/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)

Similar codes

0 vote344 views1 answer
Zipfian distribution python
Python
0 vote315 views1 answer
Cptac dataset
Python
0 vote273 views1 answer
Convert pandas.core.indexes.numeric.int64index to list
Python
0 vote334 views1 answer
Python add hyphen to string
Python
0 vote329 views3 answers
Translate python to c
Python
0 vote334 views1 answer
String pattern matching pandas
Python
5 votes292 views2 answers
Array of 1 to 100 python
Python
4 votes364 views2 answers
Plt dashed line
Python
0 vote344 views1 answer
How to capitalize every item in a list python
Python
2 votes406 views1 answer
How to open file dialog in pytohn
Python