# pandas.DataFrame.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`

and `freq`

are unsupported.

## Examples¶

```
import pandas as pd
from numba import njit
@njit
def dataframe_pct_change():
df = pd.DataFrame({"A": [14, 4, 5, 4, 1, 55],
"B": [5, 2, 54, 3, 2, 32],
"C": [20, 20, 7, 21, 8, 5],
"D": [14, 3, 6, 2, 6, 4]})
out_df = df.pct_change()
return out_df
print(dataframe_pct_change())
```

```
$ python ./dataframe/dataframe_pct_change.py
A B C D
0 NaN NaN NaN NaN
1 -0.714286 -0.600000 0.000000 -0.785714
2 0.250000 26.000000 -0.650000 1.000000
3 -0.200000 -0.944444 2.000000 -0.666667
4 -0.750000 -0.333333 -0.619048 2.000000
5 54.000000 15.000000 -0.375000 -0.333333
```

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.