airalcorn2 · August 28, 2024 14:34
diff --git a/plot_check_ins.py b/plot_check_ins.py
 # Adapted from: https://stackoverflow.com/a/77261943/1316276.

 import matplotlib

 matplotlib.use("Agg")

 import geodatasets
 import geopandas as gpd
 import glob
 import json
 import matplotlib.pyplot as plt
 import os
 import pandas as pd
 import requests

 from datetime import datetime, timedelta
 from json import JSONDecodeError
 from shapely.geometry import Point


 def get_checkins(foursquare_path):
    api_key_path = f"{foursquare_path}/fsq_api_key.txt"
    with open(api_key_path) as f:
        api_key = f.read().strip()

    headers = {"accept": "application/json", "Authorization": api_key}
    url = "https://api.foursquare.com/v3/places/{fsq_id}?fields=geocodes"

    rows = []
    checkin_jsons = glob.glob(f"{foursquare_path}/checkins*.json")
    for checkin_json in checkin_jsons:
        with open(checkin_json) as f:
            checkins = json.load(f)

        for checkin in checkins["items"]:
            try:
                fsq_id = checkin["venue"]["id"]
            except KeyError:
                continue

            response = requests.get(url.format(fsq_id=fsq_id), headers=headers)
            try:
                locations = response.json()
                rows.append(
                    {
                        "name": checkin["venue"]["name"],
                        "fsq_id": fsq_id,
                        "date": checkin["createdAt"],
                        "lat": locations["geocodes"]["main"]["latitude"],
                        "lon": locations["geocodes"]["main"]["longitude"],
                    }
                )
            except JSONDecodeError:
                continue
            except KeyError:
                continue

    df = pd.DataFrame(rows)
    df.to_csv(f"{foursquare_path}/all_checkins.csv", index=False)


 def save_maps(foursquare_path):
    df = pd.read_csv(f"{foursquare_path}/all_checkins.csv")
    geometry = [Point(xy) for xy in zip(df["lon"], df["lat"])]
    gdf = gpd.GeoDataFrame(df, geometry=geometry)
    gdf.set_crs(epsg=4326, inplace=True)

    world = gpd.read_file(geodatasets.get_path("naturalearth.land"))

    output_dir = "maps"
    os.makedirs(output_dir)
    cur_date = datetime.strptime(df["date"].min().split()[0], "%Y-%m-%d")
    end_date = datetime.strptime(df["date"].max().split()[0], "%Y-%m-%d")
    days = (end_date - cur_date).days
    for day in range(days + 1):
        plt.close("all")
        ax = world.plot(figsize=(10, 6), color="lightgray", edgecolor="black")

        cur_date_start = cur_date.strftime("%Y-%m-%d 00:00:00.000000")
        prev_checkins = gdf[gdf["date"] < cur_date_start]
        if len(prev_checkins) > 0:
            prev_checkins.plot(ax=ax, color="blue", markersize=20)

        cur_date_end = cur_date.strftime("%Y-%m-%d 24:00:00.000000")
        today_checkins = gdf[
            (cur_date_start < gdf["date"]) & (gdf["date"] < cur_date_end)
        ]
        if len(today_checkins) > 0:
            today_checkins.plot(ax=ax, color="red", markersize=40)

        checkins = gdf[gdf["date"] < cur_date_end]
        n_checkins = len(checkins)
        n_places = len(checkins["fsq_id"].unique())

        cur_date_str = cur_date_start.split()[0]
        ax.set_title(f"{cur_date_str}  Check-ins: {n_checkins}  Places: {n_places}")
        ax.axis("off")
        ax.set_aspect("equal")
        plt.savefig(f"{output_dir}/{cur_date_str}.png", dpi=300, bbox_inches="tight")

        cur_date += timedelta(days=1)


 def main():
    foursquare_path = "/home/airalcorn2/Documents/Foursquare"
    get_checkins(foursquare_path)
    save_maps(foursquare_path)
    # To create a video of the saved images, in the maps directory, run:
    # ffmpeg -framerate 14 -pattern_type glob -i 'maps/*.png' -c:v libx264 out.mp4


 if __name__ == "__main__":
    main()
	# Adapted from: https://stackoverflow.com/a/77261943/1316276.

