pyspark.pandas.DataFrame.pct_change¶
-
DataFrame.pct_change(periods: int = 1) → pyspark.pandas.frame.DataFrame¶ 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
- DataFrame
Examples
Percentage change in French franc, Deutsche Mark, and Italian lira from 1980-01-01 to 1980-03-01.
>>> df = ps.DataFrame({ ... 'FR': [4.0405, 4.0963, 4.3149], ... 'GR': [1.7246, 1.7482, 1.8519], ... 'IT': [804.74, 810.01, 860.13]}, ... index=['1980-01-01', '1980-02-01', '1980-03-01']) >>> df FR GR IT 1980-01-01 4.0405 1.7246 804.74 1980-02-01 4.0963 1.7482 810.01 1980-03-01 4.3149 1.8519 860.13
>>> df.pct_change() FR GR IT 1980-01-01 NaN NaN NaN 1980-02-01 0.013810 0.013684 0.006549 1980-03-01 0.053365 0.059318 0.061876
You can set periods to shift for forming percent change
>>> df.pct_change(2) FR GR IT 1980-01-01 NaN NaN NaN 1980-02-01 NaN NaN NaN 1980-03-01 0.067912 0.073814 0.06883