# dask.dataframe.DataFrame.abs

DataFrame.abs()

  Return a Series/DataFrame with absolute numeric value of each element.

  This docstring was copied from pandas.core.frame.DataFrame.abs.

  Some inconsistencies with the Dask version may exist.

  This function only applies to elements that are all numeric.

  Returns:
    abs

      Series/DataFrame containing the absolute value of each element.

  See also

  `numpy.absolute`

    Calculate the absolute value element-wise.

  Notes

  For `complex` inputs, `1.2 + 1j`, the absolute value is \(\sqrt{ a^2 + b^2 }\).

  Examples

  Absolute numeric values in a Series.

      >>> s = pd.Series([-1.10, 2, -3.33, 4])
      >>> s.abs()
      0    1.10
      1    2.00
      2    3.33
      3    4.00
      dtype: float64

  Absolute numeric values in a Series with complex numbers.

      >>> s = pd.Series([1.2 + 1j])
      >>> s.abs()
      0    1.56205
      dtype: float64

  Absolute numeric values in a Series with a Timedelta element.

      >>> s = pd.Series([pd.Timedelta('1 days')])
      >>> s.abs()
      0   1 days
      dtype: timedelta64[ns]

  Select rows with data closest to certain value using argsort (from StackOverflow).

      >>> df = pd.DataFrame({
      ...     'a': [4, 5, 6, 7],
      ...     'b': [10, 20, 30, 40],
      ...     'c': [100, 50, -30, -50]
      ... })
      >>> df
           a    b    c
      0    4   10  100
      1    5   20   50
      2    6   30  -30
      3    7   40  -50
      >>> df.loc[(df.c - 43).abs().argsort()]
           a    b    c
      1    5   20   50
      0    4   10  100
      2    6   30  -30
      3    7   40  -50