2', 'Group 3']\n\n# Create distplot with custom bin_size\nfig = ff.create_distplot(\n hist_data, group_labels, bin_size=[.1, .25, .5])\n\n# Plot!\nst.plotly_chart(fig, use_container_width=True)\n```\n\nTheming:\nPlotly charts are displayed using the Streamlit theme by default...The Streamlit theme is available from Streamlit 1.16.0 through the `theme=\"streamlit\"` keyword argument. To disable it, and use Plotly's native theme, use `theme=None` instead","question_idx":1,"row_idx":25,"model":"gpt-3.5-turbo","idx":25,"Template":0,"persona":"bot","response":"```\ndf = px.data.iris()\nfig = px.scatter(\n df,\n x=\"sepal_width\",\n y=\"sepal_length\",\n color=\"sepal_length\",\n color_continuous_scale=\"reds\",\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n st.plotly_chart(fig, theme=None, use_container_width=True)\n```\n```\nNotice how the custom color scale is still reflected in the chart, even when the Streamlit theme is enabled 👇\n\nFor many more examples of Plotly charts with and without the Streamlit theme, check out the [plotly.streamlit.app](https://plotly.streamlit.app).\n```","experiment_id":0,"question_embeddings":[0.088330105,0.011396006,-0.017542858,-0.08434498,-0.047787853,0.03425188,0.048996642,0.0034383428,-0.022393193,-0.023409048,-0.07357438,-0.077896774,0.026116539,-0.00085928355,0.039049085,-0.026642563,-0.097047776,-0.022016235,-0.08539825,-0.17395513,0.010976068,-0.05704131,-0.03725233,-0.06842565,-0.0044478704,0.0649463,0.031023948,0.040923957,0.07282005,-0.049106944,0.059667658,-0.0753585,0.062485617,-0.02494093,-0.007864315,-0.019300802,-0.036084615,0.051608577,-0.09109866,0.033572853,0.042465758,0.01174127,-0.019712325,-0.065684274,-0.017155608,0.08364792,-0.073342375,0.01874716,0.037283268,0.025831383,-0.043462474,-0.073857106,0.029871376,0.017697562,0.009775645,-0.036767107,-0.04120292,-0.06703686,0.07610773,-0.10925221,-0.04442994,-0.0074998676,0.022256946,-0.014896059,0.06088412,0.016017038,-0.012465867,0.049446587,0.08847953,-0.018837655,0.019807337,0.06478816,0.06848112,0.055087257,-0.07049523,-0.020874226,-0.011705072,0.048881352,-0.059627306,-0.05197535,-0.027297586,0.014144446,0.037603576,0.040695284,0.017761882,0.06532191,-0.06894137,0.013939522,-0.04712859,0.024932921,-0.062471792,0.066132456,0.002363949,-0.03655384,-0.052409384,0.07198713,0.09174018,-0.006315629,0.06124142,-0.023097236,0.040439002,-0.07812325,0.016205361,-0.014299262,0.07228006,-0.003125131,-0.02446053,0.09691148,0.025791425,-0.037827283,0.048649594,-0.042109657,0.016840104,-0.086937375,-0.017265989,0.075562194,-0.10699093,0.01211867,-0.06403345,0.018178374,0.061768565,-0.002032798,-0.05675274,-0.010576633,-0.034583665,-0.039890874,-0.029935757,-3.2848764e-33,0.0378979,-0.106998086,-0.040995043,0.04149618,0.065572456,0.039515913,-0.008075179,0.003411869,-0.02091417,-0.05122435,-0.005777524,0.037594054,-0.055417888,0.010974505,-0.08005184,-0.052646156,0.007957076,-0.024725603,-0.06924275,-0.037430324,-0.08051367,-0.023205118,0.052269068,-0.012416274,0.016556906,-0.020465432,0.04609017,-0.027405446,0.037574787,0.03561955,0.03827268,0.08577126,0.0042460887,0.014051184,0.05974666,-0.058780804,-0.048364103,0.040574744,-0.043581553,0.07378104,0.061412837,0.0014289903,-0.052190572,-0.00078052504,-0.057369288,0.04606968,0.06747937,-0.030284451,0.009257126,-0.025518835,0.04138671,0.08106319,0.0042691617,-0.014420229,0.11329392,-0.022430757,0.032329742,0.047505144,0.040817976,0.04313649,-0.024551831,0.15228917,0.034013808,0.01941502,0.06144809,-0.036756065,0.10396538,0.070308425,-0.006481227,-0.03454383,-0.00991815,0.037999697,0.016863624,-0.016421068,-0.025025293,-0.04278919,0.066235885,0.010628494,-0.052254688,-0.03445316,-0.01905931,-0.052874748,0.010571877,0.026651157,-0.089318834,0.03158032,0.05560046,0.031757142,-0.11445971,-0.09785465,-0.027041305,0.025731953,0.03934218,-0.10917421,0.0022965784,9.564032e-34,-0.06313915,0.09419001,-0.04081826,0.07181917,0.066276036,0.0030092914,0.13137865,0.035464074,0.045764312,0.051538132,-0.055806544,-0.0046785898,-0.124816924,0.017279215,-0.015864715,-0.040863328,0.0009500781,0.018876879,-0.05487937,-0.037517846,-0.08503278,0.03304914,-0.034198888,0.002668823,-0.04557246,0.050836373,-0.013927419,-0.005447964,0.017712409,0.019973949,0.027383726,0.037844945,-0.014945877,-0.04143812,-0.01959012,-0.105157845,0.06470922,0.013278265,-0.013803623,0.067147404,0.04178529,-0.0632891,-0.010079848,-0.08619708,-0.008960702,0.096153274,-0.035347067,0.06595369,-0.020878192,-0.016643418,-0.019682482,0.013243405,-0.032486048,0.08356432,0.07674347,-0.06361975,0.080223106,0.03534406,0.0060911328,0.0065864087,-0.060241528,-0.10307839,0.10199058,0.00088820775,0.030220982,-0.0011668602,0.0099102575,-0.060083468,-0.042249147,0.017135648,-0.0036030465,-0.0972523,0.07683787,-0.06330369,0.03142023,-0.0026465172,-0.008431761,0.06634554,-0.0038314487,0.010890359,-0.018100841,-0.015494008,0.036994852,0.060362976,0.057365444,0.003517775,-0.0029040098,-0.0502847,0.050799564,0.07383564,0.023432627,0.055715792,-0.02273529,0.058175955,0.08986104,-1.720074e-8,0.022305466,-0.070501976,-0.016909117,0.014119327,0.055804323,0.02039817,-0.06730445,0.059458356,0.035946358,-0.014027031,0.071772315,-0.022881763,-0.003811465,-0.057003707,-0.018651411,-0.04579891,-0.015629753,-0.020469574,0.013314239,0.035074934,-0.026234025,0.0120668635,0.0072116307,0.01317788,-0.08294273,0.02837273,0.017769746,-0.073891856,0.021844728,-0.05221814,-0.0060682157,0.030079223,0.063992664,-0.02636329,-0.026866086,-0.07240491,-0.15313517,0.049820986,-0.04309975,0.0044540553,0.008091409,0.01155717,-0.011134993,-0.015595453,-0.0044206656,0.031132616,0.021964429,0.08499096,-0.029608035,0.09432952,-0.10045928,-0.0016386824,0.045343123,-0.027784642,0.04225195,-0.077244245,-0.025754198,-0.062053796,0.017611738,-0.031203467,0.01756977,-0.025270505,-0.02455264,0.0032717404],"context_embeddings":[0.016982855,-0.025003677,-0.048720736,0.030192828,0.027741695,-0.037901856,-0.03407475,0.04990793,-0.059711836,-0.09270833,-0.021111587,0.013642712,-0.06988687,-0.009262903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{"question":"Can I create histograms with different bucket colors in Streamlit","document_title":"API reference","document_link":"https://docs.streamlit.io/1.4.0/library/api-reference/charts/st.plotly_chart#stplotly_chart","document_text":"## st.plotly\\_chart\n\nDisplay an interactive Plotly chart.\n\n\nPlotly is a charting library for Python. The arguments to this function\nclosely follow the ones for Plotly's plot() function. You can find\nmore about Plotly at <https://plot.ly/python>.\n\n\nTo show Plotly charts in Streamlit, call st.plotly\\_chart wherever you\nwould call Plotly's py.plot or py.iplot.\n\n\n\n\n| Function signature[[source]](https://github.com/streamlit/streamlit/blob/1.4.0/lib/streamlit/elements/plotly_chart.py#L42 \"View st.plotly_chart source code on GitHub\") |\n| --- |\n| st.plotly\\_chart(figure\\_or\\_data, use\\_container\\_width=False, sharing=\"streamlit\", \\*\\*kwargs) |\n| Parameters |\n| \n\nfigure\\_or\\_data\n(plotly.graph\\_objs.Figure, plotly.graph\\_objs.Data,)\n | \ndict/list of plotly.graph\\_objs.Figure/Data\nSee <https://plot.ly/python/> for examples of graph descriptions.\n |\n| \n\nuse\\_container\\_width\n(bool)\n | \nIf True, set the chart width to the column width. This takes\nprecedence over the figure's native width value.\n |\n| \n\nsharing\n({'streamlit', 'private', 'secret', 'public'})\n | \nUse 'streamlit' to insert the plot and all its dependencies\ndirectly in the Streamlit app using plotly's offline mode (default).\nUse any other sharing mode to send the chart to Plotly chart studio, which\nrequires an account. See <https://plotly.com/chart-studio/> for more information.\n |\n| \n\n\\*\\*kwargs\n(null)\n | \nAny argument accepted by Plotly's plot() function.\n |\n\n#### Example\n\n\n> \n> The example below comes straight from the examples at\n> <https://plot.ly/python>:\n> \n> \n> \n> ```\n> \n> import streamlit as st\n> import plotly.figure_factory as ff\n> import numpy as np\n> \n> # Add histogram data\n> x1 = np.random.randn(200) - 2\n> x2 = np.random.randn(200)\n> x3 = np.random.randn(200) + 2\n> \n> # Group data together\n> hist_data = [x1, x2, x3]\n> \n> group_labels = ['Group 1', 'Group 2', 'Group 3']\n> \n> # Create distplot with custom bin_size\n> fig = ff.create_distplot(\n> hist_data, group_labels, bin_size=[.1, .25, .5])\n> \n> # Plot!\n> st.plotly_chart(fig, use_container_width=True)\n> \n> ```\n> \n> \n> [(view standalone Streamlit app)](https://static.streamlit.io/0.56.0-xTAd/index.html?id=TuP96xX8JnsoQeUGAPjkGQ) \n> \n\n\n### Theming\n\nPlotly charts are displayed using the Streamlit theme by default. This theme is sleek, user-friendly, and incorporates Streamlit's color palette. The added benefit is that your charts better integrate with the rest of your app's design.\n\nThe Streamlit theme is available from Streamlit 1.16.0 through the `theme=\"streamlit\"` keyword argument. To disable it, and use Plotly's native theme, use `theme=None` instead.\n\nLet's look at an example of charts with the Streamlit theme and the native Plotly theme:\n\n\n```\nimport plotly.express as px\nimport streamlit as st\n\ndf = px.data.gapminder()\n\nfig = px.scatter(\n df.query(\"year==2007\"),\n x=\"gdpPercap\",\n y=\"lifeExp\",\n size=\"pop\",\n color=\"continent\",\n hover_name=\"country\",\n log_x=True,\n size_max=60,\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n # Use the Streamlit theme.\n # This is the default. So you can also omit the theme argument.\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n # Use the native Plotly theme.\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\n```\nClick the tabs in the interactive app below to see the charts with the Streamlit theme enabled and disabled.\n\nIf you're wondering if your own customizations will still be taken into account, don't worry! You can still make changes to your chart configurations. In other words, although we now enable the Streamlit theme by default, you can overwrite it with custom colors or fonts. For example, if you want a chart line to be green instead of the default red, you can do it!\n\nHere's an example of an Plotly chart where a custom color scale is defined and reflected:\n\n\n```\nimport plotly.express as px\nimport streamlit as st\n\nst.subheader(\"Define a custo","answer":"unction signature:\nst.plotly_chart(figure_or_data, use_container_width=False, sharing=\"streamlit\", **kwargs)\n\nParameters:\nfigure_or_data (plotly.graph_objs.Figure, plotly.graph_objs.Data,) | dict/list of plotly.graph_objs.Figure/Data\nuse_container_width (bool)\nsharing ({'streamlit', 'private', 'secret', 'public'})\n**kwargs (null)\n\nExample:\nimport streamlit as st\nimport plotly.figure_factory as ff\nimport numpy as np\n\n# Add histogram data\nx1 = np.random.randn(200) - 2\nx2 = np.random.randn(200)\nx3 = np.random.randn(200) + 2\n\n# Group data together\nhist_data = [x1, x2, x3]\n\ngroup_labels = ['Group 1', 'Group 2', 'Group 3']\n\n# Create distplot with custom bin_size\nfig = ff.create_distplot(\n hist_data, group_labels, bin_size=[.1, .25, .5])\n\n# Plot!\nst.plotly_chart(fig, use_container_width=True)\n\nTheming:\nPlotly charts are displayed using the Streamlit theme by default. This theme is sleek, user-friendly, and incorporates Streamlit's color palette. The added benefit is that your charts better integrate with the rest of your app's design.\nThe Streamlit theme is available from Streamlit 1.16.0 through the 'theme=\"streamlit\"' keyword argument. To disable it, and use Plotly's native theme, use 'theme=None' instead","question_idx":0,"row_idx":26,"model":"gpt-3.5-turbo","idx":26,"Template":0,"persona":"bot","response":"\"When using session state to update widgets or values in your script, you need to use the unique key you assigned to the widget, **not** the variable that you assigned your widget to. In the example code block below, the unique *key* assigned to the slider widget is `slider`, and the *variable* the widget is assigned to is `slide_val`.\"\n\n\"To have the slider's value update on the button click, you need to use a [callback function](https://docs.streamlit.io/library/api-reference/session-state#use-callbacks-to-update-session-state) with the `on_click` parameter of [`st.button`](https://docs.streamlit.io/library/api-reference/widgets/st.button):\"\n\n```\n# the callback function for the button will add 1 to the\n# slider value up to 10\ndef plus_one():\n if st.session_state[\"slider\"] < 10:\n st.session_state.slider += 1\n else:\n pass\n return\n\n# when creating the button, assign the name of your callback\n# function to the on_click parameter\nadd_one = st.button(\"Add one to the slider\", on_click=plus_one, key=\"add_one\")\n\n# create the slider\nslide_val = st.slider(\"Pick a number\", 0, 10, key=\"slider\")\n```","experiment_id":0,"question_embeddings":[0.06357269,-0.0065760594,-0.020345902,-0.08352584,-0.047350194,0.036682703,0.03675301,-0.020481193,-0.023199504,-0.023003703,-0.08344998,-0.046929147,0.030856805,0.0040366957,0.055860724,-0.027778918,-0.08961629,0.0041082106,-0.090726905,-0.14028054,0.005671198,-0.04953355,-0.056541827,-0.07677412,-0.0054286676,0.046765037,0.028512418,0.05420102,0.068443455,-0.0604626,0.054457724,-0.07275235,0.049726702,-0.022302784,-0.0041490933,-0.02186213,-0.03887204,0.058403235,-0.08978373,0.037947502,0.038772896,0.015465372,-0.031523794,-0.051518813,-0.026647044,0.0863903,-0.07547597,0.013137831,0.012855303,0.022156958,-0.033148255,-0.07180802,0.036730874,0.022195915,0.015626686,-0.029947298,-0.04305715,-0.06709682,0.05954109,-0.08123926,-0.05617996,-0.008180384,0.022568718,-0.0036913706,0.09570576,0.03136336,-0.015436422,0.03444204,0.09311254,-0.02689361,0.03140673,0.06345534,0.08536748,0.048517168,-0.06511003,0.0054839347,-0.012848926,0.05942965,-0.06755942,-0.053685118,-0.027762018,0.008932237,0.040417593,0.022191966,0.011978196,0.054522794,-0.072129376,0.014587649,-0.04637386,0.02310457,-0.06725896,0.06178685,0.024150467,-0.049363486,-0.061521318,0.055563316,0.08960045,-0.01576581,0.057299186,-0.02973093,0.042051695,-0.06689739,0.007888104,-0.022333588,0.08404724,-0.021441972,-0.02634069,0.09471672,0.018893978,-0.03912352,0.0329555,-0.03708901,0.03689426,-0.09556095,-0.009662683,0.06899001,-0.11976706,0.0066234786,-0.06276309,0.017529482,0.064207785,-0.01157287,-0.040234894,-0.015450808,-0.0153679075,-0.052646134,-0.032788604,-2.7589148e-33,0.03576235,-0.10662839,-0.04067808,0.029993126,0.063296854,0.04668259,-0.012749555,0.005248918,-0.010436894,-0.07561844,-0.011633145,0.05444743,-0.048320852,0.014772509,-0.07199935,-0.014760617,0.021598626,-0.017174078,-0.05955723,-0.03472137,-0.07610088,-0.048029725,0.038275547,-0.024732482,0.02252993,-0.014710533,0.053196922,-0.01815156,0.046866003,0.038138613,0.023503724,0.07431182,-0.010030737,0.018859217,0.054400813,-0.051315624,-0.05778552,0.052278083,-0.04012966,0.07762834,0.07195341,0.011121125,-0.05060351,0.012136496,-0.07420707,0.04311224,0.07492402,-0.04081308,-0.018771872,-0.033988312,0.045980997,0.08672062,-0.005062198,-0.025109446,0.12977187,-0.016560083,0.029968856,0.042827725,0.067344815,0.04638003,-0.035595536,0.14303884,0.032466277,0.02497015,0.050941344,-0.024447702,0.10157372,0.0778076,0.00053819915,-0.031346135,-0.008758584,0.036722686,-0.0015840823,-0.020259231,-0.015971852,-0.04298156,0.07306846,0.022992812,-0.034721397,-0.030194966,-0.014201621,-0.043520536,0.010887479,0.03231367,-0.087124325,0.027420446,0.06266317,0.027834242,-0.12047557,-0.087669924,-0.020153027,0.031243222,0.027246276,-0.10769241,-0.0072499076,9.307464e-34,-0.080400184,0.08192685,-0.04577184,0.078311056,0.0642137,0.012169457,0.13736194,0.022015871,0.03278156,0.05398484,-0.035939127,-0.0022418867,-0.1290434,0.008012245,-0.017896941,-0.030848654,-0.012321777,0.024660239,-0.06502408,-0.03576453,-0.10739129,0.0059367563,-0.038558144,-0.0053904355,-0.029615968,0.0663225,-0.009698477,0.002204676,0.016577557,0.016558561,0.032411598,0.025009926,-0.023183554,-0.0548188,-0.013516646,-0.11561085,0.06011747,0.0032648896,-0.019577319,0.08061338,0.036386278,-0.06483969,-0.009423049,-0.067994475,-0.0059552514,0.07898494,-0.030586459,0.057788316,-0.011511716,-0.007741939,-0.02863135,0.03207052,-0.025858352,0.076669626,0.07364335,-0.0601048,0.078869574,0.049763173,0.0026653612,0.007474002,-0.052608352,-0.10268198,0.102147534,-0.019444479,0.051910717,-0.002900365,0.015770577,-0.067796655,-0.029883914,0.022909926,0.009268357,-0.121122375,0.067859925,-0.059911028,0.045639582,-0.009814225,0.014831371,0.059833657,-0.014894034,-0.0022807359,-0.027649293,-0.014831903,0.052625373,0.056469955,0.07557365,0.0031232166,-0.011547768,-0.05443782,0.06120629,0.07160346,0.032031905,0.059437387,-0.012607803,0.04696337,0.07722856,-1.6495452e-8,0.014486489,-0.048435584,0.003250121,0.028159982,0.031189898,0.0023627344,-0.070192665,0.056730375,0.03496575,0.011610652,0.06183044,-0.027920958,-0.0121314,-0.052380722,-0.020452451,-0.04563529,0.017542096,-0.03620699,0.0011459879,0.041698407,-0.028633622,0.03700075,-0.00061687466,0.021913622,-0.07560133,0.03271757,0.017450893,-0.07702778,0.020872569,-0.06213861,-0.0038546,0.04003318,0.069114655,-0.0065786745,-0.016454224,-0.09361585,-0.16091056,0.058383908,-0.052135747,0.010157994,0.016596014,-0.0043797004,-0.014434132,0.0061570127,0.0016335461,0.02599054,0.034217644,0.056406163,-0.020769285,0.08216932,-0.10429248,0.004765623,0.04851646,-0.022152325,0.04684329,-0.058515728,-0.017122269,-0.064585134,0.008293409,-0.034130603,0.024276521,-0.04850379,-0.00979301,-0.0031762286],"context_embeddings":[0.01773843,-0.025135072,-0.048691485,0.030078726,0.027537169,-0.037590545,-0.03419359,0.050082006,-0.060125668,-0.09300214,-0.021205166,0.013854705,-0.070095606,-0.009250988,0.021089613,-0.07803596,0.0062000165,-0.07568778,-0.0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{"question":"Can I create histograms with different bucket colors in Streamlit","document_title":"API reference","document_link":"https://docs.streamlit.io/1.10.0/library/api-reference/charts/st.plotly_chart#stplotly_chart","document_text":"## st.plotly\\_chart\n\nDisplay an interactive Plotly chart.