Set values of a column in pandas dataframe based on values in other columns

Question

I want to set the value of a column(Z) in a pandas dataframe based on the values in other columns (X,Y):

Here is a sample code for that:

for i, row in df.iterrows():
    #print(i, row['Z'])
    if row['X'] == 1 and row['Y'] == 0:
        row['Z'] = 1
    if row['X'] == 0 and row['Y'] == 1:
        row['Z'] = 0
    if row['X'] == 0 and row['Y'] == 0:
        row['Z'] = 2
    if row['X'] == 1 and row['Y'] == 1:
        row['Z'] = 3

what is the way to do so?

jezrael · Accepted Answer · 2019-07-18 07:19:32Z

1

Use numpy.select with & for bitwise AND:

m1 = df['X'] == 0
m2 = df['X'] == 1
m3 = df['Y'] == 0
m4 = df['Y'] == 1

df['Z'] = np.select([m2 & m3, m1 & m4, m1 & m3, m2 & m4], [1,0,2,3])

answered Jul 18, 2019 at 7:19

jezrael

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Comments

Ayoub ZAROU · Accepted Answer · 2019-07-18 07:30:38Z

0

if you just want to code the Z value, you could do about

df['Z'] = df['X'] + 2 * df['Y']

if that's not the case, you use pandas.Series.map afterwards :

df['Z'] = df['Z'].map({1:0, 2:1, 0:2, 3:3})

edited Jul 18, 2019 at 7:30

answered Jul 18, 2019 at 7:23

Ayoub ZAROU

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