def hw_forecast(df,future,lag=12,method='mul',**kwargs):
forecast=len(df)-1+future
m=es(df,seasonal=method,trend=method,seasonal_periods=lag,**kwargs)
model=m.fit(optimized=True)
return model.predict(start=0,end=forecast)
def hw_smooth(df,future,lag=12,method='mul',**kwargs):
forecast=len(df)-1+future
m=es(df,seasonal=method,trend=method,seasonal_periods=lag,**kwargs)
model=m.fit(optimized=True)
plt.plot(model.predict(start=0,end=forecast),label='fitted', \
color=pick_a_color())
plt.plot(df.index,df,label='actual',color=pick_a_color())
plt.legend(loc='best')
plt.show()