pyspark.pandas.Series.pct_change¶
-
Series.pct_change(periods: int = 1) → pyspark.pandas.series.Series¶ 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 move all data into single partition in single machine and could cause serious performance degradation. Avoid this method against very large dataset.
- 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