DataFrame.at ⚬ Entries

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DataFrame.at ⚬｜Documentation｜1st｜20251021151535-00-⌔

pandas.DataFrame.at — pandas 2.3.3 documentation#pandas.DataFrame.at

property DataFrame.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

If getting a value and ‘label’ does not exist in a DataFrame or Series.

ValueError

If row/column label pair is not a tuple or if any label from the pair is not a scalar for DataFrame. If label is list-like (excluding NamedTuple) for Series.

See also:

DataFrame.at

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

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).

DataFrame.iloc

Access a group of rows and columns by integer position(s).

Series.at

Access a single value by label.

Series.iat

Access a single value by integer position.

Series.loc

Access a group of rows by label(s).

Series.iloc

Access a group of rows by integer position(s).

Notes:

See Fast scalar value getting and setting for more details.

Examples:

>>> df = pd.DataFrame(
...     [[0, 2, 3], [0, 4, 1], [10, 20, 30]],
...     index=[4, 5, 6],
...     columns=["A", "B", "C"],
... )
>>> df
   A   B   C
4   0   2   3
5   0   4   1
6  10  20  30

Get value at specified row/column pair

>>> df.at[4, "B"]
np.int64(2)

Set value at specified row/column pair

>>> df.at[4, "B"] = 10
>>> df.at[4, "B"]
np.int64(10)

Get value within a Series

>>> df.loc[5].at["B"]
np.int64(4)

Printed 2026-06-28.

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