Discussions for article "A comprehensive beginner's guide to create a Time Series Forecast (with Codes in Python)"


Hi All,

The article “A comprehensive beginner’s guide to create a Time Series Forecast (with Codes in Python)” is quiet old now and you might not get a prompt response from the author.

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A brief description of the article -

Time Series Analytics is considered to be one of the less known skills in the analytics space. This article covers Time Series Analysis concepts in an end-to-end manner along with codes in Python. The following steps are covered:

  1. What makes Time Series Special?
  2. Loading and Handling Time Series in Pandas
  3. How to Check Stationarity of a Time Series?
  4. How to make a Time Series Stationary?
  5. Forecasting a Time Series


Here I’m using Python 3.7.0. So some command is not running/causing error. Can you suggest me the replacement for that command which is causing the error.
a) why print is not supporting like print “abc” while your command is displaying as print “abc”.
b) command is not working “rolmean = pd.rolling_mean(timeseries,window=12)”
c) ‘pandas’ has no attribute ‘rolling_mean’
d)pd.ewma(ts_log, halflife=12)
please suggest alternate command for above error



Hi @santosh.gupta,

As the libraries have been updated, you have to make a little changes in the code:

Use print(abc)

Use df.rolling instead of rolling_mean. For more details, refer here.



Whom library is new? Mine or your? can you guide me what changes require. Thanks



Hi @santosh.gupta,

This article has been written a few months ago, so the libraries used in this are outdated. You must be working on the updated libraries so have to make a few changes in the codes.



Hello, This is sumanth and I am new to machine learning and modelling. I took a project based on Time Series for my masters academic subject project from analytics vidhya and can you guide me how to actually decrease the error in data(rmse score)? I just need the tips or how to model which could produce a good forecasting result.