pandas.Series.pct_change

Percentage change between the current and a prior element.

Computes the percentage change from the immediately previous row by default. This is useful in comparing the percentage of change in a time series of elements.

param periods

int, default 1

Periods to shift for forming percent change.

param fill_method

str, default ‘pad’

How to handle NAs before computing percent changes.

param limit

int, default None

The number of consecutive NAs to fill before stopping.

param freq

DateOffset, timedelta, or offset alias string, optional

Increment to use from time series API (e.g. ‘M’ or BDay()). **kwargs Additional keyword arguments are passed into DataFrame.shift or Series.shift.

return

chg : Series or DataFrame The same type as the calling object.

Limitations

• Parameters limit, freq are currently unsupported by Intel Scalable Dataframe Compiler

• This function may reveal slower performance than Pandas* on user system. Users should exercise a tradeoff

  between staying in JIT-region with that function or going back to interpreter mode.

Examples

Percentage change between the current and a prior element.

import numpy as np
import pandas as pd
from numba import njit


@njit
def series_pct_change():
    s = pd.Series([5., 0, 3.3, np.nan, 9.2])

    return s.pct_change(periods=2, fill_method=None, limit=None, freq=None)


print(series_pct_change())

$ python ./series/series_pct_change.py
0         NaN
1         NaN
2   -0.340000
3         NaN
4    1.787879
dtype: float64

See also

Series.diff

Compute the difference of two elements in a Series.

DataFrame.diff

Compute the difference of two elements in a DataFrame.

Series.shift

Shift the index by some number of periods.

DataFrame.shift

Shift the index by some number of periods.