Skip to main content
`Ctrl`+`K`

# pandas.Index.notna

final 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. NA values, such as None or `numpy.NaN`, get mapped to `False` values.

  Returns:
    numpy.ndarray[bool]

      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
      Index([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', nan], dtype='str')
      >>> idx.notna()
      array([ True,  True,  True, False])