cudf.DataFrame.rtruediv#
- DataFrame.rtruediv(other, axis='columns', level=None, fill_value=None)[source]#
Get Floating division of DataFrame or Series and other, element-wise (binary operator rtruediv).
Equivalent to
frame + other, but with support to substitute afill_valuefor missing data in one of the inputs.- Parameters:
- otherscalar, sequence, Series, or DataFrame
Any single or multiple element data structure, or list-like object.
- axisint or string
Only
0is supported for series,1orcolumnssupported for dataframe- levelint or name
Broadcast across a level, matching Index values on the passed MultiIndex level. Not yet supported.
- fill_valuefloat or None, 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:
- DataFrame or Series
Result of the arithmetic operation.
Examples
DataFrame
>>> df = cudf.DataFrame( ... {'angles': [0, 3, 4], 'degrees': [360, 180, 360]}, ... index=['circle', 'triangle', 'rectangle'] ... )
>>> df.rtruediv(1) angles degrees circle inf 0.002778 triangle 0.333333 0.005556 rectangle 0.250000 0.002778
Series
>>> a = cudf.Series([1, 1, 1, None], index=['a', 'b', 'c', 'd']) >>> b = cudf.Series([1, None, 1, None], index=['a', 'b', 'd', 'e'])
>>> a.rtruediv(b) a 1.0 b <NA> c <NA> d <NA> e <NA> dtype: float64 >>> a.rtruediv(b, fill_value=0) a 1.0 b 0.0 c 0.0 d Inf e <NA> dtype: float64