import matplotlib
import pandas as pd
from fbprophet import Prophet

import matplotlib.pyplot as plt
plt.style.use('fivethirtyeight')

#input dataset with one date column and one value column
df = pd.read_csv('syf_prophet.csv')

#parse date column to datetime
df['DOWNLOAD_ACTIVITY_DATE']=df['DOWNLOAD_ACTIVITY_DATE'].astype('datetime64[ns]')
print df.shape
print df.dtypes
 
#rename columns to prophet standard
df = df.rename(columns={'DOWNLOAD_ACTIVITY_DATE': 'ds',
                        'SUM(UNITS)': 'y'})

print df.head(5)

ax = df.set_index('ds').plot(figsize=(12, 8))
ax.set_ylabel('Spotify Streams')
ax.set_xlabel('Date')

#define model
my_model = Prophet(interval_width=0.8)

#fit model
my_model.fit(df)

#make rows for future dates
future_dates = my_model.make_future_dataframe(periods=14)
print future_dates.tail()

#create predictions
forecast = my_model.predict(future_dates)
print forecast[['ds', 'yhat', 'yhat_lower', 'yhat_upper']].tail(14)

my_model.plot(forecast,
              uncertainty=True)
             
my_model.plot_components(forecast)


plt.show()