熊猫0.25.x到1.5.2，嵌套重命名器迁移

Question

[In]：

pd.set_option('display.max_colwidth', 200)
topic_stats_df = corpus_topic_df.groupby('Dominant Topic').agg({
'Dominant Topic': {
'Doc Count': np.size,
'% Total Docs': np.size }
})
topic_stats_df = topic_stats_df['Dominant Topic'].reset_index()
topic_stats_df['% Total Docs'] = topic_stats_df['% Total Docs'].apply(lambda row: round((row*100) / len(papers), 2))
topic_stats_df['Topic Desc'] = [topics_df.iloc[t]['Terms per Topic'] for t in range(len(topic_stats_df))]
topic_stats_df

[输出]：

---------------------------------------------------------------------------
SpecificationError                        Traceback (most recent call last)
Cell In[47], line 2
1 pd.set_option('display.max_colwidth', 200)
----> 2 topic_stats_df = corpus_topic_df.groupby('Dominant Topic').agg({
3                                                 'Dominant Topic': {
4                                                     'Doc Count': np.size,
5                                                     '% Total Docs': np.size }
6                                               })
7 topic_stats_df = topic_stats_df['Dominant Topic'].reset_index()
8 topic_stats_df['% Total Docs'] = topic_stats_df['% Total Docs'].apply(lambda row: round((row*100) / len(papers), 2))
File ~/miniconda3/envs/nlp/lib/python3.8/site-packages/pandas/core/groupby/generic.py:894, in DataFrameGroupBy.aggregate(self, func, engine, engine_kwargs, *args, **kwargs)
891 func = maybe_mangle_lambdas(func)
893 op = GroupByApply(self, func, args, kwargs)
--> 894 result = op.agg()
895 if not is_dict_like(func) and result is not None:
896     return result
File ~/miniconda3/envs/nlp/lib/python3.8/site-packages/pandas/core/apply.py:169, in Apply.agg(self)
166     return self.apply_str()
168 if is_dict_like(arg):
--> 169     return self.agg_dict_like()
170 elif is_list_like(arg):
171     # we require a list, but not a 'str'
172     return self.agg_list_like()
File ~/miniconda3/envs/nlp/lib/python3.8/site-packages/pandas/core/apply.py:478, in Apply.agg_dict_like(self)
475     selected_obj = obj._selected_obj
476     selection = obj._selection
--> 478 arg = self.normalize_dictlike_arg("agg", selected_obj, arg)
480 if selected_obj.ndim == 1:
481     # key only used for output
482     colg = obj._gotitem(selection, ndim=1)
File ~/miniconda3/envs/nlp/lib/python3.8/site-packages/pandas/core/apply.py:594, in Apply.normalize_dictlike_arg(self, how, obj, func)
587 # Can't use func.values(); wouldn't work for a Series
588 if (
589     how == "agg"
590     and isinstance(obj, ABCSeries)
591     and any(is_list_like(v) for _, v in func.items())
592 ) or (any(is_dict_like(v) for _, v in func.items())):
593     # GH 15931 - deprecation of renaming keys
--> 594     raise SpecificationError("nested renamer is not supported")
596 if obj.ndim != 1:
597     # Check for missing columns on a frame
598     cols = set(func.keys()) - set(obj.columns)
SpecificationError: nested renamer is not supported

该代码归功于Sarkar，D.(2019)使用Python的文本分析Apress，主题建模部分。

Pip pandas 0.25.3失败了，因为我使用的是m1 Mac。

• 尝试过：pipinstallpandas==0.25.3
• 尝试过：arch-x86_64 pip install pandas==0.25.3

Answer 1

Pandas a将支持删除嵌套重命名，以支持使用pd.NamedAgg

topic_stats_df = corpus_topic_df.groupby('Dominant Topic').agg({
'Dominant Topic': {
'Doc Count': np.size,
'% Total Docs': np.size }
})

此语句可以重写如下：

topic_stats_df = corpus_topic_df.groupby('Dominant Topic')
.agg(Doc_count=('Dominant Topic', np.size), 
Pct_Total_Docs=('Dominant Topic', np.size))