Prophetでcovid-19の入院治療を要する人数を予測する
Prophetを使用したサンプルとして、厚生労働省のオープンデータを使用して、入院治療等を要する人数を予測してみました。 %matplotlib inline import urllib import numpy as np import pandas as pd import matplotlib.pyplot as plt from fbprophet import Prophet cases_total_req = urllib.request.urlopen('https://www.mhlw.go.jp/content/cases_total.csv') cases_total_df = pd.read_csv(cases_total_req) cases_total_df['ds'] = pd.to_datetime(cases_total_df['日付']).dt.date cases_total_df['y'] = cases_total_df['入院治療を要する者'] cases_total_df['y'].plot() <matplotlib.axes._subplots.AxesSubplot at 0x1648a3d9c88> model = Prophet() model.fit(cases_total_df) INFO:fbprophet:Disabling yearly seasonality. Run prophet with yearly_seasonality=True to override this. INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this. <fbprophet.forecaster.Prophet at 0x1648a8297c8> future = model.make_future_dataframe(periods=365) forecast = model.predict(future) model.plot(forecast)