Drop rows with all zeros in pandas data frame

pandas, python

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

Problem

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. thanks!

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