# pandas.Index.notna

`Index.``notna`()

  Detect existing (non-missing) values.

  Return a boolean same-sized object indicating if the values are not NA. Non-missing values get mapped to `True`. Characters such as empty strings `''` or `numpy.inf` are not considered NA values (unless you set `pandas.options.mode.use_inf_as_na = True`). NA values, such as None or `numpy.NaN`, get mapped to `False` values.

  New in version 0.20.0.

  Returns:

  numpy.ndarray

  > Boolean array to indicate which entries are not NA.

  See also

  `Index.notnull`
    Alias of notna.
  `Index.isna`
    Inverse of notna.
  `notna`
    Top-level notna.

  Examples

  Show which entries in an Index are not NA. The result is an array.

      >>> idx = pd.Index([5.2, 6.0, np.NaN])
      >>> idx
      Float64Index([5.2, 6.0, nan], dtype='float64')
      >>> idx.notna()
      array([ True,  True, False])

  Empty strings are not considered NA values. None is considered a NA value.

      >>> idx = pd.Index(['black', '', 'red', None])
      >>> idx
      Index(['black', '', 'red', None], dtype='object')
      >>> idx.notna()
      array([ True,  True,  True, False])

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