\n\n\nPlotly is a charting library for Python. The arguments to this function\nclosely follow the ones for Plotly's plot() function. You can find\nmore about Plotly at <https://plot.ly/python>.\n\n\nTo show Plotly charts in Streamlit, call st.plotly\\_chart wherever you\nwould call Plotly's py.plot or py.iplot.\n\n\n\n\n| Function signature[[source]](https://github.com/streamlit/streamlit/blob/1.10.0/lib/streamlit/elements/plotly_chart.py#L67 \"View st.plotly_chart source code on GitHub\") |\n| --- |\n| st.plotly\\_chart(figure\\_or\\_data, use\\_container\\_width=False, sharing=\"streamlit\", \\*\\*kwargs) |\n| Parameters |\n| \n\nfigure\\_or\\_data\n(plotly.graph\\_objs.Figure, plotly.graph\\_objs.Data,)\n | \ndict/list of plotly.graph\\_objs.Figure/Data\nSee <https://plot.ly/python/> for examples of graph descriptions.\n |\n| \n\nuse\\_container\\_width\n(bool)\n | \nIf True, set the chart width to the column width. This takes\nprecedence over the figure's native width value.\n |\n| \n\nsharing\n({'streamlit', 'private', 'secret', 'public'})\n | \nUse 'streamlit' to insert the plot and all its dependencies\ndirectly in the Streamlit app using plotly's offline mode (default).\nUse any other sharing mode to send the chart to Plotly chart studio, which\nrequires an account. See <https://plotly.com/chart-studio/> for more information.\n |\n| \n\n\\*\\*kwargs\n(null)\n | \nAny argument accepted by Plotly's plot() function.\n |\n\n#### Example\n\n\n> \n> The example below comes straight from the examples at\n> <https://plot.ly/python>:\n> \n> \n> \n> ```\n> \n> import streamlit as st\n> import plotly.figure_factory as ff\n> import numpy as np\n> \n> # Add histogram data\n> x1 = np.random.randn(200) - 2\n> x2 = np.random.randn(200)\n> x3 = np.random.randn(200) + 2\n> \n> # Group data together\n> hist_data = [x1, x2, x3]\n> \n> group_labels = ['Group 1', 'Group 2', 'Group 3']\n> \n> # Create distplot with custom bin_size\n> fig = ff.create_distplot(\n> hist_data, group_labels, bin_size=[.1, .25, .5])\n> \n> # Plot!\n> st.plotly_chart(fig, use_container_width=True)\n> \n> ```\n> \n> \n> [(view standalone Streamlit app)](https://share.streamlit.io/streamlit/docs/main/python/api-examples-source/charts.plotly_chart.py) \n> \n\n\n### Theming\n\nPlotly charts are displayed using the Streamlit theme by default. This theme is sleek, user-friendly, and incorporates Streamlit's color palette. The added benefit is that your charts better integrate with the rest of your app's design.\n\nThe Streamlit theme is available from Streamlit 1.16.0 through the `theme=\"streamlit\"` keyword argument. To disable it, and use Plotly's native theme, use `theme=None` instead.\n\nLet's look at an example of charts with the Streamlit theme and the native Plotly theme:\n\n\n```\nimport plotly.express as px\nimport streamlit as st\n\ndf = px.data.gapminder()\n\nfig = px.scatter(\n df.query(\"year==2007\"),\n x=\"gdpPercap\",\n y=\"lifeExp\",\n size=\"pop\",\n color=\"continent\",\n hover_name=\"country\",\n log_x=True,\n size_max=60,\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n # Use the Streamlit theme.\n # This is the default. So you can also omit the theme argument.\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n # Use the native Plotly theme.\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\n```\nClick the tabs in the interactive app below to see the charts with the Streamlit theme enabled and disabled.\n\nIf you're wondering if your own customizations will still be taken into account, don't worry! You can still make changes to your chart configurations. In other words, although we now enable the Streamlit theme by default, you can overwrite it with custom colors or fonts. For example, if you want a chart line to be green instead of the default red, you can do it!\n\nHere's an example of an Plotly chart where a custom color scale is defined and reflected:\n\n\n```\nimport plotly.express as px\nimport streamlit as st\n\nst.subh","answer":"unction signature\nst.plotly_chart(figure_or_data, use_container_width=False, sharing=\"streamlit\", \\*\\*kwargs)\n\nParameters\n\nfigure_or_data\n(plotly.graph_objs.Figure, plotly.graph_objs.Data,)\n | \ndict/list of plotly.graph_objs.Figure/Data\n\nuse_container_width\n(bool)\n | \nIf True, set the chart width to the column width. This takes\nprecedence over the figure's native width value.\n\nsharing\n({'streamlit', 'private', 'secret', 'public'})\n | \nUse 'streamlit' to insert the plot and all its dependencies\ndirectly in the Streamlit app using plotly's offline mode (default).\nUse any other sharing mode to send the chart to Plotly chart studio, which\nrequires an account. See <https://plotly.com/chart-studio/> for more information.\n\n\\*\\*kwargs\n(null)\n | \nAny argument accepted by Plotly's plot() function","question_idx":0,"row_idx":27,"model":"gpt-3.5-turbo","idx":27,"Template":0,"persona":"bot","response":"### Session State and Widget State association\n\nSession State provides the functionality to store variables across reruns. Widget state (i.e. the value of a widget) is also stored in a session.\n\nFor simplicity, we have *unified* this information in one place. i.e. the Session State. This convenience feature makes it super easy to read or write to the widget's state anywhere in the app's code. Session State variables mirror the widget value using the `key` argument.\n\nWe illustrate this with the following example. Let's say we have an app with a slider to represent temperature in Celsius. We can **set** and **get** the value of the temperature widget by using the Session State API, as follows:\n\n```\nimport streamlit as st\n\nif \"celsius\" not in st.session_state:\n # set the initial default value of the slider widget\n st.session_state.celsius = 50.0\n\nst.slider(\n \"Temperature in Celsius\",\n min_value=-100.0,\n max_value=100.0,\n key=\"celsius\"\n)\n\n# This will get the value of the slider widget\nst.write(st.session_state.celsius)\n\n```\n\n### Serializable Session State\n\nSerialization refers to the process of converting an object or data structure into a format that can be persisted and shared, and allowing you to recover the data’s original structure. Python’s built-in [pickle](https://docs.python.org/3/library/pickle.html) module serializes Python objects to a byte stream (\"pickling\") and deserializes the stream into an object (\"unpickling\").\n\nBy default, Streamlit’s [Session State](https://docs.streamlit.io/library/advanced-features/session-state) allows you to persist any Python object for the duration of the session, irrespective of the object’s pickle-serializability. This property lets you store Python primitives such as integers, floating-point numbers, complex numbers and booleans, dataframes, and even [lambdas](https://docs.python.org/3/reference/expressions.html#lambda) returned by functions. However, some execution environments may require serializing all data in Session State, so it may be useful to detect incompatibility during development, or when the execution environment will stop supporting it in the future.\n\nTo that end, Streamlit provides a `runner.enforceSerializableSessionState` [configuration option](https://docs.streamlit.io/library/advanced-features/configuration) that, when set to `true`, only allows pickle-serializable objects in Session State. To enable the option, either create a global or project config file with the following or use it as a command-line flag:\n\n```\n# .streamlit/config.toml\n[runner]\nenforceSerializableSessionState = true\n\n```\n\nBy \"*pickle-serializable*\", we mean calling `pickle.dumps(obj)` should not raise a [`PicklingError`](https://docs.python.org/3/library/pickle.html#pickle.PicklingError) exception. When the config option is enabled, adding unserializable data to session state should result in an exception. E.g.,\n\n```\nimport streamlit as st\n\ndef unserializable_data():\n return lambda x: x\n\n#👇 results in an exception when enforceSerializableSessionState is on\nst.session_state.unserializable = unserializable_data()\n\n```\n\n### Caveats and limitations\n\nHere are some limitations to keep in mind when using Session State:\n\n* Session State exists for as long as the tab is open and connected to the Streamlit server. As soon as you close the tab, 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{"question":"How can I create histograms with different bucket colors in Streamlit","document_title":"Create an app","document_link":"https://docs.streamlit.io/library/get-started/create-an-app#plot-data-on-a-map","document_text":"## Draw a histogram\n\nNow that you've had a chance to take a look at the dataset and observe what's\navailable, let's take things a step further and draw a histogram to see what\nUber's busiest hours are in New York City.\n\n1. To start, let's add a subheader just below the raw data section:\n\n\n```\nst.subheader('Number of pickups by hour')\n\n```\n2. Use NumPy to generate a histogram that breaks down pickup times binned by\nhour:\n\n\n```\nhist_values = np.histogram(\n data[DATE_COLUMN].dt.hour, bins=24, range=(0,24))[0]\n\n```\n3. Now, let's use Streamlit's\n[`st.bar_chart()`](https://docs.streamlit.io/library/api-reference/charts/st.bar_chart) method to draw this\nhistogram.\n\n\n```\nst.bar_chart(hist_values)\n\n```\n4. Save your script. This histogram should show up in your app right away.\nAfter a quick review, it looks like the busiest time is 17:00 (5 P.M.).\n\nTo draw this diagram we used Streamlit's native `bar_chart()` method, but it's\nimportant to know that Streamlit supports more complex charting libraries like\nAltair, Bokeh, Plotly, Matplotlib and more. For a full list, see\n[supported charting libraries](https://docs.streamlit.io/library/api-reference/charts).\n\n","answer":". Use NumPy to generate a histogram that breaks down pickup times binned by\nhour:\n\n\n```\nhist_values = np.histogram(\n data[DATE_COLUMN].dt.hour, bins=24, range=(0,24))[0]\n\n```\n3. Now, let's use Streamlit's\n[`st.bar_chart()`](https://docs.streamlit.io/library/api-reference/charts/st.bar_chart) method to draw this\nhistogram.\n\n\n```\nst.bar_chart(hist_values)\n\n``","question_idx":1,"row_idx":28,"model":"gpt-3.5-turbo","idx":28,"Template":0,"persona":"bot","response":"```\nAs described in [Command-line options](https://docs.streamlit.io/library/advanced-features/cli), you can\nview all available configuration option using:\n\n\nstreamlit config show\n\n\nThe command above will print something like this:\n```\n\n```\n[global]\n\n# By default, Streamlit checks if the Python watchdog module is available and, if not, prints a warning asking for you to install it. The watchdog module is not required, but highly recommended. It improves Streamlit's ability to detect changes to files in your filesystem.\n# If you'd like to turn off this warning, set this to True.\n# Default: false\ndisableWatchdogWarning = false\n\n# If True, will show a warning when you run a Streamlit-enabled script via \"python my_script.py\".\n# Default: true\nshowWarningOnDirectExecution = true\n\n# DataFrame serialization.\n# Acceptable values: - 'legacy': Serialize DataFrames using Streamlit's custom format. Slow but battle-tested. - 'arrow': Serialize DataFrames using Apache Arrow. Much faster and versatile.\n# Default: \"arrow\"\ndataFrameSerialization = \"arrow\"\n\n\n[logger]\n\n# Level of logging: 'error', 'warning', 'info', or 'debug'.\n# Default: 'info'\nlevel = \"info\"\n\n# String format for logging messages. If logger.datetimeFormat is set, logger messages will default to `%(asctime)s.%(msecs)03d %(message)s`. See [Python's documentation](https://docs.python.org/2.6/library/logging.html#formatter-objects) for available attributes.\n# Default: \"%(asctime)s %(message)s\"\nmessageFormat = \"%(asctime)s %(message)s\"\n\n\n[client]\n\n# Whether to enable st.cache.\n# Default: true\ncaching = true\n\n# If false, makes your Streamlit script not draw to a Streamlit app.\n# Default: true\ndisplayEnabled = true\n\n# Controls whether uncaught app exceptions are displayed in the browser. By default, this is set to True and Streamlit displays app exceptions and associated tracebacks in the browser.\n# If set to False, an exception will result in a generic message being shown in the browser, and exceptions and tracebacks will be printed to the console only.\n# Default: true\nshowErrorDetails = true\n\n# Change the visibility of items in the toolbar, options menu, and settings dialog (top right of the app).\n# Allowed values:\n# \"auto\" : Show the developer options if the app is accessed through localhost and hide them otherwise.\n# \"developer\" : Show the developer options.\n# \"viewer\" : Hide the developer options.\n# \"minimal\" : Show only options set externally (e.g. through Streamlit Community Cloud) or through st.set_page_config. If there are no options left, hide the menu.\n# Default: \"auto\"\ntoolbarMode = \"auto\"\n\n\n[runner]\n\n# Allows you to type a variable or string by itself in a single line of Python code to write it to the app.\n# Default: true\nmagicEnabled = true\n\n# Install a Python tracer to allow you to stop or pause your script at any point and introspect it. As a side-effect, this slows down your script's execution.\n# Default: false\ninstallTracer = false\n\n# Sets the MPLBACKEND environment variable to Agg inside Streamlit to prevent Python crashing.\n# Default: true\nfixMatplotlib = true\n\n# Run the Python Garbage Collector after each script execution. This can help avoid excess memory use in Streamlit apps, but could introduce delay in rerunning the app script for high-memory-use applications.\n# Default: true\npostScriptGC = true\n\n# Handle script rerun requests immediately, rather than waiting for script execution to reach a yield point. This makes Streamlit much more responsive to user interaction, but it can lead to race conditions in apps that mutate session_state data outside of explicit session_state assignment statements.