maxframe.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 maxframe.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