Numpy: Drop rows with all nan or 0 values

This will remove all rows which are all zeros, or all nans:

mask = np.all(np.isnan(arr), axis=1) | np.all(arr == 0, axis=1)
arr = arr[~mask]

And this will remove all rows which are all either zeros or nans:

mask = np.all(np.isnan(arr) | arr == 0, axis=1)
arr = arr[~mask]

import numpy as np

a = np.array([
    [1, 0, 0],
    [0, np.nan, 0],
    [0, 0, 0],
    [np.nan, np.nan, np.nan],
    [2, 3, 4]
])

mask = np.all(np.isnan(a) | np.equal(a, 0), axis=1)
a[~mask]