[FIXED] How to map many columns into one column

Issue

First data frame:

name        age   sex
smith row   26    male
sam smith   30    male
susan storm   25  female

Second data frame:

name        age   sex    nick_name
smith row   26    male   smity
sam smith   30    male   sammy
susan storm   25  female suanny

Output expected:

name         age   sex
smith row   26    male
sam smith   30    male
susan storm   25  female
smity             m
sammy             m
suanny            f

How can I dynamically map from other df to other df column?

Solution

You will have to modify df2 to get the result you want.

df2['name'] = df2['nick_name']
df2['sex'] = df2['sex'].str[0]
df2 = df2.drop(columns=['age', 'nick_name'])

df3 = pd.concat([df1, df2], ignore_index=True)

this is the end result

name         age    sex
smith row    26     male
sam smith    30     male
susan storm  25     female
smity        NaN    m
sammy        NaN    m
suanny       NaN    f

Answered By - Triky