Subsetting rows by categorical variables
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 separate ones.
colors = ["brown", "black", "tan"]
condition = dogs["color"].isin(colors)
dogs[condition]
homelessness
is available and pandas
is loaded as pd
.
This is a part of the course
“Data Manipulation with pandas”
Exercise instructions
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.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# The Mojave Desert states
canu = ["California", "Arizona", "Nevada", "Utah"]
# Filter for rows in the Mojave Desert states
mojave_homelessness = homelessness[____]
# See the result
print(mojave_homelessness)