In part 1 of “A guide to using pandas effectively and efficiently” article series, we’ve discussed 10 efficient ways of examing the structure of a Pandas DataFrame object. If you haven’t read that post, please read it before continuing to read this one. Here is the link:
Still, we don’t know anything about the data in the DataFrame. In this post, we’ll discuss numerical and graphical methods commonly used to describe and summarise a Pandas DataFrame.
First, we’ll begin with numerical methods
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