How to rename the columns in a Pandas DataFrame | Pandas rename column |Pandas tutorial for Beginner

Alter axes 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.

See the user guide for more.

Parameters
mapper dict-like or function
Dict-like or functions 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 int or str
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 return a new DataFrame. If True then value of copy is ignored.

levelint or level name, default None
In 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
DataFrame with the renamed axis labels.

Raises
KeyError
If any of the labels is not found in the selected axis and “errors=’raise’”.

The github link for this notebook is below 👇👇