How To Rename Pandas DataFrame Columns?

(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 and axis to specify the axis to target with mapper, or index and columns.
index: dict-like or function –
- Alternative to specifying axis (mapper, axis=0 is equivalent to index=mapper).
columns: dict-like or function –
- Alternative to specifying axis (mapper, axis=1 is equivalent to columns=mapper).
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’.
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’”.

df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
df

df.rename(columns={"A": "a", "B": "c"})

df.rename(index={0: "x", 1: "y", 2: "z"})

df.rename(columns={"A": "aa", "B": "bb"},inplace=True)
df