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Exercise

Sorting rows

Finding interesting bits of data in a DataFrame is often easier if you change the order of the rows. You can sort the rows by passing a column name to .sort_values().

In cases where rows have the same value (this is common if you sort on a categorical variable), you may wish to break the ties by sorting on another column. You can sort on multiple columns in this way by passing a list of column names.

Sort on … Syntax
one column df.sort_values("breed")
multiple columns df.sort_values(["breed", "weight_kg"])

By combining .sort_values() with .head(), you can answer questions in the form, "What are the top cases where…?".

homelessness is available and pandas is loaded as pd.

Instructions 1/3
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  • 1
    • Sort homelessness by the number of homeless individuals, from smallest to largest, and save this as homelessness_ind.
    • Print the head of the sorted DataFrame.
  • 2
    • Sort homelessness by the number of homeless family_members in descending order, and save this as homelessness_fam.
    • Print the head of the sorted DataFrame.
  • 3
    • Sort homelessness first by region (ascending), and then by number of family members (descending). Save this as homelessness_reg_fam.
    • Print the head of the sorted DataFrame.
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