过滤器 pandas df by boolean 系列

Question

I have a dataframe foo and a True/False series bar :

foo = pd.DataFrame(
    [['a', 1], ['b', 2], ['a', 3]],
    index=[0, 1, 2], columns=['col1', 'col2'])
bar = pd.Series({'a': True, 'b': False})

I want to filter foo on col1 based on the truthiness of bar . Here are some approaches that work:

foo[foo['col1'].isin(bar.where(bar == True).dropna().index)
foo[foo['col1'].isin([k for k, v in bar.to_dict().items() if v])

# desired result
    col1    col2
0   a       1
2   a       3

However, I think both approaches are a bit messy / not so intuitive to read, was wondering if I was missing any basic Pandas filtering concepts that allow for a simpler approach.

Answer 1

Use Series.map and index with the result:

foo[foo.col1.map(bar)]

   col1  col2
0    a     1
2    a     3