	import matplotlib

	matplotlib.use("Agg")

	import geodatasets
	import geopandas as gpd
	import glob
	import json
	import matplotlib.pyplot as plt
	import os
	import pandas as pd
	import requests

	from datetime import datetime, timedelta
	from json import JSONDecodeError
	from shapely.geometry import Point


	def get_checkins(foursquare_path):
	api_key_path = f"{foursquare_path}/fsq_api_key.txt"
	with open(api_key_path) as f:
	api_key = f.read().strip()

	headers = {"accept": "application/json", "Authorization": api_key}
	url = "https://api.foursquare.com/v3/places/{fsq_id}?fields=geocodes"

	rows = []
	checkin_jsons = glob.glob(f"{foursquare_path}/checkins*.json")
	for checkin_json in checkin_jsons:
	with open(checkin_json) as f:
	checkins = json.load(f)

	for checkin in checkins["items"]:
	try:
	fsq_id = checkin["venue"]["id"]
	except KeyError:
	continue

	response = requests.get(url.format(fsq_id=fsq_id), headers=headers)
	try:
	locations = response.json()
	rows.append(
	{
	"name": checkin["venue"]["name"],
	"fsq_id": fsq_id,
	"date": checkin["createdAt"],
	"lat": locations["geocodes"]["main"]["latitude"],
	"lon": locations["geocodes"]["main"]["longitude"],
	}
	)
	except JSONDecodeError:
	continue
	except KeyError:
	continue

	df = pd.DataFrame(rows)
	df.to_csv(f"{foursquare_path}/all_checkins.csv", index=False)


	def save_maps(foursquare_path):
	df = pd.read_csv(f"{foursquare_path}/all_checkins.csv")
	geometry = [Point(xy) for xy in zip(df["lon"], df["lat"])]
	gdf = gpd.GeoDataFrame(df, geometry=geometry)
	gdf.set_crs(epsg=4326, inplace=True)

	world = gpd.read_file(geodatasets.get_path("naturalearth.land"))

	output_dir = "maps"
	os.makedirs(output_dir)
	cur_date = datetime.strptime(df["date"].min().split()[0], "%Y-%m-%d")
	end_date = datetime.strptime(df["date"].max().split()[0], "%Y-%m-%d")
	days = (end_date - cur_date).days
	for day in range(days + 1):
	plt.close("all")
	ax = world.plot(figsize=(10, 6), color="lightgray", edgecolor="black")

	cur_date_start = cur_date.strftime("%Y-%m-%d 00:00:00.000000")
	prev_checkins = gdf[gdf["date"] < cur_date_start]
	if len(prev_checkins) > 0:
	prev_checkins.plot(ax=ax, color="blue", markersize=20)

	cur_date_end = cur_date.strftime("%Y-%m-%d 24:00:00.000000")
	today_checkins = gdf[
	(cur_date_start < gdf["date"]) & (gdf["date"] < cur_date_end)
	]
	if len(today_checkins) > 0:
	today_checkins.plot(ax=ax, color="red", markersize=40)

	checkins = gdf[gdf["date"] < cur_date_end]
	n_checkins = len(checkins)
	n_places = len(checkins["fsq_id"].unique())

	cur_date_str = cur_date_start.split()[0]
	ax.set_title(f"{cur_date_str} Check-ins: {n_checkins} Places: {n_places}")
	ax.axis("off")
	ax.set_aspect("equal")
	plt.savefig(f"{output_dir}/{cur_date_str}.png", dpi=300, bbox_inches="tight")

	cur_date += timedelta(days=1)


	def main():
	foursquare_path = "/home/airalcorn2/Documents/Foursquare"
	get_checkins(foursquare_path)
	save_maps(foursquare_path)
	# To create a video of the saved images, in the maps directory, run:
	# ffmpeg -framerate 14 -pattern_type glob -i 'maps/*.png' -c:v libx264 out.mp4


	if __name__ == "__main__":
	main()