Source: pandas
Version: 0.23.3+dfsg-2
Severity: important
Control: tags -1 fixed-upstream patch
np.array @ Series actually calculates Series @ np.array, which is an
error for nonsquare matrices and a *wrong answer* for square matrices.
Fixed upstream by
https://github.com/pandas-dev/pandas/pull/21578/commits/95d66f0e17c12a1ad661ad68c4fb49eadcf4b578
a= np.array([[ 0, -1, -2, -3, -4, -5, -6, -7, -8, -9],
[ 1, 0, -1, -2, -3, -4, -5, -6, -7, -8],
[ 2, 1, 0, -1, -2, -3, -4, -5, -6, -7],
[ 3, 2, 1, 0, -1, -2, -3, -4, -5, -6],
[ 4, 3, 2, 1, 0, -1, -2, -3, -4, -5],
[ 5, 4, 3, 2, 1, 0, -1, -2, -3, -4],
[ 6, 5, 4, 3, 2, 1, 0, -1, -2, -3],
[ 7, 6, 5, 4, 3, 2, 1, 0, -1, -2],
[ 8, 7, 6, 5, 4, 3, 2, 1, 0, -1],
[ 9, 8, 7, 6, 5, 4, 3, 2, 1, 0]])
b=pd.Series(np.arange(10))
a@b
array([ 285, 240, 195, 150, 105, 60, 15, -30, -75, -120])
pd.DataFrame(a)@b
0 -285
1 -240
2 -195
3 -150
4 -105
5 -60
6 -15
7 30
8 75
9 120
dtype: int64
