Answers for "pandas.rename"

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 dataframe

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'})

pandas rename column

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

pandas rename column

df.rename({'current':'updated'},axis = 1, inplace = True)

pd.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: int64

rename column pandas

>>> df.rename({1: 2, 2: 4}, axis='index')
   A  B
0  1  4
2  2  5
4  3  6