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.
If getting a value and âlabelâ does not exist in a DataFrame or Series.
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)
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