\n# Default: true\nfastReruns = true\n\n# Raise an exception after adding unserializable data to Session State. Some execution environments may require serializing all data in Session State, so it may be useful to detect incompatibility during development, or when the execution environment will stop supporting it\n```","experiment_id":0,"question_embeddings":[0.088330105,0.011396006,-0.017542858,-0.08434498,-0.047787853,0.03425188,0.048996642,0.0034383428,-0.022393193,-0.023409048,-0.07357438,-0.077896774,0.026116539,-0.00085928355,0.039049085,-0.026642563,-0.097047776,-0.022016235,-0.08539825,-0.17395513,0.010976068,-0.05704131,-0.03725233,-0.06842565,-0.0044478704,0.0649463,0.031023948,0.040923957,0.07282005,-0.049106944,0.059667658,-0.0753585,0.062485617,-0.02494093,-0.007864315,-0.019300802,-0.036084615,0.051608577,-0.09109866,0.033572853,0.042465758,0.01174127,-0.019712325,-0.065684274,-0.017155608,0.08364792,-0.073342375,0.01874716,0.037283268,0.025831383,-0.043462474,-0.073857106,0.029871376,0.017697562,0.009775645,-0.036767107,-0.04120292,-0.06703686,0.07610773,-0.10925221,-0.04442994,-0.0074998676,0.022256946,-0.014896059,0.06088412,0.016017038,-0.012465867,0.049446587,0.08847953,-0.018837655,0.019807337,0.06478816,0.06848112,0.055087257,-0.07049523,-0.020874226,-0.011705072,0.048881352,-0.059627306,-0.05197535,-0.027297586,0.014144446,0.037603576,0.040695284,0.017761882,0.06532191,-0.06894137,0.013939522,-0.04712859,0.024932921,-0.062471792,0.066132456,0.002363949,-0.03655384,-0.052409384,0.07198713,0.09174018,-0.006315629,0.06124142,-0.023097236,0.040439002,-0.07812325,0.016205361,-0.014299262,0.07228006,-0.003125131,-0.02446053,0.09691148,0.025791425,-0.037827283,0.048649594,-0.042109657,0.016840104,-0.086937375,-0.017265989,0.075562194,-0.10699093,0.01211867,-0.06403345,0.018178374,0.061768565,-0.002032798,-0.05675274,-0.010576633,-0.034583665,-0.039890874,-0.029935757,-3.2848764e-33,0.0378979,-0.106998086,-0.040995043,0.04149618,0.065572456,0.039515913,-0.008075179,0.003411869,-0.02091417,-0.05122435,-0.005777524,0.037594054,-0.055417888,0.010974505,-0.08005184,-0.052646156,0.007957076,-0.024725603,-0.06924275,-0.037430324,-0.08051367,-0.023205118,0.052269068,-0.012416274,0.016556906,-0.020465432,0.04609017,-0.027405446,0.037574787,0.03561955,0.03827268,0.08577126,0.0042460887,0.014051184,0.05974666,-0.058780804,-0.048364103,0.040574744,-0.043581553,0.07378104,0.061412837,0.0014289903,-0.052190572,-0.00078052504,-0.057369288,0.04606968,0.06747937,-0.030284451,0.009257126,-0.025518835,0.04138671,0.08106319,0.0042691617,-0.014420229,0.11329392,-0.022430757,0.032329742,0.047505144,0.040817976,0.04313649,-0.024551831,0.15228917,0.034013808,0.01941502,0.06144809,-0.036756065,0.10396538,0.070308425,-0.006481227,-0.03454383,-0.00991815,0.037999697,0.016863624,-0.016421068,-0.025025293,-0.04278919,0.066235885,0.010628494,-0.052254688,-0.03445316,-0.01905931,-0.052874748,0.010571877,0.026651157,-0.089318834,0.03158032,0.05560046,0.031757142,-0.11445971,-0.09785465,-0.027041305,0.025731953,0.03934218,-0.10917421,0.0022965784,9.564032e-34,-0.06313915,0.09419001,-0.04081826,0.07181917,0.066276036,0.0030092914,0.13137865,0.035464074,0.045764312,0.051538132,-0.055806544,-0.0046785898,-0.124816924,0.017279215,-0.015864715,-0.040863328,0.0009500781,0.018876879,-0.05487937,-0.037517846,-0.08503278,0.03304914,-0.034198888,0.002668823,-0.04557246,0.050836373,-0.013927419,-0.005447964,0.017712409,0.019973949,0.027383726,0.037844945,-0.014945877,-0.04143812,-0.01959012,-0.105157845,0.06470922,0.013278265,-0.013803623,0.067147404,0.04178529,-0.0632891,-0.010079848,-0.08619708,-0.008960702,0.096153274,-0.035347067,0.06595369,-0.020878192,-0.016643418,-0.019682482,0.013243405,-0.032486048,0.08356432,0.07674347,-0.06361975,0.080223106,0.03534406,0.0060911328,0.0065864087,-0.060241528,-0.10307839,0.10199058,0.00088820775,0.030220982,-0.0011668602,0.0099102575,-0.060083468,-0.042249147,0.017135648,-0.0036030465,-0.0972523,0.07683787,-0.06330369,0.03142023,-0.0026465172,-0.008431761,0.06634554,-0.0038314487,0.010890359,-0.018100841,-0.015494008,0.036994852,0.060362976,0.057365444,0.003517775,-0.0029040098,-0.0502847,0.050799564,0.07383564,0.023432627,0.055715792,-0.02273529,0.058175955,0.08986104,-1.720074e-8,0.022305466,-0.070501976,-0.016909117,0.014119327,0.055804323,0.02039817,-0.06730445,0.059458356,0.035946358,-0.014027031,0.071772315,-0.022881763,-0.003811465,-0.057003707,-0.018651411,-0.04579891,-0.015629753,-0.020469574,0.013314239,0.035074934,-0.026234025,0.0120668635,0.0072116307,0.01317788,-0.08294273,0.02837273,0.017769746,-0.073891856,0.021844728,-0.05221814,-0.0060682157,0.030079223,0.063992664,-0.02636329,-0.026866086,-0.07240491,-0.15313517,0.049820986,-0.04309975,0.0044540553,0.008091409,0.01155717,-0.011134993,-0.015595453,-0.0044206656,0.031132616,0.021964429,0.08499096,-0.029608035,0.09432952,-0.10045928,-0.0016386824,0.045343123,-0.027784642,0.04225195,-0.077244245,-0.025754198,-0.062053796,0.017611738,-0.031203467,0.01756977,-0.025270505,-0.02455264,0.0032717404],"context_embeddings":[0.10449726,0.00020120523,0.00030689867,0.012737274,-0.034894396,-0.024273962,0.012115382,-0.0051147924,-0.07086552,-0.04101765,-0.051549047,-0.04598007,-0.026155986,-0.012219195,0.02462915,-0.0027154824,-0.009507422,-0.0985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{"question":"Can I create histograms with different bucket colors in Streamlit","document_title":"Create an app","document_link":"https://docs.streamlit.io/library/get-started/create-an-app#plot-data-on-a-map","document_text":"## Draw a histogram\n\nNow that you've had a chance to take a look at the dataset and observe what's\navailable, let's take things a step further and draw a histogram to see what\nUber's busiest hours are in New York City.\n\n1. To start, let's add a subheader just below the raw data section:\n\n\n```\nst.subheader('Number of pickups by hour')\n\n```\n2. Use NumPy to generate a histogram that breaks down pickup times binned by\nhour:\n\n\n```\nhist_values = np.histogram(\n data[DATE_COLUMN].dt.hour, bins=24, range=(0,24))[0]\n\n```\n3. Now, let's use Streamlit's\n[`st.bar_chart()`](https://docs.streamlit.io/library/api-reference/charts/st.bar_chart) method to draw this\nhistogram.\n\n\n```\nst.bar_chart(hist_values)\n\n```\n4. Save your script. This histogram should show up in your app right away.\nAfter a quick review, it looks like the busiest time is 17:00 (5 P.M.).\n\nTo draw this diagram we used Streamlit's native `bar_chart()` method, but it's\nimportant to know that Streamlit supports more complex charting libraries like\nAltair, Bokeh, Plotly, Matplotlib and more. For a full list, see\n[supported charting libraries](https://docs.streamlit.io/library/api-reference/charts).\n\n","answer":". Use NumPy to generate a histogram that breaks down pickup times binned by\nhour:\n\n\n```\nhist_values = np.histogram(\n data[DATE_COLUMN].dt.hour, bins=24, range=(0,24))[0]\n\n```\n3. Now, let's use Streamlit's\n[`st.bar_chart()`](https://docs.streamlit.io/library/api-reference/charts/st.bar_chart) method to draw this\nhistogram.\n\n\n```\nst.bar_chart(hist_values)\n\n``","question_idx":0,"row_idx":29,"model":"gpt-3.5-turbo","idx":29,"Template":0,"persona":"bot","response":"Function signature:\nst.plotly\\_chart(figure\\_or\\_data, use\\_container\\_width=False, sharing=\"streamlit\", \\*\\*kwargs)\n\nParameters:\n- figure\\_or\\_data (plotly.graph\\_objs.Figure, plotly.graph\\_objs.Data, dict/list of plotly.graph\\_objs.Figure/Data): See <https://plot.ly/python/> for examples of graph descriptions.\n- use\\_container\\_width (bool): If True, set the chart width to the column width. This takes precedence over the figure's native width value.\n- sharing ({'streamlit', 'private', 'secret', 'public'}): Use 'streamlit' to insert the plot and all its dependencies directly in the Streamlit app using plotly's offline mode (default). Use any other sharing mode to send the chart to Plotly chart studio, which requires an account. See <https://plotly.com/chart-studio/> for more information.\n- \\*\\*kwargs (null): Any argument accepted by Plotly's plot() function.\n\nExample:\n```\nimport streamlit as st\nimport plotly.figure_factory as ff\nimport numpy as np\n\n# Add histogram data\nx1 = np.random.randn(200) - 2\nx2 = np.random.randn(200)\nx3 = np.random.randn(200) + 2\n\n# Group data together\nhist_data = [x1, x2, x3]\n\ngroup_labels = ['Group 1', 'Group 2', 'Group 3']\n\n# Create distplot with custom bin_size\nfig = ff.create_distplot(\n hist_data, group_labels, bin_size=[.1, .25, .5])\n\n# Plot!\nst.plotly_chart(fig, use_container_width=True)\n```\n\nTheming:\nPlotly charts are displayed using the Streamlit theme by default. This theme is sleek, user-friendly, and incorporates Streamlit's color palette. The added benefit is that your charts better integrate with the rest of your app's design. The Streamlit theme is available from Streamlit 1.16.0 through the `theme=\"streamlit\"` keyword argument. To disable it, and use Plotly's native theme, use `theme=None` instead.","experiment_id":0,"question_embeddings":[0.06357269,-0.0065760594,-0.020345902,-0.08352584,-0.047350194,0.036682703,0.03675301,-0.020481193,-0.023199504,-0.023003703,-0.08344998,-0.046929147,0.030856805,0.0040366957,0.055860724,-0.027778918,-0.08961629,0.0041082106,-0.090726905,-0.14028054,0.005671198,-0.04953355,-0.056541827,-0.07677412,-0.0054286676,0.046765037,0.028512418,0.05420102,0.068443455,-0.0604626,0.054457724,-0.07275235,0.049726702,-0.022302784,-0.0041490933,-0.02186213,-0.03887204,0.058403235,-0.08978373,0.037947502,0.038772896,0.015465372,-0.031523794,-0.051518813,-0.026647044,0.0863903,-0.07547597,0.013137831,0.012855303,0.022156958,-0.033148255,-0.07180802,0.036730874,0.022195915,0.015626686,-0.029947298,-0.04305715,-0.06709682,0.05954109,-0.08123926,-0.05617996,-0.008180384,0.022568718,-0.0036913706,0.09570576,0.03136336,-0.015436422,0.03444204,0.09311254,-0.02689361,0.03140673,0.06345534,0.08536748,0.048517168,-0.06511003,0.0054839347,-0.012848926,0.05942965,-0.06755942,-0.053685118,-0.027762018,0.008932237,0.040417593,0.022191966,0.011978196,0.054522794,-0.072129376,0.014587649,-0.04637386,0.02310457,-0.06725896,0.06178685,0.024150467,-0.049363486,-0.061521318,0.055563316,0.08960045,-0.01576581,0.057299186,-0.02973093,0.042051695,-0.06689739,0.007888104,-0.022333588,0.08404724,-0.021441972,-0.02634069,0.09471672,0.018893978,-0.03912352,0.0329555,-0.03708901,0.03689426,-0.09556095,-0.009662683,0.06899001,-0.11976706,0.0066234786,-0.06276309,0.017529482,0.064207785,-0.01157287,-0.040234894,-0.015450808,-0.0153679075,-0.052646134,-0.032788604,-2.7589148e-33,0.03576235,-0.10662839,-0.04067808,0.029993126,0.063296854,0.04668259,-0.012749555,0.005248918,-0.010436894,-0.07561844,-0.011633145,0.05444743,-0.048320852,0.014772509,-0.07199935,-0.014760617,0.021598626,-0.017174078,-0.05955723,-0.03472137,-0.07610088,-0.048029725,0.038275547,-0.024732482,0.02252993,-0.014710533,0.053196922,-0.01815156,0.046866003,0.038138613,0.023503724,0.07431182,-0.010030737,0.018859217,0.054400813,-0.051315624,-0.05778552,0.052278083,-0.04012966,0.07762834,0.07195341,0.011121125,-0.05060351,0.012136496,-0.07420707,0.04311224,0.07492402,-0.04081308,-0.018771872,-0.033988312,0.045980997,0.08672062,-0.005062198,-0.025109446,0.12977187,-0.016560083,0.029968856,0.042827725,0.067344815,0.04638003,-0.035595536,0.14303884,0.032466277,0.02497015,0.050941344,-0.024447702,0.10157372,0.0778076,0.00053819915,-0.031346135,-0.008758584,0.036722686,-0.0015840823,-0.020259231,-0.015971852,-0.04298156,0.07306846,0.022992812,-0.034721397,-0.030194966,-0.014201621,-0.043520536,0.010887479,0.03231367,-0.087124325,0.027420446,0.06266317,0.027834242,-0.12047557,-0.087669924,-0.020153027,0.031243222,0.027246276,-0.10769241,-0.0072499076,9.307464e-34,-0.080400184,0.08192685,-0.04577184,0.078311056,0.0642137,0.012169457,0.13736194,0.022015871,0.03278156,0.05398484,-0.035939127,-0.0022418867,-0.1290434,0.008012245,-0.017896941,-0.030848654,-0.012321777,0.024660239,-0.06502408,-0.03576453,-0.10739129,0.0059367563,-0.038558144,-0.0053904355,-0.029615968,0.0663225,-0.009698477,0.002204676,0.016577557,0.016558561,0.032411598,0.025009926,-0.023183554,-0.0548188,-0.013516646,-0.11561085,0.06011747,0.0032648896,-0.019577319,0.08061338,0.036386278,-0.06483969,-0.009423049,-0.067994475,-0.0059552514,0.07898494,-0.030586459,0.057788316,-0.011511716,-0.007741939,-0.02863135,0.03207052,-0.025858352,0.076669626,0.07364335,-0.0601048,0.078869574,0.049763173,0.0026653612,0.007474002,-0.052608352,-0.10268198,0.102147534,-0.019444479,0.051910717,-0.002900365,0.015770577,-0.067796655,-0.029883914,0.022909926,0.009268357,-0.121122375,0.067859925,-0.059911028,0.045639582,-0.009814225,0.014831371,0.059833657,-0.014894034,-0.0022807359,-0.027649293,-0.014831903,0.052625373,0.056469955,0.07557365,0.0031232166,-0.011547768,-0.05443782,0.06120629,0.07160346,0.032031905,0.059437387,-0.012607803,0.04696337,0.07722856,-1.6495452e-8,0.014486489,-0.048435584,0.003250121,0.028159982,0.031189898,0.0023627344,-0.070192665,0.056730375,0.03496575,0.011610652,0.06183044,-0.027920958,-0.0121314,-0.052380722,-0.020452451,-0.04563529,0.017542096,-0.03620699,0.0011459879,0.041698407,-0.028633622,0.03700075,-0.00061687466,0.021913622,-0.07560133,0.03271757,0.017450893,-0.07702778,0.020872569,-0.06213861,-0.0038546,0.04003318,0.069114655,-0.0065786745,-0.016454224,-0.09361585,-0.16091056,0.058383908,-0.052135747,0.010157994,0.016596014,-0.0043797004,-0.014434132,0.0061570127,0.0016335461,0.02599054,0.034217644,0.056406163,-0.020769285,0.08216932,-0.10429248,0.004765623,0.04851646,-0.022152325,0.04684329,-0.058515728,-0.017122269,-0.064585134,0.008293409,-0.034130603,0.024276521,-0.04850379,-0.00979301,-0.0031762286],"context_embeddings":[0.10449726,0.00020120523,0.00030689867,0.012737274,-0.034894396,-0.024273962,0.012115382,-0.0051147924,-0.07086552,-0.04101765,-0.051549047,-0.04598007,-0.026155986,-0.012219195,0.02462915,-0.0027154824,-0.009507422,-0.09852741,0.040576775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{"question":"How to use the sessionstate feature in Streamlit","document_title":"What is serializable session state?","document_link":"https://docs.streamlit.io/knowledge-base/using-streamlit/serializable-session-state#pickle.PicklingError","document_text":"## Serializable Session State\n\nSerialization refers to the process of converting an object or data structure into a format that can be persisted and shared, and allowing you to recover the data’s original structure. Python’s built-in [pickle](https://docs.python.org/3/library/pickle.html) module serializes Python objects to a byte stream (\"pickling\") and deserializes the stream into an object (\"unpickling\").\n\nBy default, Streamlit’s [Session State](https://docs.streamlit.io/library/advanced-features/session-state) allows you to persist any Python object for the duration of the session, irrespective of the object’s pickle-serializability. This property lets you store Python primitives such as integers, floating-point numbers, complex numbers and booleans, dataframes, and even [lambdas](https://docs.python.org/3/reference/expressions.html#lambda) returned by functions. However, some execution environments may require serializing all data in Session State, so it may be useful to detect incompatibility during development, or when the execution environment will stop supporting it in the future.\n\nTo that end, Streamlit provides a `runner.enforceSerializableSessionState` [configuration option](https://docs.streamlit.io/library/advanced-features/configuration) that, when set to `true`, only allows pickle-serializable objects in Session State. To enable the option, either create a global or project config file with the following or use it as a command-line flag:\n\n\n```\n# .streamlit/config.toml\n[runner]\nenforceSerializableSessionState = true\n\n```\nBy \"*pickle-serializable*\", we mean calling `pickle.dumps(obj)` should not raise a [`PicklingError`](https://docs.python.org/3/library/pickle.html#pickle.PicklingError) exception. When the config option is enabled, adding unserializable data to session state should result in an exception. E.g.,\n\n\n```\nimport streamlit as st\n\ndef unserializable_data():\n return lambda x: x\n\n#👇 results in an exception when enforceSerializableSessionState is on\nst.session_state.unserializable = unserializable_data()\n\n```\n![UnserializableSessionStateError](https://docs.streamlit.io/images/unserializable-session-state-error.png)","answer":"erialization refers to the process of converting an object or data structure into a format that can be persisted and shared, and allowing you to recover the data’s original structure.\n\nBy default, Streamlit’s [Session State](https://docs.streamlit.io/library/advanced-features/session-state) allows you to persist any Python object for the duration of the session, irrespective of the object’s pickle-serializability. \n\nStreamlit provides a `runner.enforceSerializableSessionState` [configuration option](https://docs.streamlit.io/library/advanced-features/configuration) that, when set to `true`, only allows pickle-serializable objects in Session State.\n\nBy \"*pickle-serializable*\", we mean calling `pickle.dumps(obj)` should not raise a [`PicklingError`](https://docs.python.org/3/library/pickle.html#pickle.PicklingError) exception","question_idx":2,"row_idx":0,"model":"gpt-3.5-turbo","idx":1,"Template":0,"persona":"Streamlit expert","response":"<EMPTY 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{"question":"How can I create histograms with different bucket colors in Streamlit","document_title":"API reference","document_link":"https://docs.streamlit.io/1.9.0/library/api-reference/charts/st.plotly_chart#stplotly_chart","document_text":"ader(\"Define a custom colorscale\")\ndf = px.data.iris()\nfig = px.scatter(\n df,\n x=\"sepal_width\",\n y=\"sepal_length\",\n color=\"sepal_length\",\n color_continuous_scale=\"reds\",\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\n```\nNotice how the custom color scale is still reflected in the chart, even when the Streamlit theme is enabled 👇\n\nFor many more examples of Plotly charts with and without the Streamlit theme, check out the [plotly.streamlit.app](https://plotly.streamlit.app).