argsort(self, ascending=True, kind='quicksort', **kwargs)
Changed to sort missing values at the end.
While an ordering is applied to the category values, arg-sorting in this context refers more to organizing and grouping together based on matching category values. Thus, this function can be called on an unordered Categorical instance unlike the functions 'Categorical.min' and 'Categorical.max'.
Whether the indices should result in an ascending or descending sort.
Sorting algorithm.
passed through to numpy.argsort
.
Return the indices that would sort the Categorical.
>>> pd.Categorical(['b', 'b', 'a', 'c']).argsort() array([2, 0, 1, 3])This example is valid syntax, but we were not able to check execution
>>> cat = pd.Categorical(['b', 'b', 'a', 'c'],
... categories=['c', 'b', 'a'],
... ordered=True)
... cat.argsort() array([3, 0, 1, 2])
Missing values are placed at the end
This example is valid syntax, but we were not able to check execution>>> cat = pd.Categorical([2, None, 1])See :
... cat.argsort() array([2, 0, 1])
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