map(self: 'SparseArrayT', mapper) -> 'SparseArrayT'
The correspondence from old values to new.
The output array will have the same density as the input. The output fill value will be the result of applying the mapping to self.fill_value
Map categories using an input mapping or function.
>>> arr = pd.arrays.SparseArray([0, 1, 2])This example is valid syntax, but we were not able to check execution
... arr.map(lambda x: x + 10) [10, 11, 12] Fill: 10 IntIndex Indices: array([1, 2], dtype=int32)
>>> arr.map({0: 10, 1: 11, 2: 12}) [10, 11, 12] Fill: 10 IntIndex Indices: array([1, 2], dtype=int32)This example is valid syntax, but we were not able to check execution
>>> arr.map(pd.Series([10, 11, 12], index=[0, 1, 2])) [10, 11, 12] Fill: 10 IntIndex Indices: array([1, 2], dtype=int32)See :
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