Course Description

    This video introduces the basic concepts of reading and indexing your data for time series using Python's pandas package. The processes of checking the requirements and transforming the data are explained with the help of examples, with emphasis on the usefulness of indexing data for time series. This video also highlights the importance of Python's pandas package in the world of data science. This series is curated for intermediate and advanced users.

    What You'll Learn

      >  Introduction to time series and Python's pandas package

      >  Modeling and plotting the data to test for requirements and assumptions

      >  Transforming the data to make it more stationary



     

    Code, R & Python Script Repository can be accessed here.

    Packages used in this course: pandasmatplotlib, statsmodelsstatistics.




     

    Rebecca Merrett - Rebecca holds a bachelor’s degree of information and media from the University of Technology Sydney and a post graduate diploma in mathematics and statistics from the University of Southern Queensland. She has a background in technical writing for games dev and has written for tech publications.