PYTHON

find and replace string dataframe

df['range'] = df['range'].str.replace(',','-')

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

replace column values pandas

df['column'] = df['column'].str.replace(',','-')
df

replacing values in pandas dataframe

df['coloum'] = df['coloum'].replace(['value_1','valu_2'],'new_value')

replace values of pandas column

df.loc[df['column'] == 'column_value', 'column'] = 'new_column_value'

replace value pandas df

# this will replace "Boston Celtics" with "Omega Warrior"
df.replace(to_replace ="Boston Celtics",
                 value ="Omega Warrior")

replace all values in column pandas

df.loc[df['column_name'] == value_you_want_replaced, 'column_name'] = your_value

how to change values in dataframe python

energy['Country'] = energy['Country'].replace(['Afghanistan','Albania'],['Sa','lol'])

pandas replace values

df.replace([0, 1, 2, 3], [4, 3, 2, 1])

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

change value in dataframe

# change value in column_where_to_change and in the row where column_name == column_value
df.loc[df['<column_name>']=='column_value', '<column_where_to_change>'] = '<new_value>'