pythonpandasdataframe

Drop rows with all zeros in pandas data frame

I can use pandas dropna() functionality to remove rows with some or all columns set as NA's. Is there an equivalent function for dropping rows with all columns having value 0?

P   kt  b   tt  mky depth
1   0   0   0   0   0
2   0   0   0   0   0
3   0   0   0   0   0
4   0   0   0   0   0
5   1.1 3   4.5 2.3 9.0

In this example, we would like to drop the first 4 rows from the data frame.

Solution

  • It turns out this can be nicely expressed in a vectorized fashion:

    > df = pd.DataFrame({'a':[0,0,1,1], 'b':[0,1,0,1]})
> df = df[(df.T != 0).any()]
> df
   a  b
1  0  1
2  1  0
3  1  1