How to sort a numpy array with key as isnan?

Question

I have a numpy array like

np.array([[1.0, np.nan, 5.0, 1, True, True, np.nan, True],
       [np.nan, 4.0, 7.0, 2, True, np.nan, False, True],
       [2.0, 5         


        

Answer 1

Since you have an object array anyway, do the sorting in Python, then make your array. You can write a key that does something like this:

from math import isnan

def key(x):
    if isnan(x):
        t = 3
        x = 0
    elif isinstance(x, bool):
        t = 2
    else:
        t = 1
    return t, x

This key returns a two-element tuple, where the first element gives the preliminary ordering by type. It considers all NaNs to be equal and greater than any other type.

Even if you start with data in a DataFrame, you can do something like:

values = [list(sorted(row, key=key)) for row in data.values]
values = np.array(values, dtype=np.object)

You can replace the list comprehension with np.apply_along_axis if that suits your needs better:

values = np.apply_along_axis(lambda row: np.array(list(sorted(row, key=key))),
                             axis=1, arr=data.values)