Created
November 21, 2019 06:06
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Facebook Prophet Gold price prediction
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import pandas as pd | |
from fbprophet import Prophet | |
import sys | |
import matplotlib.pyplot as plt | |
from fbprophet.diagnostics import cross_validation | |
from fbprophet.diagnostics import performance_metrics | |
from fbprophet.plot import plot_cross_validation_metric | |
plt.style.use('fivethirtyeight') | |
df = pd.read_csv('gold.csv') | |
df = df[['ds','USD (AM)']].rename(columns={"USD (AM)": "y"}) | |
m = Prophet(daily_seasonality=False, interval_width=0.95) | |
m.fit(df) | |
future = m.make_future_dataframe(periods=365) | |
forecast = m.predict(future) | |
fig1 = m.plot(forecast) | |
plt.xlabel("Date") | |
plt.ylabel("Gold Price") | |
plt.show() | |
fig2 = m.plot_components(forecast) | |
plt.show() | |
df_cv = cross_validation(m, initial='730 days', period='180 days', horizon = '365 days') | |
df_cv.head() | |
df_p = performance_metrics(df_cv) | |
df_p.head() | |
fig = plot_cross_validation_metric(df_cv, metric='rmse') | |
plt.show() |
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