maxframe.dataframe.Series.transform#

Series.transform(func, convert_dtype=True, axis=0, *args, skip_infer=False, dtype=None, **kwargs)#

Call func on self producing a Series with transformed values.

Produced Series will have same axis length as self.

Parameters:

  • func (function, str, list or dict)

  • function (-)

  • either (must)

  • Series.apply. (work when passed a Series or when passed to)

  • are (Accepted combinations)

  • function

  • name (- string function)

  • names (- list of functions and/or function)

  • 'sqrt'] (e.g. [np.exp.)

  • functions (- dict of axis labels ->)

  • such. (function names or list of)

  • axis ({0 or 'index'}) – Parameter needed for compatibility with DataFrame.

  • dtype (numpy.dtype, default None) – Specify dtypes of returned DataFrames. See Notes for more details.

  • skip_infer (bool, default False) – Whether infer dtypes when dtypes or output_type is not specified.

  • *args – Positional arguments to pass to func.

  • **kwargs – Keyword arguments to pass to func.

Returns:

  • Series

  • A Series that must have the same length as self.

:raises ValueError : If the returned Series has a different length than self.:

See also

Series.agg

Only perform aggregating type operations.

Series.apply

Invoke function on a Series.

Notes

When deciding output dtypes and shape of the return value, MaxFrame will try applying func onto a mock Series, and the transform call may fail. When this happens, you need to specify dtype of output Series.

Examples

>>> import maxframe.tensor as mt
>>> import maxframe.dataframe as md
>>> df = md.DataFrame({'A': range(3), 'B': range(1, 4)})
>>> df.execute()
A  B
0  0  1
1  1  2
2  2  3
>>> df.transform(lambda x: x + 1).execute()
A  B
0  1  2
1  2  3
2  3  4
On this page

This Page