для ключа, значение в dftest [4] .items (): dfoutput ['Критическое значение (% s)'% ключ] = значение
#moving onto adcf test
из statsmodels.tsa.stattools import adfuller def test_stationarity (timeseries): # определение скользящей статистики. movingAverage = timeseries.rolling (window = 12) .mean () movingSTD = timeseries.rolling (window = 12) .std ()
#plot rolling statistics.
orig=plt.plot(timeseries,color='blue',label='Original')
mean=plt.plot(movingAverage,color='red',label='Rolling mean')
std=plt.plot(movingSTD,color='black',label="Rolling std")
plt.legend(loc='best')
plt.title('Rolling mean & standard deviation')
plt.show(block=False)
#perform Dickey -fuller test:
print('Results of Dickey-Fuller Test:')
dftest= adfuller(timeseries['Sales'],autolag='AIC')
dfoutput= pd.Series(dftest[0:4],index=['Test Statistic','p-value','Lags used','no.of observation used'])
for key,value in dftest[4].items():
dfoutput['Critical Value (%s)'%key] = value
print(dfoutput)