Filtering Pandas Dataframe using OR statement over a list of columns

Question

I want to filter a dataframe according to whether any of several columns in a list match a test.

E.g., it can work in this way:

ddf = pd.DataFrame(np.random.randint(0,100,size=(100, 4)), columns=list('ABCD'))
ddf[(ddf['A']==0)|(ddf['B']==0)|(ddf['C']==0)|(ddf['D']==0)]

...and one could build a loop if there are many more columns to process. But I wonder whether there's a more pythonic way to proceed, starting from the result of

ddf[list('ABCD')]==0

which gives 4 columns of booleans, over which I'd like to apply a or operation by row.

StupidWolf · Accepted Answer · 2020-10-24 21:31:34Z

2

If it is the same test like whether it is zero, then you use any() across the rows:

np.random.seed(999)
ddf = pd.DataFrame(np.random.randint(0,100,size=(100, 4)), columns=list('ABCD'))

ddf[(ddf[['A','B','C','D']]==0).any(axis=1)]

     A   B   C   D
71  52  13   0  50
93  51   0  60  71

answered Oct 24, 2020 at 21:31

StupidWolf

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