renaming headers pandasd
df = df.rename(columns={"old_col1": "new_col1", "old_col2": "new_col2"})renaming headers pandasd
df = df.rename(columns={"old_col1": "new_col1", "old_col2": "new_col2"})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'})df change column names
df.rename(columns={"A": "a", "B": "b", "C": "c"},
errors="raise", inplace=True)how to change a header in pandas
# Can just use df.columns to rename
>>> df = pd.DataFrame({'$a':[1,2], '$b': [10,20]})
>>> df.columns = ['a', 'b']
>>> df
a b
0 1 10
1 2 20how 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 31.997 853.100710Copyright © 2021 Codeinu
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