mars.dataframe.DataFrame.rename#

DataFrame.rename(mapper=None, index=None, columns=None, axis='index', 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.

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 with the renamed axis labels.

Return type

DataFrame

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:

>>> import mars.dataframe as md
>>> df = md.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
>>> df.rename(columns={"A": "a", "B": "c"}).execute()
   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"}).execute()
   A  B
x  1  4
y  2  5
z  3  6

Cast index labels to a different type:

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

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

Using axis-style parameters

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

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