Python Pandas - Logical indexing dataframe with multiple indexes based on single index -


i'm still pretty new pandas i've searched around quite bit , can't quite find i'm looking for.

so here problem:

i have 2 dataframe - 1 mutliple indexes , 1 index

df1=                 value1  value2 ind1 ind2      1          1.1     7.1 b      2          2.0     8.0 c      3          3.0     9.0      4          4.0    10.0 b      5          5.0    11.0 c      6          6.0    12.0   df2=             value1  value2 ind1           8.0     7.0 b           9.0     8.0 c           3.0     9.0 d           11.0   10.0 e           12.0    11.0 f           1.0    12.0

i index data df1 based on df2 value1 > value2.

df2['value1'] > df2['value2']

i know can data df2 with

df2.loc[df2['value1'] > df2['value2']]

but how data df1? tried:

df1.loc[df2['value1'] > df2['value2']]

but fails with

*** indexingerror: unalignable boolean series key provided

any suggestions appreciated, thank you!

get indices df2 , select df1 on indices:

indices = df2.loc[df2['value1'] > df2['value2']] >>>indices index([u'b', u'd', u'e'], dtype='object') >>>df1.ix[indices]  ind1 ind2   val1    val2 b    2      2.0     8.0 b    5      5.0     11.0

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