# pandas.Series.at¶

Access a single value for a row/column label pair.

Similar to `loc`

, in that both provide label-based lookups. Use
`at`

if you only need to get or set a single value in a DataFrame
or Series.

- raises
- KeyError
When label does not exist in DataFrame

## Limitations¶

- 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¶

```
import numpy as np
import pandas as pd
from numba import njit
@njit
def series_at_value():
series = pd.Series([5, 4, 3, 2, 1], index=[0, 2, 4, 6, 8])
return series.at[4] # Expect array: [3]
print(series_at_value())
```

```
$ python ./series/series_at/series_at_single_result.py
[3]
```

```
import numpy as np
import pandas as pd
from numba import njit
@njit
def series_at_many_idx():
series = pd.Series([5, 4, 3, 2, 1], index=[0, 2, 0, 6, 0])
return series.at[0] # Expect array: [5 3 1]
print(series_at_many_idx())
```

```
$ python ./series/series_at/series_at_multiple_result.py
[5 3 1]
```

See also

- DataFrame.iat
Access a single value for a row/column pair by integer position.

- DataFrame.loc
Access a group of rows and columns by label(s).

- Series.at
Access a single value using a label.