# pandas.DataFrame.rename

`DataFrame.``rename`(mapper=None, index=None, columns=None, axis=None, copy=True, inplace=False, level=None, errors='ignore')

  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.

  level : int 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’”.

  See also

  `DataFrame.rename_axis`
    Set the name of the axis.

  Examples

  `DataFrame.rename` supports two calling conventions

  - `(index=index_mapper, columns=columns_mapper, ...)`
  - `(mapper, axis={'index', 'columns'}, ...)`

  We highly recommend using keyword arguments to clarify your intent.

  Rename columns using a mapping:

      >>> df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
      >>> df.rename(columns={"A": "a", "B": "c"})
         a  c
      0  1  4
      1  2  5
      2  3  6

  Rename index using a mapping:

      >>> df.rename(index={0: "x", 1: "y", 2: "z"})
         A  B
      x  1  4
      y  2  5
      z  3  6

  Cast index labels to a different type:

      >>> df.index
      RangeIndex(start=0, stop=3, step=1)
      >>> df.rename(index=str).index
      Index(['0', '1', '2'], dtype='object')

      >>> df.rename(columns={"A": "a", "B": "b", "C": "c"}, errors="raise")
      Traceback (most recent call last):
      KeyError: ['C'] not found in axis

  Using axis-style parameters

      >>> df.rename(str.lower, axis='columns')
         a  b
      0  1  4
      1  2  5
      2  3  6

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

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