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How to Check if Time Series Data is Stationary with Python
I am having about 1000+ different time-series dataset in the format of (year,number) and need to forecast the values in next 5 years.
For models like ARIMA the dataset should fulfill stationarity before performing the forecasting. If the data does not fulfill the stationarity we have to diffrenciate the dataset and re-check, if not differenciate again and re-check etc.
Therefore, I would like to know if there is a way to automate the aforementioned stationarity check step?
If so, please let me know how I can automate it for my 1000+ different datasets for time-series forcasting?
python time-series arima
asked Nov 20 '18 at 1:42
J CenaJ Cena
343216
add a comment |
I am having about 1000+ different time-series dataset in the format of (year,number) and need to forecast the values in next 5 years.
For models like ARIMA the dataset should fulfill stationarity before performing the forecasting. If the data does not fulfill the stationarity we have to diffrenciate the dataset and re-check, if not differenciate again and re-check etc.
Therefore, I would like to know if there is a way to automate the aforementioned stationarity check step?
If so, please let me know how I can automate it for my 1000+ different datasets for time-series forcasting?
python time-series arima
asked Nov 20 '18 at 1:42
J CenaJ Cena
343216
add a comment |
I am having about 1000+ different time-series dataset in the format of (year,number) and need to forecast the values in next 5 years.
For models like ARIMA the dataset should fulfill stationarity before performing the forecasting. If the data does not fulfill the stationarity we have to diffrenciate the dataset and re-check, if not differenciate again and re-check etc.
Therefore, I would like to know if there is a way to automate the aforementioned stationarity check step?
If so, please let me know how I can automate it for my 1000+ different datasets for time-series forcasting?
python time-series arima
asked Nov 20 '18 at 1:42
J CenaJ Cena
343216
I am having about 1000+ different time-series dataset in the format of (year,number) and need to forecast the values in next 5 years.
For models like ARIMA the dataset should fulfill stationarity before performing the forecasting. If the data does not fulfill the stationarity we have to diffrenciate the dataset and re-check, if not differenciate again and re-check etc.
Therefore, I would like to know if there is a way to automate the aforementioned stationarity check step?
If so, please let me know how I can automate it for my 1000+ different datasets for time-series forcasting?
python time-series arima
python time-series arima
asked Nov 20 '18 at 1:42
J CenaJ Cena
343216
asked Nov 20 '18 at 1:42
J CenaJ Cena
343216
edited Nov 20 '18 at 4:56
J Cena
asked Nov 20 '18 at 1:42
J CenaJ Cena
343216
asked Nov 20 '18 at 1:42
J CenaJ Cena
343216
asked Nov 20 '18 at 1:42
J CenaJ Cena
343216
343216
add a comment |
add a comment |
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