\n\n","answer":"EMPTY MESSAGE","question_idx":1,"row_idx":1,"model":"gpt-3.5-turbo","idx":2,"Template":0,"persona":"Streamlit expert","response":"<EMPTY 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{"question":"Can I create histograms with different bucket colors in Streamlit","document_title":"API reference","document_link":"https://docs.streamlit.io/1.10.0/library/api-reference/charts/st.plotly_chart#stplotly_chart","document_text":"eader(\"Define a custom colorscale\")\ndf = px.data.iris()\nfig = px.scatter(\n df,\n x=\"sepal_width\",\n y=\"sepal_length\",\n color=\"sepal_length\",\n color_continuous_scale=\"reds\",\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\n```\nNotice how the custom color scale is still reflected in the chart, even when the Streamlit theme is enabled 👇\n\nFor many more examples of Plotly charts with and without the Streamlit theme, check out the [plotly.streamlit.app](https://plotly.streamlit.app).\n\n","answer":"EMPTY 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{"question":"Can I create histograms with different bucket colors in Streamlit","document_title":"API reference","document_link":"https://docs.streamlit.io/1.6.0/library/api-reference/charts/st.plotly_chart#stplotly_chart","document_text":"ader(\"Define a custom colorscale\")\ndf = px.data.iris()\nfig = px.scatter(\n df,\n x=\"sepal_width\",\n y=\"sepal_length\",\n color=\"sepal_length\",\n color_continuous_scale=\"reds\",\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\n```\nNotice how the custom color scale is still reflected in the chart, even when the Streamlit theme is enabled 👇\n\nFor many more examples of Plotly charts with and without the Streamlit theme, check out the [plotly.streamlit.app](https://plotly.streamlit.app).\n\n","answer":"EMPTY 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{"question":"Can I create histograms with different bucket colors in Streamlit","document_title":"API reference","document_link":"https://docs.streamlit.io/1.8.0/library/api-reference/charts/st.plotly_chart#stplotly_chart","document_text":"ader(\"Define a custom colorscale\")\ndf = px.data.iris()\nfig = px.scatter(\n df,\n x=\"sepal_width\",\n y=\"sepal_length\",\n color=\"sepal_length\",\n color_continuous_scale=\"reds\",\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\n```\nNotice how the custom color scale is still reflected in the chart, even when the Streamlit theme is enabled 👇\n\nFor many more examples of Plotly charts with and without the Streamlit theme, check out the [plotly.streamlit.app](https://plotly.streamlit.app).\n\n","answer":"EMPTY 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{"question":"How to use the sessionstate feature in Streamlit","document_title":"Configuration","document_link":"https://docs.streamlit.io/library/advanced-features/configuration#view-all-configuration-options","document_text":"## View all configuration options\n\nAs described in [Command-line options](https://docs.streamlit.io/library/advanced-features/cli), you can\nview all available configuration option using:\n\n\n```\nstreamlit config show\n\n```\nThe command above will print something like this:\n\n\n```\n# Streamlit version: 1.22.0\n\n[global]\n\n# By default, Streamlit checks if the Python watchdog module is available and, if not, prints a warning asking for you to install it. The watchdog module is not required, but highly recommended. It improves Streamlit's ability to detect changes to files in your filesystem.\n# If you'd like to turn off this warning, set this to True.\n# Default: false\ndisableWatchdogWarning = false\n\n# If True, will show a warning when you run a Streamlit-enabled script via \"python my_script.py\".\n# Default: true\nshowWarningOnDirectExecution = true\n\n# DataFrame serialization.\n# Acceptable values: - 'legacy': Serialize DataFrames using Streamlit's custom format. Slow but battle-tested. - 'arrow': Serialize DataFrames using Apache Arrow. Much faster and versatile.\n# Default: \"arrow\"\ndataFrameSerialization = \"arrow\"\n\n\n[logger]\n\n# Level of logging: 'error', 'warning', 'info', or 'debug'.\n# Default: 'info'\nlevel = \"info\"\n\n# String format for logging messages. If logger.datetimeFormat is set, logger messages will default to `%(asctime)s.%(msecs)03d %(message)s`. See [Python's documentation](https://docs.python.org/2.6/library/logging.html#formatter-objects) for available attributes.\n# Default: \"%(asctime)s %(message)s\"\nmessageFormat = \"%(asctime)s %(message)s\"\n\n\n[client]\n\n# Whether to enable st.cache.\n# Default: true\ncaching = true\n\n# If false, makes your Streamlit script not draw to a Streamlit app.\n# Default: true\ndisplayEnabled = true\n\n# Controls whether uncaught app exceptions are displayed in the browser. By default, this is set to True and Streamlit displays app exceptions and associated tracebacks in the browser.\n# If set to False, an exception will result in a generic message being shown in the browser, and exceptions and tracebacks will be printed to the console only.\n# Default: true\nshowErrorDetails = true\n\n# Change the visibility of items in the toolbar, options menu, and settings dialog (top right of the app).\n# Allowed values:\n# \"auto\" : Show the developer options if the app is accessed through localhost and hide them otherwise.\n# \"developer\" : Show the developer options.\n# \"viewer\" : Hide the developer options.\n# \"minimal\" : Show only options set externally (e.g. through Streamlit Community Cloud) or through st.set_page_config. If there are no options left, hide the menu.\n# Default: \"auto\"\ntoolbarMode = \"auto\"\n\n\n[runner]\n\n# Allows you to type a variable or string by itself in a single line of Python code to write it to the app.\n# Default: true\nmagicEnabled = true\n\n# Install a Python tracer to allow you to stop or pause your script at any point and introspect it. As a side-effect, this slows down your script's execution.\n# Default: false\ninstallTracer = false\n\n# Sets the MPLBACKEND environment variable to Agg inside Streamlit to prevent Python crashing.\n# Default: true\nfixMatplotlib = true\n\n# Run the Python Garbage Collector after each script execution. This can help avoid excess memory use in Streamlit apps, but could introduce delay in rerunning the app script for high-memory-use applications.\n# Default: true\npostScriptGC = true\n\n# Handle script rerun requests immediately, rather than waiting for script execution to reach a yield point. This makes Streamlit much more responsive to user interaction, but it can lead to race conditions in apps that mutate session_state data outside of explicit session_state assignment statements.\n# Default: true\nfastReruns = true\n\n# Raise an exception after adding unserializable data to Session State. Some execution environments may require serializing all data in Session State, so it may be useful to detect incompatibility during development, or when the execution environment will stop supporting it","answer":"EMPTY MESSAGE","question_idx":2,"row_idx":6,"model":"gpt-3.5-turbo","idx":7,"Template":0,"persona":"Streamlit expert","response":"<EMPTY 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{"question":"How to use the sessionstate feature in Streamlit","document_title":"Configuration","document_link":"https://docs.streamlit.io/library/advanced-features/configuration#view-all-configuration-options","document_text":" in the future.\n# Default: false\nenforceSerializableSessionState = false\n\n[server]\n\n# List of folders that should not be watched for changes. This impacts both \"Run on Save\" and @st.cache.\n# Relative paths will be taken as relative to the current working directory.\n# Example: ['/home/user1/env', 'relative/path/to/folder']\n# Default: []\nfolderWatchBlacklist = []\n\n# Change the type of file watcher used by Streamlit, or turn it off completely.\n# Allowed values: * \"auto\" : Streamlit will attempt to use the watchdog module, and falls back to polling if watchdog is not available. * \"watchdog\" : Force Streamlit to use the watchdog module. * \"poll\" : Force Streamlit to always use polling. * \"none\" : Streamlit will not watch files.\n# Default: \"auto\"\nfileWatcherType = \"auto\"\n\n# Symmetric key used to produce signed cookies. If deploying on multiple replicas, this should be set to the same value across all replicas to ensure they all share the same secret.\n# Default: randomly generated secret key.\ncookieSecret =\n\n# If false, will attempt to open a browser window on start.\n# Default: false unless (1) we are on a Linux box where DISPLAY is unset, or (2) we are running in the Streamlit Atom plugin.\nheadless = false\n\n# Automatically rerun script when the file is modified on disk.\n# Default: false\nrunOnSave = false\n\n# The address where the server will listen for client and browser connections. Use this if you want to bind the server to a specific address. If set, the server will only be accessible from this address, and not from any aliases (like localhost).\n# Default: (unset)\n# address =\n\n# The port where the server will listen for browser connections.\n# Default: 8501\nport = 8501\n\n# The base path for the URL where Streamlit should be served from.\n# Default: \"\"\nbaseUrlPath = \"\"\n\n# Enables support for Cross-Origin Request Sharing (CORS) protection, for added security.\n# Due to conflicts between CORS and XSRF, if `server.enableXsrfProtection` is on and `server.enableCORS` is off at the same time, we will prioritize `server.enableXsrfProtection`.\n# Default: true\nenableCORS = true\n\n# Enables support for Cross-Site Request Forgery (XSRF) protection, for added security.\n# Due to conflicts between CORS and XSRF, if `server.enableXsrfProtection` is on and `server.enableCORS` is off at the same time, we will prioritize `server.enableXsrfProtection`.\n# Default: true\nenableXsrfProtection = true\n\n# Max size, in megabytes, for files uploaded with the file_uploader.\n# Default: 200\nmaxUploadSize = 200\n\n# Max size, in megabytes, of messages that can be sent via the WebSocket connection.\n# Default: 200\nmaxMessageSize = 200\n\n# Enables support for websocket compression.\n# Default: false\nenableWebsocketCompression = false\n\n# Enable serving files from a `static` directory in the running app's directory.\n# Default: false\nenableStaticServing = false\n\n# Server certificate file for connecting via HTTPS. Must be set at the same time as \"server.sslKeyFile\".\n# ['DO NOT USE THIS OPTION IN A PRODUCTION ENVIRONMENT. It has not gone through security audits or performance tests. For the production environment, we recommend performing SSL termination by the load balancer or the reverse proxy.']\n# sslCertFile =\n\n# Cryptographic key file for connecting via HTTPS. Must be set at the same time as \"server.sslCertFile\".\n# ['DO NOT USE THIS OPTION IN A PRODUCTION ENVIRONMENT. It has not gone through security audits or performance tests. For the production environment, we recommend performing SSL termination by the load balancer or the reverse proxy.']\n# sslKeyFile =\n\n[browser]\n\n# Internet address where users should point their browsers in order to connect to the app. Can be IP address or DNS name and path.\n# This is used to: - Set the correct URL for CORS and XSRF protection purposes. - Show the URL on the terminal - Open the browser\n# Default: 'localhost'\nserverAddress = \"localhost\"\n\n# Whether to send usage statistics to Streamlit.\n# Default: true\ngatherUsageStats = true\n\n# Port whe","answer":"EMPTY MESSAGE","question_idx":2,"row_idx":7,"model":"gpt-3.5-turbo","idx":8,"Template":0,"persona":"Streamlit expert","response":"```\nhist_values = np.histogram(data[DATE_COLUMN].dt.hour, bins=24, range=(0,24))[0]\nst.bar_chart(hist_values)\n```\n```\n# Some number in the range 0-23\nhour_to_filter = st.slider('hour', 0, 23, 17)\nfiltered_data = data[data[DATE_COLUMN].dt.hour == hour_to_filter]\n\nst.subheader('Map of all pickups at %s:00' % hour_to_filter)\nst.map(filtered_data)\n```","experiment_id":1,"question_embeddings":[-0.008069718,0.019030994,-0.04399113,-0.018124266,-0.022838099,0.06364004,0.09799271,0.028880155,-0.027881691,-0.0026304945,-0.093847126,-0.052826203,-0.0495291,0.050359074,0.057861276,-0.081056945,-0.043767277,-0.034344412,0.030334882,-0.054179147,0.081798576,-0.06108611,-0.027220473,0.016159661,0.045966722,0.043755453,0.04657097,-0.04207103,0.0606236,-0.010835065,0.01963093,0.023086326,-0.08611886,-0.09577034,-0.042422198,-0.031213628,-0.02303005,-0.012711064,-0.061771363,-0.032626864,0.04722137,-0.05833356,-0.024581093,-0.014408672,-0.043140084,0.043106694,-0.043605175,0.012564146,-0.0024074847,0.07467294,-0.026442008,0.024675488,0.06863068,0.05543007,-0.036845602,0.021533161,0.03818942,0.07087255,-0.014140007,0.012392753,-0.029511698,-0.03693794,0.0142641105,-0.0068583405,-0.021607645,0.032087505,-0.004642361,-0.00048144456,0.08657255,-0.091415726,-0.0654163,0.040753946,0.04778726,-0.07014419,-0.054056033,-0.13101906,0.0106581375,-0.033824015,-0.015706005,0.036165632,0.06448401,-0.027799198,-0.016320214,-0.030502934,0.044609677,-0.0064864736,-0.023485867,-0.02510403,-0.032146394,0.11691514,-0.093619,0.09026529,-0.04394514,-0.040745012,-0.074140415,0.07941597,-0.058178466,0.10143081,0.00082231086,0.034904383,0.021032574,0.02780719,0.020528773,0.07157437,0.015880924,-0.07901302,0.002658145,0.033562664,0.025330164,-0.0620102,0.00088657654,0.043670274,0.06292877,0.020624137,0.024602726,0.014736394,-0.012740257,0.024506299,-0.01692787,0.03850096,0.05740074,-0.048916616,-0.041654356,-0.016295029,0.06332491,0.007249942,0.1201618,-3.069891e-33,0.038632937,-0.07285959,-0.097846106,0.06889692,0.039875455,0.061407413,0.06816671,-0.021834662,-0.041231632,-0.06655201,-0.02681365,-0.00846934,0.0056336895,0.025145523,-0.07212278,-0.088356264,-0.06571071,0.034034792,0.022489915,-0.057755113,0.041024677,-0.0111023635,0.060905315,-0.03981662,0.025356166,0.003709564,0.039863884,-0.009520236,0.026838858,0.009208849,0.061858226,0.041652687,0.027003404,0.008471059,0.100978374,-0.07413808,0.02455753,-0.019793069,0.016882718,-0.06035224,0.005419944,0.030355176,-0.05040027,0.009402115,-0.09048009,-0.060497977,-0.034752905,0.026658474,-0.031877108,-0.019351725,-0.024361955,0.08411059,-0.051161606,-0.006133748,0.023922987,-0.03208829,-0.034828957,0.09694366,-0.023172703,-0.028460398,-0.02360395,0.011142688,-0.046996046,-0.07437975,-0.024909688,0.03751471,0.051979627,0.02110711,-0.016065998,-0.15068954,-0.0536162,-0.027345277,-0.012201718,0.024762029,-0.0059242416,-0.0022329595,0.042477656,0.07530215,-0.06591605,-0.00408647,0.020814484,-0.032786287,-0.022626853,0.12286805,0.0066859704,-0.022303088,0.002724913,-0.03851183,-0.032818407,-0.057483967,-0.054443043,-0.0041463273,0.16144624,0.007332825,0.054585196,1.2820273e-33,0.022542262,-0.020859636,-0.052710604,0.001758398,0.052588698,0.025964668,0.10388966,0.014702435,0.0043939003,-0.041091733,-0.0074163736,0.035646103,-0.11103489,0.03836938,-0.030325333,0.013828032,0.03198602,0.0045473897,-0.03992809,-0.023974352,-0.0017821189,0.008392904,-0.05047325,0.012730342,0.06085425,-0.056332808,0.07645324,-0.0226349,0.015513832,0.030792732,0.090231426,0.015368832,-0.074278586,0.012956486,0.045075648,-0.013657695,0.091199115,0.010006847,-0.12094287,0.11235369,0.09024848,-0.03860437,-0.07123643,-0.045214918,0.019595131,0.07379895,-0.09251951,0.008591872,-0.13025522,0.061584905,0.007761197,-0.10383422,-0.009915873,-0.025119737,0.009733272,-0.06666904,0.06700916,-0.02102678,-0.04229344,-0.11801866,0.009725576,-0.0668771,0.0069729257,-0.019669157,0.07609675,0.03374921,0.026979292,0.07371696,0.09338998,-0.022135435,0.00040826626,-0.09352545,0.054446653,0.032927696,0.08484965,0.036018204,-0.017780457,-0.044531226,-0.0012620412,0.009875729,-0.04044144,0.020187803,-0.041872904,-0.07363746,0.0780202,0.040785998,0.0111372005,0.07780356,-0.011045198,-0.014636242,-0.057807446,0.051122837,-0.08242229,0.031930815,0.08355099,-1.4805702e-8,-0.051469665,-0.033614144,0.018845683,0.06451867,0.0058652232,0.0007405246,-0.027512264,-0.023120081,-0.024361122,-0.061715182,-0.009631923,-0.035585366,0.14869612,-0.082732216,0.024393944,-0.035837397,-0.00039809948,0.044956114,-0.02445103,0.024959521,0.021514298,-0.026425743,0.0038626466,0.100734875,-0.05428898,0.008292243,0.08542635,0.0042307405,0.014428068,-0.031963438,0.0071916976,0.07829516,0.058305006,-0.007757116,-0.008674596,0.07569885,-0.032974575,0.028838512,-0.023347737,0.023153437,-0.002992033,-0.008270725,0.02424749,-0.02757731,-0.028802924,0.05631192,-0.0530676,0.079994015,0.046310086,0.004630426,-0.021416683,0.05256077,0.008517852,0.07715209,0.018514486,-0.023122005,0.04937923,-0.07301177,0.007907248,-0.09448888,0.02026514,0.03812597,-0.05387038,-0.011038521],"context_embeddings":[-0.027450047,-0.055739854,-0.088104494,0.016431704,0.13177769,-0.025336778,0.021939218,-0.0372217,0.03749185,0.014046368,0.00398038,0.038273536,-0.03862615,0.033957433,-0.043568775,-0.06777249,0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{"question":"How can I create histograms with different bucket colors in Streamlit","document_title":"API reference","document_link":"https://docs.streamlit.io/1.7.0/library/api-reference/charts/st.plotly_chart#stplotly_chart","document_text":"ader(\"Define a custom colorscale\")\ndf = px.data.iris()\nfig = px.scatter(\n df,\n x=\"sepal_width\",\n y=\"sepal_length\",\n color=\"sepal_length\",\n color_continuous_scale=\"reds\",\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\n```\nNotice how the custom color scale is still reflected in the chart, even when the Streamlit theme is enabled 👇\n\nFor many more examples of Plotly charts with and without the Streamlit theme, check out the [plotly.streamlit.app](https://plotly.streamlit.app).