flex_wrapper(self, other, level=None, fill_value=None, axis=0)
Equivalent to series / other
, but with support to substitute a fill_value for missing data in either one of the inputs.
Fill existing missing (NaN) values, and any new element needed for successful Series alignment, with this value before computation. If data in both corresponding Series locations is missing the result of filling (at that location) will be missing.
Broadcast across a level, matching Index values on the passed MultiIndex level.
The result of the operation.
Return Floating division of series and other, element-wise (binary operator :None:None:`truediv`).
Series.rtruediv
Reverse of the Floating division operator, see :None:None:`Python documentation
<https://docs.python.org/3/reference/datamodel.html#emulating-numeric-types>` for more details.
>>> a = pd.Series([1, 1, 1, np.nan], index=['a', 'b', 'c', 'd'])This example is valid syntax, but we were not able to check execution
... a a 1.0 b 1.0 c 1.0 d NaN dtype: float64
>>> b = pd.Series([1, np.nan, 1, np.nan], index=['a', 'b', 'd', 'e'])This example is valid syntax, but we were not able to check execution
... b a 1.0 b NaN d 1.0 e NaN dtype: float64
>>> a.divide(b, fill_value=0) a 1.0 b inf c inf d 0.0 e NaN dtype: float64See :
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