change specific column name pandas
df_new = df.rename(columns={'A': 'a'}) #change a from Achange specific column name pandas
df_new = df.rename(columns={'A': 'a'}) #change a from Arename df column
import pandas as pd
data = pd.read_csv(file)
data.rename(columns={'original':'new_name'}, inplace=True)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'})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 change column name in pandas
print(df.rename(columns={'A': 'a', 'C': 'c'}))
# a B c
# ONE 11 12 13
# TWO 21 22 23
# THREE 31 32 33name columns pandas
>gapminder.columns = ['country','year','population',
'continent','life_exp','gdp_per_cap']Copyright © 2021 Codeinu
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