商業數據挖掘FaceBook工具（「BI」）jetrail

import pandas as pd
import numpy as np

# 數據加載
train = pd.read_csv('./train.csv')
print(train.head())

# 轉換爲pandas中的日期格式
train['Datetime'] = pd.to_datetime(train.Datetime, format='%d-%m-%Y %H:%M')
# 將Datetime作爲train的索引
train.index = train.Datetime
# 去掉ID, Datetime
train.drop(['ID', 'Datetime'], axis=1, inplace=True)

# 按天進行採樣
daily_train = train.resample('D').sum()
daily_train['ds'] = daily_train.index
daily_train['y'] = daily_train.Count
daily_train.drop(['Count'], axis=1, inplace=True)
print(daily_train)

from fbprophet import Prophet
# 擬合prophet模型
m = Prophet(yearly_seasonality=True, seasonality_prior_scale=0.1)
# 使用fit完成擬合
m.fit(daily_train)
# 預測未來7個月，213天
future = m.make_future_dataframe(periods=213)
print(future.tail())
# 預測未來，prophet考慮了 周、月，還有holidays
forecast = m.predict(future)
m.plot(forecast)

# 成分分析
m.plot_components(forecast)