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# pandas.Series.empty

property Series.empty

  Indicator whether Series/DataFrame is empty.

  True if Series/DataFrame is entirely empty (no items), meaning any of the axes are of length 0.

  Returns:
    bool

      If Series/DataFrame is empty, return True, if not return False.

  See also

  `Series.dropna`

    Return series without null values.

  `DataFrame.dropna`

    Return DataFrame with labels on given axis omitted where (all or any) data are missing.

  Notes

  If Series/DataFrame contains only NaNs, it is still not considered empty. See the example below.

  Examples

  An example of an actual empty DataFrame. Notice the index is empty:

      >>> df_empty = pd.DataFrame({'A' : []})
      >>> df_empty
      Empty DataFrame
      Columns: [A]
      Index: []
      >>> df_empty.empty
      True

  If we only have NaNs in our DataFrame, it is not considered empty! We will need to drop the NaNs to make the DataFrame empty:

      >>> df = pd.DataFrame({'A' : [np.nan]})
      >>> df
          A
      0 NaN
      >>> df.empty
      False
      >>> df.dropna().empty
      True

      >>> ser_empty = pd.Series({'A' : []})
      >>> ser_empty
      A    []
      dtype: object
      >>> ser_empty.empty
      False
      >>> ser_empty = pd.Series()
      >>> ser_empty.empty
      True