pyspark.pandas.DataFrame.rename#

DataFrame.rename(mapper=None, index=None, columns=None, axis='index', inplace=False, level=None, errors='ignore')[source]#

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:

mapperdict-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.
indexdict-like or function: Alternative to specifying axis (“mapper, axis=0” is equivalent to “index=mapper”).
columnsdict-like or function: Alternative to specifying axis (“mapper, axis=1” is equivalent to “columns=mapper”).
axisint or str, default ‘index’: Axis to target with mapper. Can be either the axis name (‘index’, ‘columns’) or number (0, 1).
inplacebool, default False: Whether to return a new DataFrame.
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 with the renamed axis labels.

Raises:

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

Examples

>>> psdf1 = ps.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
>>> psdf1.rename(columns={"A": "a", "B": "c"})
   a  c
0  1  4
1  2  5
2  3  6

>>> psdf1.rename(index={1: 10, 2: 20})
    A  B
0   1  4
10  2  5
20  3  6

>>> psdf1.rename(columns={"A": "a", "C": "c"}, errors="raise")
Traceback (most recent call last):
    ...
KeyError: 'Index include value which is not in the `mapper`'

>>> def str_lower(s) -> str:
...     return str.lower(s)
>>> psdf1.rename(str_lower, axis='columns')
   a  b
0  1  4
1  2  5
2  3  6

>>> def mul10(x) -> int:
...     return x * 10
>>> psdf1.rename(mul10, axis='index')
    A  B
0   1  4
10  2  5
20  3  6

>>> idx = pd.MultiIndex.from_tuples([('X', 'A'), ('X', 'B'), ('Y', 'C'), ('Y', 'D')])
>>> psdf2 = ps.DataFrame([[1, 2, 3, 4], [5, 6, 7, 8]], columns=idx)
>>> psdf2.rename(columns=str_lower, level=0)
   x     y
   A  B  C  D
0  1  2  3  4
1  5  6  7  8

>>> psdf3 = ps.DataFrame([[1, 2], [3, 4], [5, 6], [7, 8]], index=idx, columns=list('ab'))
>>> psdf3.rename(index=str_lower)
     a  b
x a  1  2
  b  3  4
y c  5  6
  d  7  8