pandas.DataFrame.subtract

DataFrame.subtract(other, axis='columns', level=None, fill_value=None) [source]

Subtraction of dataframe and other, element-wise (binary operator sub).

Equivalent to dataframe - other, but with support to substitute a fill_value for missing data in one of the inputs.

Parameters:

other : Series, DataFrame, or constant axis : {0, 1, ‘index’, ‘columns’} For Series input, axis to match Series index on level : int or name Broadcast across a level, matching Index values on the passed MultiIndex level fill_value : None or float value, default None Fill existing missing (NaN) values, and any new element needed for successful DataFrame alignment, with this value before computation. If data in both corresponding DataFrame locations is missing the result will be missing

Returns:

result : DataFrame

See also

DataFrame.rsub

Notes

Mismatched indices will be unioned together

Examples

>>> a = pd.DataFrame([2, 1, 1, np.nan], index=['a', 'b', 'c', 'd'],
...                  columns=['one'])
>>> a
   one
a  2.0
b  1.0
c  1.0
d  NaN
>>> b = pd.DataFrame(dict(one=[1, np.nan, 1, np.nan],
...                       two=[3, 2, np.nan, 2]),
...                  index=['a', 'b', 'd', 'e'])
>>> b
   one  two
a  1.0  3.0
b  NaN  2.0
d  1.0  NaN
e  NaN  2.0
>>> a.sub(b, fill_value=0)
   one  two
a  1.0  -3.0
b  1.0  -2.0
c  1.0  NaN
d  -1.0  NaN
e  NaN  -2.0