PANDAS : Assigning a value for each row in certain column based on multiple if condition

Question

I'm really new to python codes and having trouble with applying some of the answers for similar questions for my own case. Please help

So I have a dataframe with Column A and B, with numerous rows

Both contains negative and positive numbers, and I'm trying to make a new Column C with following conditions

If "Value of row 1, Column A is less than 0" & "Value of row 1, Column B is less than 0", return -100 in "row 1, Column C"

Elif "Value of row 1, Column A is less than 0" & "Value of row 1, Column B is greater than 0", return 100 in "row 1, Column C"

Elif "Value of row 1, Column A is greater than 0" & "Value of row 1, Column B is less than 0", return 100 in "row 1, Column C"

Else : return (Column A.Value / Column B.Value) in Column C

Thanks a lot

Answer 1

I think you are looking for np.select:

condlist = [(df['A'] < 0) & (df['B'] < 0),
            (df['A'] < 0) & (df['B'] > 0),
            (df['A'] > 0) & (df['B'] < 0)]

choicelist = [-100, 100, 100]

default = df['A'] / df['B']

df['C'] = np.select(condlist, choicelist, default)

Output:

>>> df
          A          B           C
0 -0.002639  -1.374507 -100.000000
1 -0.696428   9.923431  100.000000
2  1.410547   3.804043    0.370802
3  1.504908   2.701486    0.557067
4  1.867486   1.889067    0.988576
5 -0.451066 -11.529716 -100.000000
6  5.713800  -7.678271  100.000000
7 -4.318760   5.082725  100.000000
8  5.169819  -4.122461  100.000000
9  0.094524  -1.916718  100.000000

Setup a MRE

import pandas as pd
import numpy as np

np.random.seed(2022)
df = pd.DataFrame(np.random.normal(0, 5, (10, 2)), columns=['A', 'B'])