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