cudf.Series.reindex

Series.reindex(*args, **kwargs)

Conform Series to new index.

Parameters

indexIndex, Series-convertible, default None

New labels / index to conform to, should be specified using keywords.

method: Not Supported

copyboolean, default True

level: Not Supported

fill_valueValue to use for missing values.

Defaults to NA, but can be any “compatible” value.

limit: Not Supported

tolerance: Not Supported

Returns

Series with changed index.

Examples

>>> import cudf
>>> series = cudf.Series([10, 20, 30, 40], index=['a', 'b', 'c', 'd'])
>>> series
a    10
b    20
c    30
d    40
dtype: int64
>>> series.reindex(['a', 'b', 'y', 'z'])
a      10
b      20
y    <NA>
z    <NA>
dtype: int64

Pandas Compatibility Note

Series.reindex

Note: One difference from Pandas is that NA is used for rows that do not match, rather than NaN. One side effect of this is that the series retains an integer dtype in cuDF where it is cast to float in Pandas.