replace column values pandas
df['column'] = df['column'].str.replace(',','-')
df
                                
                            replace column values pandas
df['column'] = df['column'].str.replace(',','-')
df
                                
                            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
                                
                            replacing 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 values from another dataframe
In [36]:
df['Group'] = df['Group'].map(df1.set_index('Group')['Hotel'])
df
Out[36]:
         Date  Group  Family  Bonus
0  2011-06-09  Jamel  Laavin    456
1  2011-07-09  Frank  Grendy    679
2  2011-09-10   Luxy  Fantol    431
3  2011-11-02  Frank  Gondow    569
                                
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