Preserve sign when squaring values in dataframe

Question

I have tried this:

>>> (-10) ** 2
100
>>> -10 ** 2
-100

In short, I was trying to get the output of the negative values squaring as negative.
So I tried the above simple expressions.
Then I tried the same formula on Pandas DataFrame, but I received ll the positive values.

>>> listi = [-10,-2,2,3,4,5,-100,-3,4]
>>> import pandas as pd
>>> df = pd.DataFrame(listi)
>>> df
     0
0  -10
1   -2
2    2
3    3
4    4
5    5
6 -100
7   -3
8    4
>>> df**2
       0
0    100
1      4
2      4
3      9
4     16
5     25
6  10000
7      9
8     16

I want to know why this happened? And how I can keep the squaring of the negative values as negative using pandas?

Answer 1

You can multiple values by numpy.sign for -1 for negative values:

print (df**2 * np.sign(df))
       0
0   -100
1     -4
2      4
3      9
4     16
5     25
6 -10000
7     -9
8     16