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# pandas.Series.idxmax

Series.idxmax(axis=0, skipna=True, *args, **kwargs)

  Return the row label of the maximum value.

  If multiple values equal the maximum, the first row label with that value is returned.

  Parameters:
    axis{0 or ‘index’}

      Unused. Parameter needed for compatibility with DataFrame.

    skipnabool, default True

      Exclude NA/null values. If the entire Series is NA, the result will be NA.

    *args, **kwargs

      Additional arguments and keywords have no effect but might be accepted for compatibility with NumPy.

  Returns:
    Index

      Label of the maximum value.

  Raises:
    ValueError

      If the Series is empty.

  See also

  `numpy.argmax`

    Return indices of the maximum values along the given axis.

  `DataFrame.idxmax`

    Return index of first occurrence of maximum over requested axis.

  `Series.idxmin`

    Return index label of the first occurrence of minimum of values.

  Notes

  This method is the Series version of `ndarray.argmax`. This method returns the label of the maximum, while `ndarray.argmax` returns the position. To get the position, use `series.values.argmax()`.

  Examples

      >>> s = pd.Series(data=[1, None, 4, 3, 4],
      ...               index=['A', 'B', 'C', 'D', 'E'])
      >>> s
      A    1.0
      B    NaN
      C    4.0
      D    3.0
      E    4.0
      dtype: float64

      >>> s.idxmax()
      'C'

  If skipna is False and there is an NA value in the data, the function returns `nan`.

      >>> s.idxmax(skipna=False)
      nan