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 1003replacing values in pandas dataframe
df['coloum'] = df['coloum'].replace(['value_1','valu_2'],'new_value')how to replace values in column pandas
# this will replace "Boston Celtics" with "Omega Warrior"
df.replace(to_replace ="Boston Celtics",
value ="Omega Warrior")replace values of pandas column
df.loc[df['column'] == 'column_value', 'column'] = 'new_column_value'pandas replace data in specific columns with specific values
### replace one value ###
df["column"].replace("US","UK") # you can also use numerical values
### replace more than one value ###
df["column"].replace(["man","woman","child"],[1,2,3]) # you can also use numerical values
# man ==> 1
# woman ==> 2
# child ==> 3Copyright © 2021 Codeinu
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