Pandas MultiIndex Tutorial and Best Practices

While Pandas is one of the most well known Python libraries for working with array-like data, many users limit themselves to just two dimensions of data. This talk will walk through Pandas' MultiIndex DataFrames, which extend traditional DataFrames by enabling effective storage and manipulation of arbitrarily high dimension data in a 2-dimensional tabular structure. ((If that sentence doesn't make sense yet, don't worry - it should by the end of the tutorial.)) While the displayed version of a multiindexed DataFrame doesn't appear to be much more than a prettily-organized regular DataFrame, it's actually a pretty powerful structure if the data warrants its use. This talk is beginner friendly, and will start from the assumption of having never used Pandas, though some Pandas experience will aid understanding.

Speaker: Zax Rosenberg
Additional LInks: at the bottom of the jupyter notebook in the above link

Founded in 2003, Chicago Python User Group is one of the world's most active programming language special interest groups with over 1,000 active members and many more prestigious alumni. Our main focus is the Python Programming Language.

Twitter: @ChicagoPython

Date: 2018-08-09
Location: Sully's House, Chicago

[MarcelJanKr]

Thanks Zax for this explanation in MultiIndexes. I had to extract data from a complex Excel sheet and the one thing that stood between me and being able to stack, unstack and stack the data again, was not having a MultiIndex with two levels of headers on my dataframe. Lots of frustration, but thanks to your video that now is behind me!

[mailupendra]

You are awesome Zax. Thank you. Great Job.