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pythonpandasselect
Fringant
Fringant

Reputation: 555

Python pandas: Select columns where a specific row satisfies a condition

I have a dataframe dfall where there is a row labeled 'row1' with values 'foo' and 'bar'. I want to select only columns of dfall where 'row1' has the value 'foo'.

In other words:

dfall= pd.DataFrame([['bar','foo'],['bla','bli']], columns=['col1','col2'], index=['row1','row2'])

I want as result the column 'col2'containing: ['foo','bli']

I tried:

dfall[dfall.loc['row1'].isin(['foo'])]

I get the error 

IndexingError: Unalignable boolean Series key provided

Can anybody help me with the command? Thanks in advance!

Upvotes: 1

Views: 1562

Answers (2)

Fringant
Fringant

Reputation: 555

Using EdChum's answer, to make it row specific I did: df.ix[:,(df.loc['row1'] == 'foo')]

Upvotes: 0

EdChum
EdChum

Reputation: 394041

You can compare your df against the scalar value, and then use any with axis=0 and pass this boolean mask to ix:

In [324]:
df.ix[:,(df == 'foo').any(axis=0)]

Out[324]:
     col2
row1  foo
row2  bli

breaking the above down:

In [325]:
df == 'foo'

Out[325]:
       col1   col2
row1  False   True
row2  False  False

In [326]:
(df == 'foo').any(axis=0)

Out[326]:
col1    False
col2     True
dtype: bool

Upvotes: 1

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