/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 vote244 views1 answer
Insertar valor python
Python
7 votes201 views1 answer
PIL discord
Python
1 vote208 views1 answer
Openpyxl delete column by name
Python
4 votes202 views1 answer
Pandas find inf values
Python
0 vote201 views1 answer
Get datatype of all columns pandas
Python
0 vote204 views1 answer
Pyplot common labels
Python
2 votes244 views2 answers
How to open a website with selenium python
Python
15 votes198 views6 answers
Flask install
Python
-1 vote194 views1 answer
Heads or tails python
Python
8 votes228 views3 answers
Django order by
Python