One of the most powerful features in pandas is multi-level indexing (or "hierarchical indexing"), which allows you to add extra dimensions to your Series or DataFrame objects. But when should you use a MultiIndex, and how do you create, slice, and merge MultiIndexed objects?
In this video, I'll demonstrate:
How to create a Series with a MultiIndex, and how to convert it to a DataFrame
How to select from a Series with a MultiIndex
How to create a DataFrame with a MultiIndex
How to select from a DataFrame with a MultiIndex
How to merge two DataFrames with MultiIndexes
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=== RELATED RESOURCES ===
Download the lesson notebook: http://nbviewer.jupyter.org/github/ju...
Using the pandas index (Part 1): • What do I need to know about the pand...
Using the pandas index (Part 2): • What do I need to know about the pand...
Analyzing groups with groupby: • When should I use a "groupby" in pandas?
Selection and slicing with loc: • How do I select multiple rows and col...
My full pandas video series: • Data analysis in Python with pandas
DataCamp course on MultiIndex: https://www.datacamp.com/courses/mani...
DataCamp course on merging: https://www.datacamp.com/courses/merg...
Tidy data: http://r4ds.had.co.nz/tidy-data.html
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