\n\n","answer":"EMPTY MESSAGE","question_idx":1,"row_idx":8,"model":"gpt-3.5-turbo","idx":9,"Template":0,"persona":"Streamlit expert","response":"```\ndf = px.data.iris()\nfig = px.scatter(\n df,\n x=\"sepal_width\",\n y=\"sepal_length\",\n color=\"sepal_length\",\n color_continuous_scale=\"reds\",\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n st.plotly_chart(fig, theme=None, use_container_width=True)\n```\n```\nNotice how the custom color scale is still reflected in the chart, even when the Streamlit theme is enabled 👇\n\nFor many more examples of Plotly charts with and without the Streamlit theme, check out the [plotly.streamlit.app](https://plotly.streamlit.app).\n```","experiment_id":1,"question_embeddings":[0.088330105,0.011396006,-0.017542858,-0.08434498,-0.047787853,0.03425188,0.048996642,0.0034383428,-0.022393193,-0.023409048,-0.07357438,-0.077896774,0.026116539,-0.00085928355,0.039049085,-0.026642563,-0.097047776,-0.022016235,-0.08539825,-0.17395513,0.010976068,-0.05704131,-0.03725233,-0.06842565,-0.0044478704,0.0649463,0.031023948,0.040923957,0.07282005,-0.049106944,0.059667658,-0.0753585,0.062485617,-0.02494093,-0.007864315,-0.019300802,-0.036084615,0.051608577,-0.09109866,0.033572853,0.042465758,0.01174127,-0.019712325,-0.065684274,-0.017155608,0.08364792,-0.073342375,0.01874716,0.037283268,0.025831383,-0.043462474,-0.073857106,0.029871376,0.017697562,0.009775645,-0.036767107,-0.04120292,-0.06703686,0.07610773,-0.10925221,-0.04442994,-0.0074998676,0.022256946,-0.014896059,0.06088412,0.016017038,-0.012465867,0.049446587,0.08847953,-0.018837655,0.019807337,0.06478816,0.06848112,0.055087257,-0.07049523,-0.020874226,-0.011705072,0.048881352,-0.059627306,-0.05197535,-0.027297586,0.014144446,0.037603576,0.040695284,0.017761882,0.06532191,-0.06894137,0.013939522,-0.04712859,0.024932921,-0.062471792,0.066132456,0.002363949,-0.03655384,-0.052409384,0.07198713,0.09174018,-0.006315629,0.06124142,-0.023097236,0.040439002,-0.07812325,0.016205361,-0.014299262,0.07228006,-0.003125131,-0.02446053,0.09691148,0.025791425,-0.037827283,0.048649594,-0.042109657,0.016840104,-0.086937375,-0.017265989,0.075562194,-0.10699093,0.01211867,-0.06403345,0.018178374,0.061768565,-0.002032798,-0.05675274,-0.010576633,-0.034583665,-0.039890874,-0.029935757,-3.2848764e-33,0.0378979,-0.106998086,-0.040995043,0.04149618,0.065572456,0.039515913,-0.008075179,0.003411869,-0.02091417,-0.05122435,-0.005777524,0.037594054,-0.055417888,0.010974505,-0.08005184,-0.052646156,0.007957076,-0.024725603,-0.06924275,-0.037430324,-0.08051367,-0.023205118,0.052269068,-0.012416274,0.016556906,-0.020465432,0.04609017,-0.027405446,0.037574787,0.03561955,0.03827268,0.08577126,0.0042460887,0.014051184,0.05974666,-0.058780804,-0.048364103,0.040574744,-0.043581553,0.07378104,0.061412837,0.0014289903,-0.052190572,-0.00078052504,-0.057369288,0.04606968,0.06747937,-0.030284451,0.009257126,-0.025518835,0.04138671,0.08106319,0.0042691617,-0.014420229,0.11329392,-0.022430757,0.032329742,0.047505144,0.040817976,0.04313649,-0.024551831,0.15228917,0.034013808,0.01941502,0.06144809,-0.036756065,0.10396538,0.070308425,-0.006481227,-0.03454383,-0.00991815,0.037999697,0.016863624,-0.016421068,-0.025025293,-0.04278919,0.066235885,0.010628494,-0.052254688,-0.03445316,-0.01905931,-0.052874748,0.010571877,0.026651157,-0.089318834,0.03158032,0.05560046,0.031757142,-0.11445971,-0.09785465,-0.027041305,0.025731953,0.03934218,-0.10917421,0.0022965784,9.564032e-34,-0.06313915,0.09419001,-0.04081826,0.07181917,0.066276036,0.0030092914,0.13137865,0.035464074,0.045764312,0.051538132,-0.055806544,-0.0046785898,-0.124816924,0.017279215,-0.015864715,-0.040863328,0.0009500781,0.018876879,-0.05487937,-0.037517846,-0.08503278,0.03304914,-0.034198888,0.002668823,-0.04557246,0.050836373,-0.013927419,-0.005447964,0.017712409,0.019973949,0.027383726,0.037844945,-0.014945877,-0.04143812,-0.01959012,-0.105157845,0.06470922,0.013278265,-0.013803623,0.067147404,0.04178529,-0.0632891,-0.010079848,-0.08619708,-0.008960702,0.096153274,-0.035347067,0.06595369,-0.020878192,-0.016643418,-0.019682482,0.013243405,-0.032486048,0.08356432,0.07674347,-0.06361975,0.080223106,0.03534406,0.0060911328,0.0065864087,-0.060241528,-0.10307839,0.10199058,0.00088820775,0.030220982,-0.0011668602,0.0099102575,-0.060083468,-0.042249147,0.017135648,-0.0036030465,-0.0972523,0.07683787,-0.06330369,0.03142023,-0.0026465172,-0.008431761,0.06634554,-0.0038314487,0.010890359,-0.018100841,-0.015494008,0.036994852,0.060362976,0.057365444,0.003517775,-0.0029040098,-0.0502847,0.050799564,0.07383564,0.023432627,0.055715792,-0.02273529,0.058175955,0.08986104,-1.720074e-8,0.022305466,-0.070501976,-0.016909117,0.014119327,0.055804323,0.02039817,-0.06730445,0.059458356,0.035946358,-0.014027031,0.071772315,-0.022881763,-0.003811465,-0.057003707,-0.018651411,-0.04579891,-0.015629753,-0.020469574,0.013314239,0.035074934,-0.026234025,0.0120668635,0.0072116307,0.01317788,-0.08294273,0.02837273,0.017769746,-0.073891856,0.021844728,-0.05221814,-0.0060682157,0.030079223,0.063992664,-0.02636329,-0.026866086,-0.07240491,-0.15313517,0.049820986,-0.04309975,0.0044540553,0.008091409,0.01155717,-0.011134993,-0.015595453,-0.0044206656,0.031132616,0.021964429,0.08499096,-0.029608035,0.09432952,-0.10045928,-0.0016386824,0.045343123,-0.027784642,0.04225195,-0.077244245,-0.025754198,-0.062053796,0.017611738,-0.031203467,0.01756977,-0.025270505,-0.02455264,0.0032717404],"context_embeddings":[0.07019842,-0.06461782,-0.029987501,0.016560858,0.044384483,-0.028462037,0.0154489735,0.01953127,-0.013943043,-0.048632137,-0.01622638,0.04575075,-0.08032064,-0.0057710116,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{"question":"How can I create histograms with different bucket colors in Streamlit","document_title":"API reference","document_link":"https://docs.streamlit.io/1.5.0/library/api-reference/charts/st.plotly_chart#stplotly_chart","document_text":"ader(\"Define a custom colorscale\")\ndf = px.data.iris()\nfig = px.scatter(\n df,\n x=\"sepal_width\",\n y=\"sepal_length\",\n color=\"sepal_length\",\n color_continuous_scale=\"reds\",\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\n```\nNotice how the custom color scale is still reflected in the chart, even when the Streamlit theme is enabled 👇\n\nFor many more examples of Plotly charts with and without the Streamlit theme, check out the [plotly.streamlit.app](https://plotly.streamlit.app).\n\n","answer":"EMPTY MESSAGE","question_idx":1,"row_idx":9,"model":"gpt-3.5-turbo","idx":10,"Template":0,"persona":"Streamlit expert","response":"* Session State is not persisted. If the Streamlit server crashes, then everything stored in Session State gets wiped\n* For caveats and limitations with the Session State API, please see the [API 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{"question":"How to use the sessionstate feature in Streamlit","document_title":"Add statefulness to apps","document_link":"https://docs.streamlit.io/library/advanced-features/session-state#caveats-and-limitations","document_text":"## Advanced concepts\n\n### Session State and Widget State association\n\nSession State provides the functionality to store variables across reruns. Widget state (i.e. the value of a widget) is also stored in a session.\n\nFor simplicity, we have *unified* this information in one place. i.e. the Session State. This convenience feature makes it super easy to read or write to the widget's state anywhere in the app's code. Session State variables mirror the widget value using the `key` argument.\n\nWe illustrate this with the following example. Let's say we have an app with a slider to represent temperature in Celsius. We can **set** and **get** the value of the temperature widget by using the Session State API, as follows:\n\n\n```\nimport streamlit as st\n\nif \"celsius\" not in st.session_state:\n # set the initial default value of the slider widget\n st.session_state.celsius = 50.0\n\nst.slider(\n \"Temperature in Celsius\",\n min_value=-100.0,\n max_value=100.0,\n key=\"celsius\"\n)\n\n# This will get the value of the slider widget\nst.write(st.session_state.celsius)\n\n```\nThere is a limitation to setting widget values using the Session State API.\n\nThe following example will raise a `StreamlitAPIException` on trying to set the state of `st.button` via the Session State API:\n\n\n```\nimport streamlit as st\n\nif 'my_button' not in st.session_state:\n st.session_state.my_button = True\n # Streamlit will raise an Exception on trying to set the state of button\n\nst.button('Submit', key='my_button')\n\n```\n![state-button-exception](https://docs.streamlit.io/images/state_button_exception.png)### Serializable Session State\n\nSerialization refers to the process of converting an object or data structure into a format that can be persisted and shared, and allowing you to recover the data’s original structure. Python’s built-in [pickle](https://docs.python.org/3/library/pickle.html) module serializes Python objects to a byte stream (\"pickling\") and deserializes the stream into an object (\"unpickling\").\n\nBy default, Streamlit’s [Session State](https://docs.streamlit.io/library/advanced-features/session-state) allows you to persist any Python object for the duration of the session, irrespective of the object’s pickle-serializability. This property lets you store Python primitives such as integers, floating-point numbers, complex numbers and booleans, dataframes, and even [lambdas](https://docs.python.org/3/reference/expressions.html#lambda) returned by functions. However, some execution environments may require serializing all data in Session State, so it may be useful to detect incompatibility during development, or when the execution environment will stop supporting it in the future.\n\nTo that end, Streamlit provides a `runner.enforceSerializableSessionState` [configuration option](https://docs.streamlit.io/library/advanced-features/configuration) that, when set to `true`, only allows pickle-serializable objects in Session State. To enable the option, either create a global or project config file with the following or use it as a command-line flag:\n\n\n```\n# .streamlit/config.toml\n[runner]\nenforceSerializableSessionState = true\n\n```\nBy \"*pickle-serializable*\", we mean calling `pickle.dumps(obj)` should not raise a [`PicklingError`](https://docs.python.org/3/library/pickle.html#pickle.PicklingError) exception. When the config option is enabled, adding unserializable data to session state should result in an exception. E.g.,\n\n\n```\nimport streamlit as st\n\ndef unserializable_data():\n return lambda x: x\n\n#👇 results in an exception when enforceSerializableSessionState is on\nst.session_state.unserializable = unserializable_data()\n\n```\n![UnserializableSessionStateError](https://docs.streamlit.io/images/unserializable-session-state-error.png)### Caveats and limitations\n\nHere are some limitations to keep in mind when using Session State:\n\n* Session State exists for as long as the tab is open and connected to the Streamlit server. As soon as you close the tab, e","answer":"ession State provides the functionality to store variables across reruns. Widget state (i.e. the value of a widget) is also stored in a session. \n\nSession State variables mirror the widget value using the `key` argument.\n\nBy default, Streamlit’s Session State allows you to persist any Python object for the duration of the session, irrespective of the object’s pickle-serializability. \n\nStreamlit provides a `runner.enforceSerializableSessionState` configuration option that, when set to `true`, only allows pickle-serializable objects in Session State.\n\nHere are some limitations to keep in mind when using Session State:\n\n* Session State exists for as long as the tab is open and connected to the Streamlit server","question_idx":2,"row_idx":10,"model":"gpt-3.5-turbo","idx":11,"Template":0,"persona":"Streamlit expert","response":"> ## st.plotly\\_chart\n> \n> Display an interactive Plotly chart.\n> \n> Plotly is a charting library for Python. The arguments to this function\n> closely follow the ones for Plotly's plot() function. You can find\n> more about Plotly at <https://plot.ly/python>.\n> \n> To show Plotly charts in Streamlit, call st.plotly\\_chart wherever you\n> would call Plotly's py.plot or py.iplot.\n> \n> #### Example\n> \n> ```\n> \n> import streamlit as st\n> import plotly.figure_factory as ff\n> import numpy as np\n> \n> # Add histogram data\n> x1 = np.random.randn(200) - 2\n> x2 = np.random.randn(200)\n> x3 = np.random.randn(200) + 2\n> \n> # Group data together\n> hist_data = [x1, x2, x3]\n> \n> group_labels = ['Group 1', 'Group 2', 'Group 3']\n> \n> # Create distplot with custom bin_size\n> fig = ff.create_distplot(\n> hist_data, group_labels, bin_size=[.1, .25, .5])\n> \n> # Plot!\n> st.plotly_chart(fig, use_container_width=True)\n> \n> ```\n> \n> \n> [(view standalone Streamlit app)](https://doc-plotly-chart.streamlit.app/) \n> \n> ### Theming\n> \n> Plotly charts are displayed using the Streamlit theme by default. This theme is sleek, user-friendly, and incorporates Streamlit's color palette. The added benefit is that your charts better integrate with the rest of your app's 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{"question":"Can I create histograms with different bucket colors in Streamlit","document_title":"Create an app","document_link":"https://docs.streamlit.io/library/get-started/create-an-app#share-your-app","document_text":"## Let's put it all together\n\nThat's it, you've made it to the end. Here's the complete script for our interactive app.\n\n\n```\nimport streamlit as st\nimport pandas as pd\nimport numpy as np\n\nst.title('Uber pickups in NYC')\n\nDATE_COLUMN = 'date/time'\nDATA_URL = ('https://s3-us-west-2.amazonaws.com/'\n 'streamlit-demo-data/uber-raw-data-sep14.csv.gz')\n\n@st.cache_data\ndef load_data(nrows):\n data = pd.read_csv(DATA_URL, nrows=nrows)\n lowercase = lambda x: str(x).lower()\n data.rename(lowercase, axis='columns', inplace=True)\n data[DATE_COLUMN] = pd.to_datetime(data[DATE_COLUMN])\n return data\n\ndata_load_state = st.text('Loading data...')\ndata = load_data(10000)\ndata_load_state.text(\"Done! (using st.cache_data)\")\n\nif st.checkbox('Show raw data'):\n st.subheader('Raw data')\n st.write(data)\n\nst.subheader('Number of pickups by hour')\nhist_values = np.histogram(data[DATE_COLUMN].dt.hour, bins=24, range=(0,24))[0]\nst.bar_chart(hist_values)\n\n# Some number in the range 0-23\nhour_to_filter = st.slider('hour', 0, 23, 17)\nfiltered_data = data[data[DATE_COLUMN].dt.hour == hour_to_filter]\n\nst.subheader('Map of all pickups at %s:00' % hour_to_filter)\nst.map(filtered_data)\n\n```\n","answer":"``\nst.title('Uber pickups in NYC')\n\n@st.cache_data\ndef load_data(nrows):\n data = pd.read_csv(DATA_URL, nrows=nrows)\n lowercase = lambda x: str(x).lower()\n data.rename(lowercase, axis='columns', inplace=True)\n data[DATE_COLUMN] = pd.to_datetime(data[DATE_COLUMN])\n return data\n\nhist_values = np.histogram(data[DATE_COLUMN].dt.hour, bins=24, range=(0,24))[0]\nst.bar_chart(hist_values)\n\nhour_to_filter = st.slider('hour', 0, 23, 17)\n``","question_idx":0,"row_idx":11,"model":"gpt-3.5-turbo","idx":12,"Template":0,"persona":"Streamlit expert","response":"## st.plotly\\_chart\n\nDisplay an interactive Plotly chart.