Pandas version checks

• I have checked that the issue still exists on the latest versions of the docs on main here

Location of the documentation

https://pandas.pydata.org/docs/dev/reference/api/pandas.read_csv.html#pandas-read-csv

Documentation problem

Passing a date_format argument to read_csv is enough to trigger datetime parsing, i.e. parse_dates=True is not needed:

import io import pandas as pd csv = io.StringIO("foo,bar\n2023-01-01,0\n2023-01-02,1\n2023-01-03,2") df = pd.read_csv(csv, index_col="foo", date_format="%Y-%m-%d") print(df.index)

Output:

DatetimeIndex(['2023-01-01', '2023-01-02', '2023-01-03'], dtype='datetime64[ns]', name='foo', freq=None) 

This makes sense as a shortcut, but it would be nice to document this behavior, so that users know that it's intentional.

Suggested fix for documentation

The documentation for both the parse_dates and date_format kwargs to read_csv should mention that when parse_dates is not specified but date_format is, dates will be parsed.