pandas replace value based on another column code example

Example 1: pandas replace values in column based on condition

In [41]:
df.loc[df['First Season'] > 1990, 'First Season'] = 1
df

Out[41]:
                 Team  First Season  Total Games
0      Dallas Cowboys          1960          894
1       Chicago Bears          1920         1357
2   Green Bay Packers          1921         1339
3      Miami Dolphins          1966          792
4    Baltimore Ravens             1          326
5  San Franciso 49ers          1950         1003

Example 2: replace column values pandas

df['column'] = df['column'].str.replace(',','-')
df

Example 3: change column value based on another column pandas

# Changes the 'is_electric' column based on value in the 'type' column
# If the 'type' column == 'electric' then the 'is_electric' becomes 'YES'
df['is_electric']= df['type'].apply(lambda x: 'YES' if (x == 'electric') else 'NO')

Example 4: replace value column by another if missing pandas

import numpy as np

df['column'] = np.where(df['column'].isnull(), 'value_if_true', 'value_if_false')