Sanny Khan sannykhan3777
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sannykhan3777
/ Filter homelessness for cases where the USA census state is in the list of Mojave states, canu, assigning to mojave_homelessness. View the printed result.
Created
July 12, 2020 14:05
data-manipulation-with-pandas/transforming-data/exercise
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| # The Mojave Desert states | |
| canu = ["California", "Arizona", "Nevada", "Utah"] | |
| # Filter for rows in the Mojave Desert states | |
| mojave_homelessness =homelessness[homelessness["state"].isin(canu)] | |
| # See the result | |
| print(mojave_homelessness) |
sannykhan3777
/ Subsetting data based on a categorical variable often involves using the "or" operator (|) to select rows from multiple categories. This can get tedious when you want all states in one of three different regions, for example. Instead, use the .isin()
Created
July 12, 2020 13:41
Subsetting data based on a categorical variable often involves using the "or" operator (|) to select rows from multiple categories. This can get tedious when you want all states in one of three different regions, for example. Instead, use the .isin() method, which will allow you to tackle this problem by writing one condition instead of three se…
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| # Subset for rows in South Atlantic or Mid-Atlantic regions | |
| south_mid_atlantic = homelessness [(homelessness["region"]=="South Atlantic") | (homelessness["region"]=="Mid-Atlantic")] | |
| # See the result | |
| print(south_mid_atlantic) |