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 dataframepython 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'})rename column name pandas dataframe
df.rename(columns={"old_col1": "new_col1", "old_col2": "new_col2"})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 33pd.series.rename
>>> s = pd.Series([1, 2, 3])
>>> s
0 1
1 2
2 3
dtype: int64
>>> s.rename("my_name") # scalar, changes Series.name
0 1
1 2
2 3
Name: my_name, dtype: int64
>>> s.rename(lambda x: x ** 2) # function, changes labels
0 1
1 2
4 3
dtype: int64
>>> s.rename({1: 3, 2: 5}) # mapping, changes labels
0 1
3 2
5 3
dtype: int64rename column pandas
>>> df.rename(index={0: "x", 1: "y", 2: "z"})
A B
x 1 4
y 2 5
z 3 6Copyright © 2021 Codeinu
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