\n\nPlotly is a charting library for Python. The arguments to this function\nclosely follow the ones for Plotly's plot() function. You can find\nmore about Plotly at <https://plot.ly/python>.\n\nTo show Plotly charts in Streamlit, call st.plotly\\_chart wherever you\nwould call Plotly's py.plot or py.iplot.\n\n#### Example\n\n> \n> The example below comes straight from the examples at\n> <https://plot.ly/python>:\n> \n> \n> \n> ```\n> \n> import streamlit as st\n> import plotly.figure_factory as ff\n> import numpy as np\n> \n> # Add histogram data\n> x1 = np.random.randn(200) - 2\n> x2 = np.random.randn(200)\n> x3 = np.random.randn(200) + 2\n> \n> # Group data together\n> hist_data = [x1, x2, x3]\n> \n> group_labels = ['Group 1', 'Group 2', 'Group 3']\n> \n> # Create distplot with custom bin_size\n> fig = ff.create_distplot(\n> hist_data, group_labels, bin_size=[.1, .25, .5])\n> \n> # Plot!\n> st.plotly_chart(fig, use_container_width=True)\n> \n> ```\n> \n> \n> [(view standalone Streamlit app)](https://share.streamlit.io/streamlit/docs/main/python/api-examples-source/charts.plotly_chart.py) \n\n### Theming\n\nPlotly charts are displayed using the Streamlit theme by default. This theme is sleek, user-friendly, and incorporates Streamlit's color palette. The added benefit is that your charts better integrate with the rest of your app's 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{"question":"Can I create histograms with different bucket colors in Streamlit","document_title":"API reference","document_link":"https://docs.streamlit.io/1.4.0/library/api-reference/charts/st.plotly_chart#stplotly_chart","document_text":"m colorscale\")\ndf = px.data.iris()\nfig = px.scatter(\n df,\n x=\"sepal_width\",\n y=\"sepal_length\",\n color=\"sepal_length\",\n color_continuous_scale=\"reds\",\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\n```\nNotice how the custom color scale is still reflected in the chart, even when the Streamlit theme is enabled 👇\n\nFor many more examples of Plotly charts with and without the Streamlit theme, check out the [plotly.streamlit.app](https://plotly.streamlit.app).\n\n","answer":"``\ndf = px.data.iris()\nfig = px.scatter(\n df,\n x=\"sepal_width\",\n y=\"sepal_length\",\n color=\"sepal_length\",\n color_continuous_scale=\"reds\",\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n st.plotly_chart(fig, theme=None, use_container_width=True)\n``","question_idx":0,"row_idx":12,"model":"gpt-3.5-turbo","idx":13,"Template":0,"persona":"Streamlit expert","response":"<EMPTY 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{"question":"Can I create histograms with different bucket colors in Streamlit","document_title":"API reference","document_link":"https://docs.streamlit.io/1.8.0/library/api-reference/charts/st.plotly_chart#stplotly_chart","document_text":"## st.plotly\\_chart\n\nDisplay an interactive Plotly chart.\n\n\nPlotly is a charting library for Python. The arguments to this function\nclosely follow the ones for Plotly's plot() function. You can find\nmore about Plotly at <https://plot.ly/python>.\n\n\nTo show Plotly charts in Streamlit, call st.plotly\\_chart wherever you\nwould call Plotly's py.plot or py.iplot.\n\n\n\n\n| Function signature[[source]](https://github.com/streamlit/streamlit/blob/1.8.0/lib/streamlit/elements/plotly_chart.py#L42 \"View st.plotly_chart source code on GitHub\") |\n| --- |\n| st.plotly\\_chart(figure\\_or\\_data, use\\_container\\_width=False, sharing=\"streamlit\", \\*\\*kwargs) |\n| Parameters |\n| \n\nfigure\\_or\\_data\n(plotly.graph\\_objs.Figure, plotly.graph\\_objs.Data,)\n | \ndict/list of plotly.graph\\_objs.Figure/Data\nSee <https://plot.ly/python/> for examples of graph descriptions.\n |\n| \n\nuse\\_container\\_width\n(bool)\n | \nIf True, set the chart width to the column width. This takes\nprecedence over the figure's native width value.\n |\n| \n\nsharing\n({'streamlit', 'private', 'secret', 'public'})\n | \nUse 'streamlit' to insert the plot and all its dependencies\ndirectly in the Streamlit app using plotly's offline mode (default).\nUse any other sharing mode to send the chart to Plotly chart studio, which\nrequires an account. See <https://plotly.com/chart-studio/> for more information.\n |\n| \n\n\\*\\*kwargs\n(null)\n | \nAny argument accepted by Plotly's plot() function.\n |\n\n#### Example\n\n\n> \n> The example below comes straight from the examples at\n> <https://plot.ly/python>:\n> \n> \n> \n> ```\n> \n> import streamlit as st\n> import plotly.figure_factory as ff\n> import numpy as np\n> \n> # Add histogram data\n> x1 = np.random.randn(200) - 2\n> x2 = np.random.randn(200)\n> x3 = np.random.randn(200) + 2\n> \n> # Group data together\n> hist_data = [x1, x2, x3]\n> \n> group_labels = ['Group 1', 'Group 2', 'Group 3']\n> \n> # Create distplot with custom bin_size\n> fig = ff.create_distplot(\n> hist_data, group_labels, bin_size=[.1, .25, .5])\n> \n> # Plot!\n> st.plotly_chart(fig, use_container_width=True)\n> \n> ```\n> \n> \n> [(view standalone Streamlit app)](https://share.streamlit.io/streamlit/docs/main/python/api-examples-source/charts.plotly_chart.py) \n> \n\n\n### Theming\n\nPlotly charts are displayed using the Streamlit theme by default. This theme is sleek, user-friendly, and incorporates Streamlit's color palette. The added benefit is that your charts better integrate with the rest of your app's design.\n\nThe Streamlit theme is available from Streamlit 1.16.0 through the `theme=\"streamlit\"` keyword argument. To disable it, and use Plotly's native theme, use `theme=None` instead.\n\nLet's look at an example of charts with the Streamlit theme and the native Plotly theme:\n\n\n```\nimport plotly.express as px\nimport streamlit as st\n\ndf = px.data.gapminder()\n\nfig = px.scatter(\n df.query(\"year==2007\"),\n x=\"gdpPercap\",\n y=\"lifeExp\",\n size=\"pop\",\n color=\"continent\",\n hover_name=\"country\",\n log_x=True,\n size_max=60,\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n # Use the Streamlit theme.\n # This is the default. So you can also omit the theme argument.\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n # Use the native Plotly theme.\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\n```\nClick the tabs in the interactive app below to see the charts with the Streamlit theme enabled and disabled.\n\nIf you're wondering if your own customizations will still be taken into account, don't worry! You can still make changes to your chart configurations. In other words, although we now enable the Streamlit theme by default, you can overwrite it with custom colors or fonts. For example, if you want a chart line to be green instead of the default red, you can do it!\n\nHere's an example of an Plotly chart where a custom color scale is defined and reflected:\n\n\n```\nimport plotly.express as px\nimport streamlit as st\n\nst.subhe","answer":"es, you can create histograms with different bucket colors in Streamlit using Plotly. Here's an example:\n\n```\nimport streamlit as st\nimport plotly.figure_factory as ff\nimport numpy as np\n\n# Add histogram data\nx1 = np.random.randn(200) - 2\nx2 = np.random.randn(200)\nx3 = np.random.randn(200) + 2\n\n# Group data together\nhist_data = [x1, x2, x3]\n\ngroup_labels = ['Group 1', 'Group 2', 'Group 3']\n\n# Create distplot with custom bin_size\nfig = ff.create_distplot(\n hist_data, group_labels, bin_size=[.1, .25, .5])\n\n# Plot!\nst.plotly_chart(fig, use_container_width=True)\n\n```\n\nPlotly charts are displayed using the Streamlit theme by default. This theme is sleek, user-friendly, and incorporates Streamlit's color palette. The added benefit is that your charts better integrate with the rest of your app's design","question_idx":0,"row_idx":13,"model":"gpt-3.5-turbo","idx":14,"Template":0,"persona":"Streamlit expert","response":"## st.plotly\\_chart\n\nDisplay an interactive Plotly chart.\n\nPlotly is a charting library for Python. The arguments to this function\nclosely follow the ones for Plotly's plot() function. You can find\nmore about Plotly at <https://plot.ly/python>.\n\nTo show Plotly charts in Streamlit, call st.plotly\\_chart wherever you\nwould call Plotly's py.plot or py.iplot.\n\n#### Example\n\n> \n> The example below comes straight from the examples at\n> <https://plot.ly/python>:\n> \n> \n> \n> ```\n> \n> import streamlit as st\n> import plotly.figure_factory as ff\n> import numpy as np\n> \n> # Add histogram data\n> x1 = np.random.randn(200) - 2\n> x2 = np.random.randn(200)\n> x3 = np.random.randn(200) + 2\n> \n> # Group data together\n> hist_data = [x1, x2, x3]\n> \n> group_labels = ['Group 1', 'Group 2', 'Group 3']\n> \n> # Create distplot with custom bin_size\n> fig = ff.create_distplot(\n> hist_data, group_labels, bin_size=[.1, .25, .5])\n> \n> # Plot!\n> st.plotly_chart(fig, use_container_width=True)\n> \n> ```\n> \n> \n> [(view standalone Streamlit app)](https://share.streamlit.io/streamlit/docs/main/python/api-examples-source/charts.plotly_chart.py) \n\n### Theming\n\nPlotly charts are displayed using the Streamlit theme by default. This theme is sleek, user-friendly, and incorporates Streamlit's color palette. The added benefit is that your charts better integrate with the rest of your app's 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{"question":"How can I create histograms with different bucket colors in Streamlit","document_title":"Create an app","document_link":"https://docs.streamlit.io/library/get-started/create-an-app#share-your-app","document_text":"## Let's put it all together\n\nThat's it, you've made it to the end. Here's the complete script for our interactive app.\n\n\n```\nimport streamlit as st\nimport pandas as pd\nimport numpy as np\n\nst.title('Uber pickups in NYC')\n\nDATE_COLUMN = 'date/time'\nDATA_URL = ('https://s3-us-west-2.amazonaws.com/'\n 'streamlit-demo-data/uber-raw-data-sep14.csv.gz')\n\n@st.cache_data\ndef load_data(nrows):\n data = pd.read_csv(DATA_URL, nrows=nrows)\n lowercase = lambda x: str(x).lower()\n data.rename(lowercase, axis='columns', inplace=True)\n data[DATE_COLUMN] = pd.to_datetime(data[DATE_COLUMN])\n return data\n\ndata_load_state = st.text('Loading data...')\ndata = load_data(10000)\ndata_load_state.text(\"Done! (using st.cache_data)\")\n\nif st.checkbox('Show raw data'):\n st.subheader('Raw data')\n st.write(data)\n\nst.subheader('Number of pickups by hour')\nhist_values = np.histogram(data[DATE_COLUMN].dt.hour, bins=24, range=(0,24))[0]\nst.bar_chart(hist_values)\n\n# Some number in the range 0-23\nhour_to_filter = st.slider('hour', 0, 23, 17)\nfiltered_data = data[data[DATE_COLUMN].dt.hour == hour_to_filter]\n\nst.subheader('Map of all pickups at %s:00' % hour_to_filter)\nst.map(filtered_data)\n\n```\n","answer":"``\nst.subheader('Number of pickups by hour')\nhist_values = np.histogram(data[DATE_COLUMN].dt.hour, bins=24, range=(0,24))[0]\nst.bar_chart(hist_values)\n\n# Some number in the range 0-23\nhour_to_filter = st.slider('hour', 0, 23, 17)\nfiltered_data = data[data[DATE_COLUMN].dt.hour == hour_to_filter]\n``","question_idx":1,"row_idx":14,"model":"gpt-3.5-turbo","idx":15,"Template":0,"persona":"Streamlit expert","response":"<EMPTY 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{"question":"How can I create histograms with different bucket colors in Streamlit","document_title":"API reference","document_link":"https://docs.streamlit.io/1.9.0/library/api-reference/charts/st.plotly_chart#stplotly_chart","document_text":"## st.plotly\\_chart\n\nDisplay an interactive Plotly chart.\n\n\nPlotly is a charting library for Python. The arguments to this function\nclosely follow the ones for Plotly's plot() function. You can find\nmore about Plotly at <https://plot.ly/python>.\n\n\nTo show Plotly charts in Streamlit, call st.plotly\\_chart wherever you\nwould call Plotly's py.plot or py.iplot.\n\n\n\n\n| Function signature[[source]](https://github.com/streamlit/streamlit/blob/1.9.0/lib/streamlit/elements/plotly_chart.py#L42 \"View st.plotly_chart source code on GitHub\") |\n| --- |\n| st.plotly\\_chart(figure\\_or\\_data, use\\_container\\_width=False, sharing=\"streamlit\", \\*\\*kwargs) |\n| Parameters |\n| \n\nfigure\\_or\\_data\n(plotly.graph\\_objs.Figure, plotly.graph\\_objs.Data,)\n | \ndict/list of plotly.graph\\_objs.Figure/Data\nSee <https://plot.ly/python/> for examples of graph descriptions.\n |\n| \n\nuse\\_container\\_width\n(bool)\n | \nIf True, set the chart width to the column width. This takes\nprecedence over the figure's native width value.\n |\n| \n\nsharing\n({'streamlit', 'private', 'secret', 'public'})\n | \nUse 'streamlit' to insert the plot and all its dependencies\ndirectly in the Streamlit app using plotly's offline mode (default).\nUse any other sharing mode to send the chart to Plotly chart studio, which\nrequires an account. See <https://plotly.com/chart-studio/> for more information.\n |\n| \n\n\\*\\*kwargs\n(null)\n | \nAny argument accepted by Plotly's plot() function.\n |\n\n#### Example\n\n\n> \n> The example below comes straight from the examples at\n> <https://plot.ly/python>:\n> \n> \n> \n> ```\n> \n> import streamlit as st\n> import plotly.figure_factory as ff\n> import numpy as np\n> \n> # Add histogram data\n> x1 = np.random.randn(200) - 2\n> x2 = np.random.randn(200)\n> x3 = np.random.randn(200) + 2\n> \n> # Group data together\n> hist_data = [x1, x2, x3]\n> \n> group_labels = ['Group 1', 'Group 2', 'Group 3']\n> \n> # Create distplot with custom bin_size\n> fig = ff.create_distplot(\n> hist_data, group_labels, bin_size=[.1, .25, .5])\n> \n> # Plot!\n> st.plotly_chart(fig, use_container_width=True)\n> \n> ```\n> \n> \n> [(view standalone Streamlit app)](https://share.streamlit.io/streamlit/docs/main/python/api-examples-source/charts.plotly_chart.py) \n> \n\n\n### Theming\n\nPlotly charts are displayed using the Streamlit theme by default. This theme is sleek, user-friendly, and incorporates Streamlit's color palette. The added benefit is that your charts better integrate with the rest of your app's design.\n\nThe Streamlit theme is available from Streamlit 1.16.0 through the `theme=\"streamlit\"` keyword argument. To disable it, and use Plotly's native theme, use `theme=None` instead.\n\nLet's look at an example of charts with the Streamlit theme and the native Plotly theme:\n\n\n```\nimport plotly.express as px\nimport streamlit as st\n\ndf = px.data.gapminder()\n\nfig = px.scatter(\n df.query(\"year==2007\"),\n x=\"gdpPercap\",\n y=\"lifeExp\",\n size=\"pop\",\n color=\"continent\",\n hover_name=\"country\",\n log_x=True,\n size_max=60,\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n # Use the Streamlit theme.\n # This is the default. So you can also omit the theme argument.\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n # Use the native Plotly theme.\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\n```\nClick the tabs in the interactive app below to see the charts with the Streamlit theme enabled and disabled.\n\nIf you're wondering if your own customizations will still be taken into account, don't worry! You can still make changes to your chart configurations. In other words, although we now enable the Streamlit theme by default, you can overwrite it with custom colors or fonts. For example, if you want a chart line to be green instead of the default red, you can do it!\n\nHere's an example of an Plotly chart where a custom color scale is defined and reflected:\n\n\n```\nimport plotly.express as px\nimport streamlit as st\n\nst.subhe","answer":"here is an example in the documentation that creates histograms with different bucket colors:\n> \n> ```\n> \n> import streamlit as st\n> import plotly.figure_factory as ff\n> import numpy as np\n> \n> # Add histogram data\n> x1 = np.random.randn(200) - 2\n> x2 = np.random.randn(200)\n> x3 = np.random.randn(200) + 2\n> \n> # Group data together\n> hist_data = [x1, x2, x3]\n> \n> group_labels = ['Group 1', 'Group 2', 'Group 3']\n> \n> # Create distplot with custom bin_size\n> fig = ff.create_distplot(\n> hist_data, group_labels, bin_size=[.1, .25, .5])\n> \n> # Plot!\n> st.plotly_chart(fig, use_container_width=True)\n> \n> ```\n> \n> \n","question_idx":1,"row_idx":15,"model":"gpt-3.5-turbo","idx":16,"Template":0,"persona":"Streamlit expert","response":"## st.plotly\\_chart\n\nDisplay an interactive Plotly chart.\n\nPlotly is a charting library for Python. The arguments to this function\nclosely follow the ones for Plotly's plot() function. You can find\nmore about Plotly at <https://plot.ly/python>.