*j% @ddlmZddlZddlmZddlmZmZm Z ddZ y)) annotationsN)unique1d) CategoricalCategoricalDtyperecode_for_categoriesc|rt|j|jdk7}|rtj|}|jj |}t |j|j|d}t||j}tj||S|r|St|j|jdk7}|rtj|}t|jx}t|kDrCtjtj||d} tj|| f}n|}t||jj |S)a Code the categories to ensure we can groupby for categoricals. If observed=True, we return a new Categorical with the observed categories only. If sort=False, return a copy of self, coded with categories as returned by .unique(), followed by any categories not appearing in the data. If sort=True, return self. This method is needed solely to ensure the categorical index of the GroupBy result has categories in the order of appearance in the data (GH-8868). Parameters ---------- c : Categorical sort : bool The value of the sort parameter groupby was called with. observed : bool Account only for the observed values Returns ------- Categorical If sort=False, the new categories are set to the order of appearance in codes (unless ordered=True, in which case the original order is preserved), followed by any unrepresented categories in the original order. F)copy)ordered)dtypeT) assume_unique)rcodesnpsort categoriestakerrr r _simple_newlen setdiff1darange concatenate) crobserved take_codesrrr unique_notnan_codesnum_cat missing_codess AC:\FundamentalWorkbench\vendor\pandas\core\groupby\categorical.pyrecode_for_groupbyr s6@aggaggm45 ,J\\&&z2 %aggq||ZeT!QYY?&&uE::  #177177b=#9:  gg&9:q||$$,?(@@ IIg  34 ^^%8-$HI ( q!,,++J7 88)rrrboolrr!returnr) __future__rnumpyrpandas.core.algorithmsrpandas.core.arrays.categoricalrrrrr rr(s"+F9r