Mahbubul Alam, PhD

Mahbubul Alam, PhD

Forest economist turned data scientist; trained in environmental-economic modeling

Time series forecasting resources in Python and R

1 minute read

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Beginner or an advanced learner, if you are interested in time series analysis and forecasting, there are only few materials and blogposts that should meet your 95% needs.

If you are in Python, statsmodels is a good place to start. statsmodels is a Python module for statistical analysis and has some great time series and forecasting examples. You should also read Machine Learning Mastery blog posts. Jason Brownlee is an absolute master of time series in python. A lot of theories and application you’ll find in his blog series explained in an accessible way.

Here is the “but”…..

Do you really need to go thought a steep learning curve if there is an easy solution? If you do not want that you have an one stop solution for all time series and forecasting needs. That’s in R. Just read/review Rob Hyndman’s wonderful, easy to follow book Forecasting Principles and Practice. This book covers everything you need to know and learn – from basic time series analysis to advanced forecasting techniques. One of the most amazing thing is that you can implement almost any forecasting exercise with only few lines of codes.

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