test_1 = taxi[:4, :4]
test_bool = [True, True, False, False]
test_bool_results = test_1[:, test_bool]
test_bool_rows = test_1[test_bool, :]
If the Boolean Indexing allows you to pull the True values automatically; Is there a simple way to pull the False values also?
Invert the boolean indexer with ~ to get False values. If you want both False and True at the same time, that is basically not indexing at all.
How does it look when you use ~?
training_set = df[training_data_mask]
testing_set = df[~training_data_mask]
It does not seem to work.
I saw it somewhere online as:
import numpy as np
a = np.array([[1,2,3], [4,5,6], [7,8,9]])
b = [True,False,True]
c = (~a[b])
but then I tried that… hence the edit
I got this…
[[ -2 -3 -4]
[ -8 -9 -10]]