Reputation: 8279
Considering the following DataFrames
In [136]:
df = pd.DataFrame({'A':[1,1,2,2],'B':[1,2,1,2],'C':np.arange(10,30,5)}).set_index(['A','B'])
df
Out[136]:
C
A B
1 1 10
2 15
2 1 20
2 25
In [130]:
vals = pd.DataFrame({'A':[1,2],'values':[True,False]}).set_index('A')
vals
Out[130]:
values
A
1 True
2 False
How can I select only the rows of df
with corresponding True
values in vals
?
If I reset_index
on both frames I can now merge/join them and slice however I want, but how can I do it using the (multi)indexes?
Upvotes: 4
Views: 2267
Reputation: 69256
boolean indexing all the way...
In [65]: df[pd.Series(df.index.get_level_values('A')).isin(vals[vals['values']].index)]
Out[65]:
C
A B
1 1 10
2 15
Note that you can use xs on a multiindex.
In [66]: df.xs(1)
Out[66]:
C
B
1 10
2 15
Upvotes: 7