rename column in pandas dataframe code example

Example 1: rename column pandas

>>> df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
>>> df.rename(columns={"A": "a", "B": "c"})
   a  c
0  1  4
1  2  5
2  3  6

Example 2: rename columns pandas

df.rename(columns={'oldName1': 'newName1',
                   'oldName2': 'newName2'},
          inplace=True, errors='raise')
# Make sure you set inplace to True if you want the change
# to be applied to the dataframe

Example 3: rename df column

import pandas as pd
data = pd.read_csv(file)
data.rename(columns={'original':'new_name'}, inplace=True)

Example 4: rename column name pandas dataframe

df.rename(columns={"old_col1": "new_col1", "old_col2": "new_col2"})

Example 5: rename column pandas

df_new = df.rename(columns={'A': 'a'}, index={'ONE': 'one'})
print(df_new)
#         a   B   C
# one    11  12  13
# TWO    21  22  23
# THREE  31  32  33

print(df)
#         A   B   C
# ONE    11  12  13
# TWO    21  22  23
# THREE  31  32  33

Example 6: how to give name to column in pandas

>gapminder.rename(columns={'pop':'population',
                          'lifeExp':'life_exp',
                          'gdpPercap':'gdp_per_cap'}, 
                 inplace=True)
 
>print(gapminder.columns)
 
Index([u'country', u'year', u'population', u'continent', u'life_exp',
       u'gdp_per_cap'],
      dtype='object')
 
>gapminder.head(3)
 
       country  year  population continent  life_exp  gdp_per_cap
0  Afghanistan  1952     8425333      Asia    28.801   779.445314
1  Afghanistan  1957     9240934      Asia    30.332   820.853030
2  Afghanistan  1962    10267083      Asia    31.997   853.100710