\n\nTo show Plotly charts in Streamlit, call st.plotly\\_chart wherever you\nwould call Plotly's py.plot or py.iplot.\n\n#### Example\n\n> \n> The example below comes straight from the examples at\n> <https://plot.ly/python>:\n> \n> \n> \n> ```\n> \n> import streamlit as st\n> import plotly.figure_factory as ff\n> import numpy as np\n> \n> # Add histogram data\n> x1 = np.random.randn(200) - 2\n> x2 = np.random.randn(200)\n> x3 = np.random.randn(200) + 2\n> \n> # Group data together\n> hist_data = [x1, x2, x3]\n> \n> group_labels = ['Group 1', 'Group 2', 'Group 3']\n> \n> # Create distplot with custom bin_size\n> fig = ff.create_distplot(\n> hist_data, group_labels, bin_size=[.1, .25, .5])\n> \n> # Plot!\n> st.plotly_chart(fig, use_container_width=True)\n> \n> ```\n> \n> \n> [(view standalone Streamlit app)](https://share.streamlit.io/streamlit/docs/main/python/api-examples-source/charts.plotly_chart.py) \n\n### Theming\n\nPlotly charts are displayed using the Streamlit theme by default. This theme is sleek, user-friendly, and incorporates Streamlit's color palette. The added benefit is that your charts better integrate with the rest of your app's design.\n\nThe Streamlit theme is available from Streamlit 1.16.0 through the `theme=\"streamlit\"` keyword argument. To disable it, and use Plotly's native theme, use `theme=None` instead.","experiment_id":1,"question_embeddings":[0.088330105,0.011396006,-0.017542858,-0.08434498,-0.047787853,0.03425188,0.048996642,0.0034383428,-0.022393193,-0.023409048,-0.07357438,-0.077896774,0.026116539,-0.00085928355,0.039049085,-0.026642563,-0.097047776,-0.022016235,-0.08539825,-0.17395513,0.010976068,-0.05704131,-0.03725233,-0.06842565,-0.0044478704,0.0649463,0.031023948,0.040923957,0.07282005,-0.049106944,0.059667658,-0.0753585,0.062485617,-0.02494093,-0.007864315,-0.019300802,-0.036084615,0.051608577,-0.09109866,0.033572853,0.042465758,0.01174127,-0.019712325,-0.065684274,-0.017155608,0.08364792,-0.073342375,0.01874716,0.037283268,0.025831383,-0.043462474,-0.073857106,0.029871376,0.017697562,0.009775645,-0.036767107,-0.04120292,-0.06703686,0.07610773,-0.10925221,-0.04442994,-0.0074998676,0.022256946,-0.014896059,0.06088412,0.016017038,-0.012465867,0.049446587,0.08847953,-0.018837655,0.019807337,0.06478816,0.06848112,0.055087257,-0.07049523,-0.020874226,-0.011705072,0.048881352,-0.059627306,-0.05197535,-0.027297586,0.014144446,0.037603576,0.040695284,0.017761882,0.06532191,-0.06894137,0.013939522,-0.04712859,0.024932921,-0.062471792,0.066132456,0.002363949,-0.03655384,-0.052409384,0.07198713,0.09174018,-0.006315629,0.06124142,-0.023097236,0.040439002,-0.07812325,0.016205361,-0.014299262,0.07228006,-0.003125131,-0.02446053,0.09691148,0.025791425,-0.037827283,0.048649594,-0.042109657,0.016840104,-0.086937375,-0.017265989,0.075562194,-0.10699093,0.01211867,-0.06403345,0.018178374,0.061768565,-0.002032798,-0.05675274,-0.010576633,-0.034583665,-0.039890874,-0.029935757,-3.2848764e-33,0.0378979,-0.106998086,-0.040995043,0.04149618,0.065572456,0.039515913,-0.008075179,0.003411869,-0.02091417,-0.05122435,-0.005777524,0.037594054,-0.055417888,0.010974505,-0.08005184,-0.052646156,0.007957076,-0.024725603,-0.06924275,-0.037430324,-0.08051367,-0.023205118,0.052269068,-0.012416274,0.016556906,-0.020465432,0.04609017,-0.027405446,0.037574787,0.03561955,0.03827268,0.08577126,0.0042460887,0.014051184,0.05974666,-0.058780804,-0.048364103,0.040574744,-0.043581553,0.07378104,0.061412837,0.0014289903,-0.052190572,-0.00078052504,-0.057369288,0.04606968,0.06747937,-0.030284451,0.009257126,-0.025518835,0.04138671,0.08106319,0.0042691617,-0.014420229,0.11329392,-0.022430757,0.032329742,0.047505144,0.040817976,0.04313649,-0.024551831,0.15228917,0.034013808,0.01941502,0.06144809,-0.036756065,0.10396538,0.070308425,-0.006481227,-0.03454383,-0.00991815,0.037999697,0.016863624,-0.016421068,-0.025025293,-0.04278919,0.066235885,0.010628494,-0.052254688,-0.03445316,-0.01905931,-0.052874748,0.010571877,0.026651157,-0.089318834,0.03158032,0.05560046,0.031757142,-0.11445971,-0.09785465,-0.027041305,0.025731953,0.03934218,-0.10917421,0.0022965784,9.564032e-34,-0.06313915,0.09419001,-0.04081826,0.07181917,0.066276036,0.0030092914,0.13137865,0.035464074,0.045764312,0.051538132,-0.055806544,-0.0046785898,-0.124816924,0.017279215,-0.015864715,-0.040863328,0.0009500781,0.018876879,-0.05487937,-0.037517846,-0.08503278,0.03304914,-0.034198888,0.002668823,-0.04557246,0.050836373,-0.013927419,-0.005447964,0.017712409,0.019973949,0.027383726,0.037844945,-0.014945877,-0.04143812,-0.01959012,-0.105157845,0.06470922,0.013278265,-0.013803623,0.067147404,0.04178529,-0.0632891,-0.010079848,-0.08619708,-0.008960702,0.096153274,-0.035347067,0.06595369,-0.020878192,-0.016643418,-0.019682482,0.013243405,-0.032486048,0.08356432,0.07674347,-0.06361975,0.080223106,0.03534406,0.0060911328,0.0065864087,-0.060241528,-0.10307839,0.10199058,0.00088820775,0.030220982,-0.0011668602,0.0099102575,-0.060083468,-0.042249147,0.017135648,-0.0036030465,-0.0972523,0.07683787,-0.06330369,0.03142023,-0.0026465172,-0.008431761,0.06634554,-0.0038314487,0.010890359,-0.018100841,-0.015494008,0.036994852,0.060362976,0.057365444,0.003517775,-0.0029040098,-0.0502847,0.050799564,0.07383564,0.023432627,0.055715792,-0.02273529,0.058175955,0.08986104,-1.720074e-8,0.022305466,-0.070501976,-0.016909117,0.014119327,0.055804323,0.02039817,-0.06730445,0.059458356,0.035946358,-0.014027031,0.071772315,-0.022881763,-0.003811465,-0.057003707,-0.018651411,-0.04579891,-0.015629753,-0.020469574,0.013314239,0.035074934,-0.026234025,0.0120668635,0.0072116307,0.01317788,-0.08294273,0.02837273,0.017769746,-0.073891856,0.021844728,-0.05221814,-0.0060682157,0.030079223,0.063992664,-0.02636329,-0.026866086,-0.07240491,-0.15313517,0.049820986,-0.04309975,0.0044540553,0.008091409,0.01155717,-0.011134993,-0.015595453,-0.0044206656,0.031132616,0.021964429,0.08499096,-0.029608035,0.09432952,-0.10045928,-0.0016386824,0.045343123,-0.027784642,0.04225195,-0.077244245,-0.025754198,-0.062053796,0.017611738,-0.031203467,0.01756977,-0.025270505,-0.02455264,0.0032717404],"context_embeddings":[0.016751884,-0.025236892,-0.048672583,0.02997803,0.027711188,-0.038145047,-0.034252256,0.05005091,-0.059847552,-0.09300877,-0.021060066,0.013730954,-0.06991956,-0.008946647,0.021214234,-0.07860587,0.0058901994,-0.07577686,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{"question":"How to use the sessionstate feature in Streamlit","document_title":"Configuration","document_link":"https://docs.streamlit.io/library/advanced-features/configuration#view-all-configuration-options","document_text":"re users should point their browsers in order to connect to the app.\n# This is used to: - Set the correct URL for CORS and XSRF protection purposes. - Show the URL on the terminal - Open the browser\n# Default: whatever value is set in server.port.\nserverPort = 8501\n\n\n[mapbox]\n\n# Configure Streamlit to use a custom Mapbox token for elements like st.pydeck_chart and st.map. To get a token for yourself, create an account at https://mapbox.com. It's free (for moderate usage levels)!\n# Default: \"\"\ntoken = \"\"\n\n\n[deprecation]\n\n# Set to false to disable the deprecation warning for the file uploader encoding.\n# Default: true\nshowfileUploaderEncoding = true\n\n# Set to false to disable the deprecation warning for using the global pyplot instance.\n# Default: true\nshowPyplotGlobalUse = true\n\n\n[theme]\n\n# The preset Streamlit theme that your custom theme inherits from. One of \"light\" or \"dark\".\n# base =\n\n# Primary accent color for interactive elements.\n# primaryColor =\n\n# Background color for the main content area.\n# backgroundColor =\n\n# Background color used for the sidebar and most interactive widgets.\n# secondaryBackgroundColor =\n\n# Color used for almost all text.\n# textColor =\n\n# Font family for all text in the app, except code blocks. One of \"sans serif\", \"serif\", or \"monospace\".\n# font =\n\n```\n","answer":"session]\n\n# Enable session state for Streamlit.\n# Warning: this introduces a potential security vulnerability, so use this option with caution and make sure you understand the implications.\n# Default: false\n# enableCORS = true\n<EMPTY MESSAGE","question_idx":2,"row_idx":16,"model":"gpt-3.5-turbo","idx":17,"Template":0,"persona":"Streamlit expert","response":"### Session State and Widget State association\n\nSession State provides the functionality to store variables across reruns. Widget state (i.e. the value of a widget) is also stored in a session.\n\nFor simplicity, we have *unified* this information in one place. i.e. the Session State. This convenience feature makes it super easy to read or write to the widget's state anywhere in the app's code. Session State variables mirror the widget value using the `key` argument.\n\nWe illustrate this with the following example. Let's say we have an app with a slider to represent temperature in Celsius. We can **set** and **get** the value of the temperature widget by using the Session State API, as follows:\n\n```\nimport streamlit as st\n\nif \"celsius\" not in st.session_state:\n # set the initial default value of the slider widget\n st.session_state.celsius = 50.0\n\nst.slider(\n \"Temperature in Celsius\",\n min_value=-100.0,\n max_value=100.0,\n key=\"celsius\"\n)\n\n# This will get the value of the slider widget\nst.write(st.session_state.celsius)\n\n```\n\n### Caveats and limitations\n\nHere are some limitations to keep in mind when using Session State:\n\n* Session State exists for as long as the tab is open and connected to the Streamlit server. As soon as you close the tab, 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{"question":"How can I create histograms with different bucket colors in Streamlit","document_title":"API reference","document_link":"https://docs.streamlit.io/1.11.0/library/api-reference/charts/st.plotly_chart#stplotly_chart","document_text":"ig = px.scatter(\n df,\n x=\"sepal_width\",\n y=\"sepal_length\",\n color=\"sepal_length\",\n color_continuous_scale=\"reds\",\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\n```\nNotice how the custom color scale is still reflected in the chart, even when the Streamlit theme is enabled 👇\n\nFor many more examples of Plotly charts with and without the Streamlit theme, check out the [plotly.streamlit.app](https://plotly.streamlit.app).\n\n","answer":"g = px.scatter(\n df,\n x=\"sepal_width\",\n y=\"sepal_length\",\n color=\"sepal_length\",\n color_continuous_scale=\"reds\",\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n st.plotly_chart(fig, theme=None, use_container_width=True","question_idx":1,"row_idx":17,"model":"gpt-3.5-turbo","idx":18,"Template":0,"persona":"Streamlit expert","response":"Serialization refers to the process of converting an object or data structure into a format that can be persisted and shared, and allowing you to recover the data’s original structure. Python’s built-in [pickle](https://docs.python.org/3/library/pickle.html) module serializes Python objects to a byte stream (\"pickling\") and deserializes the stream into an object (\"unpickling\").\n\nBy default, Streamlit’s [Session State](https://docs.streamlit.io/library/advanced-features/session-state) allows you to persist any Python object for the duration of the session, irrespective of the object’s pickle-serializability. This property lets you store Python primitives such as integers, floating-point numbers, complex numbers and booleans, dataframes, and even [lambdas](https://docs.python.org/3/reference/expressions.html#lambda) returned by functions. However, some execution environments may require serializing all data in Session State, so it may be useful to detect incompatibility during development, or when the execution environment will stop supporting it in the future.\n\nTo that end, Streamlit provides a `runner.enforceSerializableSessionState` [configuration option](https://docs.streamlit.io/library/advanced-features/configuration) that, when set to `true`, only allows pickle-serializable objects in Session State. To enable the option, either create a global or project config file with the following or use it as a command-line flag:\n\n```\n# .streamlit/config.toml\n[runner]\nenforceSerializableSessionState = true\n```\n\nBy \"*pickle-serializable*\", we mean calling `pickle.dumps(obj)` should not raise a [`PicklingError`](https://docs.python.org/3/library/pickle.html#pickle.PicklingError) exception. When the config option is enabled, adding unserializable data to session state should result in an exception. E.g.,\n\n```\nimport streamlit as st\n\ndef unserializable_data():\n return lambda x: x\n\n#👇 results in an exception when enforceSerializableSessionState is on\nst.session_state.unserializable = unserializable_data()\n\n```\n![UnserializableSessionStateError](https://docs.streamlit.io/images/unserializable-session-state-error.png)","experiment_id":1,"question_embeddings":[0.088330105,0.011396006,-0.017542858,-0.08434498,-0.047787853,0.03425188,0.048996642,0.0034383428,-0.022393193,-0.023409048,-0.07357438,-0.077896774,0.026116539,-0.00085928355,0.039049085,-0.026642563,-0.097047776,-0.022016235,-0.08539825,-0.17395513,0.010976068,-0.05704131,-0.03725233,-0.06842565,-0.0044478704,0.0649463,0.031023948,0.040923957,0.07282005,-0.049106944,0.059667658,-0.0753585,0.062485617,-0.02494093,-0.007864315,-0.019300802,-0.036084615,0.051608577,-0.09109866,0.033572853,0.042465758,0.01174127,-0.019712325,-0.065684274,-0.017155608,0.08364792,-0.073342375,0.01874716,0.037283268,0.025831383,-0.043462474,-0.073857106,0.029871376,0.017697562,0.009775645,-0.036767107,-0.04120292,-0.06703686,0.07610773,-0.10925221,-0.04442994,-0.0074998676,0.022256946,-0.014896059,0.06088412,0.016017038,-0.012465867,0.049446587,0.08847953,-0.018837655,0.019807337,0.06478816,0.06848112,0.055087257,-0.07049523,-0.020874226,-0.011705072,0.048881352,-0.059627306,-0.05197535,-0.027297586,0.014144446,0.037603576,0.040695284,0.017761882,0.06532191,-0.06894137,0.013939522,-0.04712859,0.024932921,-0.062471792,0.066132456,0.002363949,-0.03655384,-0.052409384,0.07198713,0.09174018,-0.006315629,0.06124142,-0.023097236,0.040439002,-0.07812325,0.016205361,-0.014299262,0.07228006,-0.003125131,-0.02446053,0.09691148,0.025791425,-0.037827283,0.048649594,-0.042109657,0.016840104,-0.086937375,-0.017265989,0.075562194,-0.10699093,0.01211867,-0.06403345,0.018178374,0.061768565,-0.002032798,-0.05675274,-0.010576633,-0.034583665,-0.039890874,-0.029935757,-3.2848764e-33,0.0378979,-0.106998086,-0.040995043,0.04149618,0.065572456,0.039515913,-0.008075179,0.003411869,-0.02091417,-0.05122435,-0.005777524,0.037594054,-0.055417888,0.010974505,-0.08005184,-0.052646156,0.007957076,-0.024725603,-0.06924275,-0.037430324,-0.08051367,-0.023205118,0.052269068,-0.012416274,0.016556906,-0.020465432,0.04609017,-0.027405446,0.037574787,0.03561955,0.03827268,0.08577126,0.0042460887,0.014051184,0.05974666,-0.058780804,-0.048364103,0.040574744,-0.043581553,0.07378104,0.061412837,0.0014289903,-0.052190572,-0.00078052504,-0.057369288,0.04606968,0.06747937,-0.030284451,0.009257126,-0.025518835,0.04138671,0.08106319,0.0042691617,-0.014420229,0.11329392,-0.022430757,0.032329742,0.047505144,0.040817976,0.04313649,-0.024551831,0.15228917,0.034013808,0.01941502,0.06144809,-0.036756065,0.10396538,0.070308425,-0.006481227,-0.03454383,-0.00991815,0.037999697,0.016863624,-0.016421068,-0.025025293,-0.04278919,0.066235885,0.010628494,-0.052254688,-0.03445316,-0.01905931,-0.052874748,0.010571877,0.026651157,-0.089318834,0.03158032,0.05560046,0.031757142,-0.11445971,-0.09785465,-0.027041305,0.025731953,0.03934218,-0.10917421,0.0022965784,9.564032e-34,-0.06313915,0.09419001,-0.04081826,0.07181917,0.066276036,0.0030092914,0.13137865,0.035464074,0.045764312,0.051538132,-0.055806544,-0.0046785898,-0.124816924,0.017279215,-0.015864715,-0.040863328,0.0009500781,0.018876879,-0.05487937,-0.037517846,-0.08503278,0.03304914,-0.034198888,0.002668823,-0.04557246,0.050836373,-0.013927419,-0.005447964,0.017712409,0.019973949,0.027383726,0.037844945,-0.014945877,-0.04143812,-0.01959012,-0.105157845,0.06470922,0.013278265,-0.013803623,0.067147404,0.04178529,-0.0632891,-0.010079848,-0.08619708,-0.008960702,0.096153274,-0.035347067,0.06595369,-0.020878192,-0.016643418,-0.019682482,0.013243405,-0.032486048,0.08356432,0.07674347,-0.06361975,0.080223106,0.03534406,0.0060911328,0.0065864087,-0.060241528,-0.10307839,0.10199058,0.00088820775,0.030220982,-0.0011668602,0.0099102575,-0.060083468,-0.042249147,0.017135648,-0.0036030465,-0.0972523,0.07683787,-0.06330369,0.03142023,-0.0026465172,-0.008431761,0.06634554,-0.0038314487,0.010890359,-0.018100841,-0.015494008,0.036994852,0.060362976,0.057365444,0.003517775,-0.0029040098,-0.0502847,0.050799564,0.07383564,0.023432627,0.055715792,-0.02273529,0.058175955,0.08986104,-1.720074e-8,0.022305466,-0.070501976,-0.016909117,0.014119327,0.055804323,0.02039817,-0.06730445,0.059458356,0.035946358,-0.014027031,0.071772315,-0.022881763,-0.003811465,-0.057003707,-0.018651411,-0.04579891,-0.015629753,-0.020469574,0.013314239,0.035074934,-0.026234025,0.0120668635,0.0072116307,0.01317788,-0.08294273,0.02837273,0.017769746,-0.073891856,0.021844728,-0.05221814,-0.0060682157,0.030079223,0.063992664,-0.02636329,-0.026866086,-0.07240491,-0.15313517,0.049820986,-0.04309975,0.0044540553,0.008091409,0.01155717,-0.011134993,-0.015595453,-0.0044206656,0.031132616,0.021964429,0.08499096,-0.029608035,0.09432952,-0.10045928,-0.0016386824,0.045343123,-0.027784642,0.04225195,-0.077244245,-0.025754198,-0.062053796,0.017611738,-0.031203467,0.01756977,-0.025270505,-0.02455264,0.0032717404],"context_embeddings":[0.10312815,-0.075470366,-0.003319214,0.012652912,0.073125444,-0.013450781,0.009499983,0.00187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{"question":"How to use the sessionstate feature in Streamlit","document_title":"Add statefulness to apps","document_link":"https://docs.streamlit.io/library/advanced-features/session-state#caveats-and-limitations","document_text":"verything stored in Session State is lost.