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[ARTICLE · art-167426] src=lernerpython.com ↗ pub= topic=developer-tools verified=true sentiment=· neutral

Pandas 3.1 filter: Selecting rows with a pd.col condition

Pandas 3.1 introduces a filter method that applies a row condition via pd.col, letting users replace .loc[pd.col('passenger_count') > 1, 'trip_distance'] with .filter(cond=pd.col('passenger_count') > 1)['trip_distance'], according to a November 8, 2026 post on the release. The post notes the new filter-based form is "much slower" than the equivalent .loc expression. The change gives Pandas users an alternative row-selection syntax but at a performance cost versus .loc.

by read1 min views6 publishedNov 8, 2026
Pandas 3.1 filter: Selecting rows with a pd.col condition
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Pandas 3.1 filter: Selecting rows with a pd.col condition

November 8, 2026

Python

Python

Starting with Python Pandas 3.1, use “filter” to apply a condition to rows. So:

(
  df
  .loc[ pd.col('passenger_count') > 1 , 'trip_distance']
  .mean()
)

can now be (the much slower):

(
  df
  .filter(cond=pd.col('passenger_count') > 1)
  ['trip_distance']
  .mean()
)

← Pandas 3.1 select method: Retrieving specific columns

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