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pandas.DataFrame.rmul

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

Multiplication of dataframe and other, element-wise (binary operator rmul).

Equivalent to other * dataframe, 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

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

level : int or name

Broadcast across a level, matching Index values on the passed MultiIndex level

Returns:

result : DataFrame

See also

DataFrame.mul

Notes

Mismatched indices will be unioned together

Examples

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