\n* Session State is not persisted. If the Streamlit server crashes, then everything stored in Session State gets wiped\n* For caveats and limitations with the Session State API, please see the [API limitations](https://docs.streamlit.io/library/api-reference/session-state#caveats-and-limitations).\n","answer":" Session State is not persisted. If the Streamlit server crashes, then everything stored in Session State gets wiped\n* For caveats and limitations with the Session State API, please see the [API limitations](https://docs.streamlit.io/library/api-reference/session-state#caveats-and-limitations)","question_idx":2,"row_idx":18,"model":"gpt-3.5-turbo","idx":19,"Template":0,"persona":"Streamlit expert","response":"<EMPTY 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{"question":"How can I create histograms with different bucket colors in Streamlit","document_title":"API reference","document_link":"https://docs.streamlit.io/1.11.0/library/api-reference/charts/st.plotly_chart#stplotly_chart","document_text":"## st.plotly\\_chart\n\nDisplay an interactive Plotly chart.\n\n\nPlotly is a charting library for Python. The arguments to this function\nclosely follow the ones for Plotly's plot() function. You can find\nmore about Plotly at <https://plot.ly/python>.\n\n\nTo show Plotly charts in Streamlit, call st.plotly\\_chart wherever you\nwould call Plotly's py.plot or py.iplot.\n\n\n\n\n| Function signature[[source]](https://github.com/streamlit/streamlit/blob/1.11.0/lib/streamlit/elements/plotly_chart.py#L67 \"View st.plotly_chart source code on GitHub\") |\n| --- |\n| st.plotly\\_chart(figure\\_or\\_data, use\\_container\\_width=False, sharing=\"streamlit\", \\*\\*kwargs) |\n| Parameters |\n| \n\nfigure\\_or\\_data\n(plotly.graph\\_objs.Figure, plotly.graph\\_objs.Data,)\n | \ndict/list of plotly.graph\\_objs.Figure/Data\nSee <https://plot.ly/python/> for examples of graph descriptions.\n |\n| \n\nuse\\_container\\_width\n(bool)\n | \nIf True, set the chart width to the column width. This takes\nprecedence over the figure's native width value.\n |\n| \n\nsharing\n({'streamlit', 'private', 'secret', 'public'})\n | \nUse 'streamlit' to insert the plot and all its dependencies\ndirectly in the Streamlit app using plotly's offline mode (default).\nUse any other sharing mode to send the chart to Plotly chart studio, which\nrequires an account. See <https://plotly.com/chart-studio/> for more information.\n |\n| \n\n\\*\\*kwargs\n(null)\n | \nAny argument accepted by Plotly's plot() function.\n |\n\n#### Example\n\n\n> \n> The example below comes straight from the examples at\n> <https://plot.ly/python>:\n> \n> \n> \n> ```\n> \n> import streamlit as st\n> import plotly.figure_factory as ff\n> import numpy as np\n> \n> # Add histogram data\n> x1 = np.random.randn(200) - 2\n> x2 = np.random.randn(200)\n> x3 = np.random.randn(200) + 2\n> \n> # Group data together\n> hist_data = [x1, x2, x3]\n> \n> group_labels = ['Group 1', 'Group 2', 'Group 3']\n> \n> # Create distplot with custom bin_size\n> fig = ff.create_distplot(\n> hist_data, group_labels, bin_size=[.1, .25, .5])\n> \n> # Plot!\n> st.plotly_chart(fig, use_container_width=True)\n> \n> ```\n> \n> \n> [(view standalone Streamlit app)](https://doc-plotly-chart.streamlit.app/) \n> \n\n\n### Theming\n\nPlotly charts are displayed using the Streamlit theme by default. This theme is sleek, user-friendly, and incorporates Streamlit's color palette. The added benefit is that your charts better integrate with the rest of your app's design.\n\nThe Streamlit theme is available from Streamlit 1.16.0 through the `theme=\"streamlit\"` keyword argument. To disable it, and use Plotly's native theme, use `theme=None` instead.\n\nLet's look at an example of charts with the Streamlit theme and the native Plotly theme:\n\n\n```\nimport plotly.express as px\nimport streamlit as st\n\ndf = px.data.gapminder()\n\nfig = px.scatter(\n df.query(\"year==2007\"),\n x=\"gdpPercap\",\n y=\"lifeExp\",\n size=\"pop\",\n color=\"continent\",\n hover_name=\"country\",\n log_x=True,\n size_max=60,\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n # Use the Streamlit theme.\n # This is the default. So you can also omit the theme argument.\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n # Use the native Plotly theme.\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\n```\nClick the tabs in the interactive app below to see the charts with the Streamlit theme enabled and disabled.\n\nIf you're wondering if your own customizations will still be taken into account, don't worry! You can still make changes to your chart configurations. In other words, although we now enable the Streamlit theme by default, you can overwrite it with custom colors or fonts. For example, if you want a chart line to be green instead of the default red, you can do it!\n\nHere's an example of an Plotly chart where a custom color scale is defined and reflected:\n\n\n```\nimport plotly.express as px\nimport streamlit as st\n\nst.subheader(\"Define a custom colorscale\")\ndf = px.data.iris()\nf","answer":"Display an interactive Plotly chart.\"\n\n\"Plotly is a charting library for Python.\"\n\n\"The arguments to this function closely follow the ones for Plotly's plot() function.\"\n\n\"import streamlit as st\"\n\n\"The example below comes straight from the examples at <https://plot.ly/python>\"\n\n\"st.plotly_chart(figure\\_or\\_data, use\\_container\\_width=False, sharing=\"streamlit\", \\*\\*kwargs)\"\n\n\"The Streamlit theme is available from Streamlit 1.16.0 through the `theme=\"streamlit\"` keyword argument. To disable it, and use Plotly's native theme, use `theme=None` instead.\"\n\n\"In other words, although we now enable the Streamlit theme by default, you can overwrite it with custom colors or fonts.","question_idx":1,"row_idx":19,"model":"gpt-3.5-turbo","idx":20,"Template":0,"persona":"Streamlit expert","response":"| Function signature[[source]](https://github.com/streamlit/streamlit/blob/1.4.0/lib/streamlit/elements/plotly_chart.py#L42 \"View st.plotly_chart source code on GitHub\") |\n| --- |\n| st.plotly\\_chart(figure\\_or\\_data, use\\_container\\_width=False, sharing=\"streamlit\", \\*\\*kwargs) |\n| Parameters |\n| \n\nfigure\\_or\\_data\n(plotly.graph\\_objs.Figure, plotly.graph\\_objs.Data,)\n | \ndict/list of plotly.graph\\_objs.Figure/Data\nSee <https://plot.ly/python/> for examples of graph descriptions.\n |\n| \n\nuse\\_container\\_width\n(bool)\n | \nIf True, set the chart width to the column width. This takes\nprecedence over the figure's native width value.\n |\n| \n\nsharing\n({'streamlit', 'private', 'secret', 'public'})\n | \nUse 'streamlit' to insert the plot and all its dependencies\ndirectly in the Streamlit app using plotly's offline mode (default).\nUse any other sharing mode to send the chart to Plotly chart studio, which\nrequires an account. See <https://plotly.com/chart-studio/> for more information.\n |\n| \n\n\\*\\*kwargs\n(null)\n | \nAny argument accepted by Plotly's plot() function.\n |\n\n> ```\n> \n> import streamlit as st\n> import plotly.figure_factory as ff\n> import numpy as np\n> \n> # Add histogram data\n> x1 = np.random.randn(200) - 2\n> x2 = np.random.randn(200)\n> x3 = np.random.randn(200) + 2\n> \n> # Group data together\n> hist_data = [x1, x2, x3]\n> \n> group_labels = ['Group 1', 'Group 2', 'Group 3']\n> \n> # Create distplot with custom bin_size\n> fig = ff.create_distplot(\n> hist_data, group_labels, bin_size=[.1, .25, .5])\n> \n> # Plot!\n> st.plotly_chart(fig, use_container_width=True)\n> \n> ```\n> \n\n<EMPTY 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{"question":"How can I create histograms with different bucket colors in Streamlit","document_title":"API reference","document_link":"https://docs.streamlit.io/1.7.0/library/api-reference/charts/st.plotly_chart#stplotly_chart","document_text":"## st.plotly\\_chart\n\nDisplay an interactive Plotly chart.\n\n\nPlotly is a charting library for Python. The arguments to this function\nclosely follow the ones for Plotly's plot() function. You can find\nmore about Plotly at <https://plot.ly/python>.\n\n\nTo show Plotly charts in Streamlit, call st.plotly\\_chart wherever you\nwould call Plotly's py.plot or py.iplot.\n\n\n\n\n| Function signature[[source]](https://github.com/streamlit/streamlit/blob/1.7.0/lib/streamlit/elements/plotly_chart.py#L42 \"View st.plotly_chart source code on GitHub\") |\n| --- |\n| st.plotly\\_chart(figure\\_or\\_data, use\\_container\\_width=False, sharing=\"streamlit\", \\*\\*kwargs) |\n| Parameters |\n| \n\nfigure\\_or\\_data\n(plotly.graph\\_objs.Figure, plotly.graph\\_objs.Data,)\n | \ndict/list of plotly.graph\\_objs.Figure/Data\nSee <https://plot.ly/python/> for examples of graph descriptions.\n |\n| \n\nuse\\_container\\_width\n(bool)\n | \nIf True, set the chart width to the column width. This takes\nprecedence over the figure's native width value.\n |\n| \n\nsharing\n({'streamlit', 'private', 'secret', 'public'})\n | \nUse 'streamlit' to insert the plot and all its dependencies\ndirectly in the Streamlit app using plotly's offline mode (default).\nUse any other sharing mode to send the chart to Plotly chart studio, which\nrequires an account. See <https://plotly.com/chart-studio/> for more information.\n |\n| \n\n\\*\\*kwargs\n(null)\n | \nAny argument accepted by Plotly's plot() function.\n |\n\n#### Example\n\n\n> \n> The example below comes straight from the examples at\n> <https://plot.ly/python>:\n> \n> \n> \n> ```\n> \n> import streamlit as st\n> import plotly.figure_factory as ff\n> import numpy as np\n> \n> # Add histogram data\n> x1 = np.random.randn(200) - 2\n> x2 = np.random.randn(200)\n> x3 = np.random.randn(200) + 2\n> \n> # Group data together\n> hist_data = [x1, x2, x3]\n> \n> group_labels = ['Group 1', 'Group 2', 'Group 3']\n> \n> # Create distplot with custom bin_size\n> fig = ff.create_distplot(\n> hist_data, group_labels, bin_size=[.1, .25, .5])\n> \n> # Plot!\n> st.plotly_chart(fig, use_container_width=True)\n> \n> ```\n> \n> \n> [(view standalone Streamlit app)](https://share.streamlit.io/streamlit/docs/main/python/api-examples-source/charts.plotly_chart.py) \n> \n\n\n### Theming\n\nPlotly charts are displayed using the Streamlit theme by default. This theme is sleek, user-friendly, and incorporates Streamlit's color palette. The added benefit is that your charts better integrate with the rest of your app's design.\n\nThe Streamlit theme is available from Streamlit 1.16.0 through the `theme=\"streamlit\"` keyword argument. To disable it, and use Plotly's native theme, use `theme=None` instead.\n\nLet's look at an example of charts with the Streamlit theme and the native Plotly theme:\n\n\n```\nimport plotly.express as px\nimport streamlit as st\n\ndf = px.data.gapminder()\n\nfig = px.scatter(\n df.query(\"year==2007\"),\n x=\"gdpPercap\",\n y=\"lifeExp\",\n size=\"pop\",\n color=\"continent\",\n hover_name=\"country\",\n log_x=True,\n size_max=60,\n)\n\ntab1, tab2 = st.tabs([\"Streamlit theme (default)\", \"Plotly native theme\"])\nwith tab1:\n # Use the Streamlit theme.\n # This is the default. So you can also omit the theme argument.\n st.plotly_chart(fig, theme=\"streamlit\", use_container_width=True)\nwith tab2:\n # Use the native Plotly theme.\n st.plotly_chart(fig, theme=None, use_container_width=True)\n\n```\nClick the tabs in the interactive app below to see the charts with the Streamlit theme enabled and disabled.\n\nIf you're wondering if your own customizations will still be taken into account, don't worry! You can still make changes to your chart configurations. In other words, although we now enable the Streamlit theme by default, you can overwrite it with custom colors or fonts. For example, if you want a chart line to be green instead of the default red, you can do it!\n\nHere's an example of an Plotly chart where a custom color scale is defined and reflected:\n\n\n```\nimport plotly.express as px\nimport streamlit as st\n\nst.subhe","answer":"unction signature:\nst.plotly\\_chart(figure\\_or\\_data, use\\_container\\_width=False, sharing=\"streamlit\", \\*\\*kwargs)\n\nParameters:\nfigure\\_or\\_data\n(plotly.graph\\_objs.Figure, plotly.graph\\_objs.Data,)\n | \ndict/list of plotly.graph\\_objs.Figure/Data\nSee <https://plot.ly/python/> for examples of graph descriptions.\n\nuse\\_container\\_width\n(bool)\n | \nIf True, set the chart width to the column width. This takes\nprecedence over the figure's native width value.\n\n\\*\\*kwargs\n(null)\n | \nAny argument accepted by Plotly's plot() function.\n\n#### Example:\n```\n\nimport streamlit as st\nimport plotly.figure_factory as ff\nimport numpy as np\n\n# Add histogram data\nx1 = np.random.randn(200) - 2\nx2 = np.random.randn(200)\nx3 = np.random.randn(200) + 2\n\n# Group data together\nhist_data = [x1, x2, x3]\n\ngroup_labels = ['Group 1', 'Group 2', 'Group 3']\n\n# Create distplot with custom bin_size\nfig = ff.create_distplot(\n hist_data, group_labels, bin_size=[.1, .25, .5])\n\n# Plot!\nst.plotly_chart(fig, use_container_width=True)\n\n```\nTheming:\nPlotly charts are displayed using the Streamlit theme by default. This theme is sleek, user-friendly, and incorporates Streamlit's color palette. The added benefit is that your charts better integrate with the rest of your app's design","question_idx":1,"row_idx":20,"model":"gpt-3.5-turbo","idx":21,"Template":0,"persona":"Streamlit expert","response":"| Function signature[[source]](https://github.com/streamlit/streamlit/blob/1.10.0/lib/streamlit/elements/plotly_chart.py#L67 \"View st.plotly_chart source code on GitHub\") |\n| --- |\n| st.plotly\\_chart(figure\\_or\\_data, use\\_container\\_width=False, sharing=\"streamlit\", \\*\\*kwargs) |\n| Parameters |\n| \n\nfigure\\_or\\_data\n(plotly.graph\\_objs.Figure, plotly.graph\\_objs.Data,)\n | \ndict/list of plotly.graph\\_objs.Figure/Data\nSee <https://plot.ly/python/> for examples of graph descriptions.\n |\n| \n\nuse\\_container\\_width\n(bool)\n | \nIf True, set the chart width to the column width. This takes\nprecedence over the figure's native width value.\n |\n| \n\nsharing\n({'streamlit', 'private', 'secret', 'public'})\n | \nUse 'streamlit' to insert the plot and all its dependencies\ndirectly in the Streamlit app using plotly's offline mode (default).\nUse any other sharing mode to send the chart to Plotly chart studio, which\nrequires an account. See <https://plotly.com/chart-studio/> for more information.\n |\n| \n\n\\*\\*kwargs\n(null)\n | \nAny argument accepted by Plotly's plot() function.\n |\n\n> ```\n> \n> import streamlit as st\n> import plotly.figure_factory as ff\n> import numpy as np\n> \n> # Add histogram data\n> x1 = np.random.randn(200) - 2\n> x2 = np.random.randn(200)\n> x3 = np.random.randn(200) + 2\n> \n> # Group data together\n> hist_data = [x1, x2, x3]\n> \n> group_labels = ['Group 1', 'Group 2', 'Group 3']\n> \n> # Create distplot with custom bin_size\n> fig = ff.create_distplot(\n> hist_data, group_labels, bin_size=[.1, .25, .5])\n> \n> # Plot!\n> st.plotly_chart(fig, use_container_width=True)\n> \n> ```\n> \n\n<EMPTY 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