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# pandas.Series.at

property 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

      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)