renaming columns in pandas dataframe code example

Example 1: python how to rename columns in pandas dataframe

# Basic syntax:
# Assign column names to a Pandas dataframe:
pandas_dataframe.columns = ['list', 'of', 'column', 'names']
# Note, the list of column names must equal the number of columns in the
# 	dataframe and order matters

# Rename specific column names of a Pandas dataframe:
pandas_dataframe.rename(columns={'column_name_to_change':'new_name'})
# Note, with this approach, you can specify just the names you want to
# 	change and the order doesn't matter

# For rows, use "index". E.g.:
pandas_dataframe.index = ['list', 'of', 'row', 'names']
pandas_dataframe.rename(index={'row_name_to_change':'new_name'})

Example 2: pandas dataframe column rename

>>> 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 3: pandas rename column

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

Example 4: 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