/Python/Change pandas column value based on condition

Change pandas column value 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

Source: stackoverflow.com

Pandas update with condition

import pandas as pd
import numpy as np

df = pd.DataFrame({'value':np.arange(1000000)})

# Solution 1 - Fastest :
df['value'] = np.where(df['value'] > 20000, 0, df['value'])

# Solution 2:
df.loc[df['value'] > 20000, 'value'] = 0

# Solution 3:
df['value'] = df['value'].mask(df['value'] > 20000, 0)

# Solution 4 - Slowest, note that df.where applies where condition is wrong:
df['a'] = df.where(df.a <= 20000, 0)

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