# pandas.Series.pow¶

Return Exponential power of series and other, element-wise (binary operator pow).

Equivalent to `series \*\* other`

, but with support to substitute a fill_value for
missing data in one of the inputs.

- param other
Series or scalar value

- param fill_value
- None or float value, default None (NaN)
Fill existing missing (NaN) values, and any new element needed for successful Series alignment, with this value before computation. If data in both corresponding Series locations is missing the result will be missing.

- param level
- int or name
Broadcast across a level, matching Index values on the passed MultiIndex level.

- return
Series The result of the operation.

## Limitations¶

Parameter

`axis`

is supported only with default value`0`

.Parameters

`level`

and`fill_value`

are supported only with default value`None`

.

## Examples¶

```
import pandas as pd
from numba import njit
@njit
def series_pow():
s1 = pd.Series([5, 4, 3, 2, 1])
s2 = pd.Series([0, 2, 3, 6, 8])
return s1.pow(s2) # Expect series of 1, 16, 27, 64, 1
print(series_pow())
```

```
$ python ./series/series_pow.py
0 1
1 16
2 27
3 64
4 1
dtype: int64
```

Note

Parameter axis is currently unsupported by Intel Scalable Dataframe Compiler

See also