Read and Transform Your Data


r_subheading-Course Description-r_end 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.r_break 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. r_break r_break r_subheading-What You'll Learn-r_end • Introduction to time series and Python's pandas package. r_break • Modeling and plotting the data to test for requirements and assumptions. r_break • Transforming the data to make it more stationary.

Code, R & Python Script Repository can be accessed r_link-here.- https://code.datasciencedojo.com/rebeccam/tutorials/tree/master/Time%20Series-r_end r_break r_break Packages used in this course: r_link-pandas- https://pandas.pydata.org/-r_end, r_link-matplotlib- https://matplotlib.org/-r_end, r_link-statsmodels- https://www.statsmodels.org/stable/index.html-r_end, r_link-statistics.- https://docs.python.org/3/library/statistics.html-r_end

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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.