Time series analysis python


my data plot has no positive or negative trend also there are data of day wise.
Still the mean and std plot is not straight line ? still is it not stationary? confused since visually we cannot say and after dickey fuller plot also getting a bad p value which is .1608



did u handle outliners , also have you tried to apply any transformations to the dataset



Hi ,

Thanks for the reply.
I have used the box plot to remove them also read the articles about time series but still confused, what exactly this transformation do ? And when we train our model on these transformed series how can it predict values based on our series, suggest me some transformation techniques though



hi kunal, transformation techniques are used when the data seems to be highly skewed to achive normality or to reduce variance, when u try dickery fuller test in time series u can observe the p-value if it is more than critical value , u can try to transform data(e.g log, sqrt, sine etc…) and rerun the test for satisfied p-value. Note: after applying transformation u need to revert the obtained result to original scale(re.g for log - 10 power, sqrt- squaring , sine-inverse sine etc.)



Also i have an issues running the predict function on the result from the ARIMA,

Function :
start_index = ‘2015-12-26’
end_index = ‘2016-02-14’
print(results_AR.predict(start=start_index, end=end_index))

ERROR : KeyError: ‘only integers, slices ( : ), ellipsis ( ... ), numpy.newaxis ( None ) and integer or boolean arrays are valid indices’

why is this error and how do i solve ?