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 dataframerename 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 dataframepandas rename column
df.rename(columns={"old_col1": "new_col1", "old_col2": "new_col2"}, inplace=True)rename multiple pandas columns with list
for j in range(len(df.columns)):
old = df.columns[j]
new = new_columns[j]
df = df.rename(columns = {old:new})df change column names
df.rename(columns={"A": "a", "B": "b", "C": "c"},
errors="raise", inplace=True)change name of column pandas
#df.rename() will only return a new df with the new headers
#df = df.rename() will change the heders of the current dataframe
df = df.rename(columns={"old_col1": "new_col1", "old_col2": "new_col2"})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 31.997 853.100710Copyright © 2021 Codeinu
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