pyspark.pandas.Series.pct_change#

Series.pct_change(periods=1)[source]#

Percentage change between the current and a prior element.

Note

the current implementation of this API uses Spark’s Window without specifying partition specification. This leads to moveing all data into a single partition in a single machine and could cause serious performance degradation. Avoid this method with very large datasets.

Parameters

periodsint, default 1: Periods to shift for forming percent change.

Returns

Series

Examples

>>> psser = ps.Series([90, 91, 85], index=[2, 4, 1])
>>> psser
2    90
4    91
1    85
dtype: int64

>>> psser.pct_change()
2         NaN
4    0.011111
1   -0.065934
dtype: float64

>>> psser.sort_index().pct_change()
1         NaN
2    0.058824
4    0.011111
dtype: float64

>>> psser.pct_change(periods=2)
2         NaN
4         NaN
1   -0.055556
dtype: float64