BUG: pd.col does not support & for combining conditions in .loc #63322
Description
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I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import pandas as pd import io data = '''datetime,cfs 2018-02-28,350 2018-03-15,420 2019-04-10,380 2019-06-01,450 ''' dd = pd.read_csv(io.StringIO(data), parse_dates=['datetime']).set_index('datetime') (dd .reset_index() .sort_values('datetime') .loc[(pd.col('datetime') > '2018-03-01') & (pd.col('datetime') <= '2019-05-31')] .assign(cfs=pd.col('cfs').clip(upper=400)) )Issue Description
When using pd.col inside .loc to filter rows based on multiple conditions, combining conditions with & does not work as expected.
Expected Behavior
It works like this lambda version:
import pandas as pd import io data = '''datetime,cfs 2018-02-28,350 2018-03-15,420 2019-04-10,380 2019-06-01,450 ''' dd = pd.read_csv(io.StringIO(data), parse_dates=['datetime']).set_index('datetime') (dd .reset_index() .sort_values('datetime') #.loc[(pd.col('datetime') > '2018-03-01') & (pd.col('datetime') <= '2019-05-31')] .loc[lambda df_: (df_['datetime'] > '2018-03-01') & (df_['datetime'] <= '2019-05-31')] .assign(cfs=pd.col('cfs').clip(upper=400)) )Installed Versions
Replace this line with the output of pd.show_versions()