How To Rename Pandas DataFrame Columns?
Table Of Contents:
- Syntax ‘rename( )’ Method In Pandas.
- Examples ‘rename( )’ Method.
(1) Syntax:
DataFrame.rename(mapper=None, *, index=None, columns=None, axis=None, copy=None, inplace=False, level=None, errors='ignore')
Description:
Rename the column or Row Labels.
Function / dict values must be unique (1-to-1). Labels not contained in a dict / Series will be left as-is. Extra labels listed don’t throw an error.
Parameters:
- mapper: dict-like or function –
- Dict-like or function transformations to apply to that axis’ values. Use either
mapper
andaxis
to specify the axis to target withmapper
, orindex
andcolumns
.
- Dict-like or function transformations to apply to that axis’ values. Use either
- index: dict-like or function –
- Alternative to specifying axis (
mapper, axis=0
is equivalent toindex=mapper
).
- Alternative to specifying axis (
- columns: dict-like or function –
- Alternative to specifying axis (
mapper, axis=1
is equivalent tocolumns=mapper
).
- Alternative to specifying axis (
- axis: {0 or ‘index’, 1 or ‘columns’}, default 0 –
- Axis to target with
mapper
. Can be either the axis name (‘index’, ‘columns’) or number (0, 1). The default is ‘index’.
- Axis to target with
- copy: bool, default True –
- Also copy underlying data.
- inplace – bool, default False –
- Whether to modify the DataFrame rather than create a new one. If True then value of copy is ignored.
- level: int or level name, default None –
- In the case of a MultiIndex, only rename labels in the specified level.
- errors: {‘ignore’, ‘raise’}, default ‘ignore’ –
- If ‘raise’, raise a KeyError when a dict-like mapper, index, or columns contains labels that are not present in the Index being transformed. If ‘ignore’, existing keys will be renamed and extra keys will be ignored.
Returns:
- DataFrame or None – DataFrame with the renamed axis labels or None if
inplace=True
.
Raises:
- KeyError – If any of the labels is not found in the selected axis and “errors=’raise’”.
(2) Examples Of rename() Method:
Example-1
df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
df
Output:
# Rename columns using a mapping:
df.rename(columns={"A": "a", "B": "c"})
Output:
# Rename index using a mapping:
df.rename(index={0: "x", 1: "y", 2: "z"})
Output:
# Modifying The Original DataFrame.
df.rename(columns={"A": "aa", "B": "bb"},inplace=True)
df