Featuretools TypeError：不可哈希类型：'Int64Index'

Question

我正在尝试从3个数据帧创建一个实体集，但这样做却出现错误：TypeError：无法散列的类型：'Int64Index'

我已经在Internet上搜索了类似的问题，但是找不到与日期时间类型有关的任何问题。请注意，df_raw_view_logs的所有列都不是唯一的，因此这些列均不能用作索引值，因此正在使用dataframe.index。

当我从中创建列作为时间索引时，我正在为其抛出错误的数据帧共享dtypes。

df_raw_view_logs.dtypes

server_time    datetime64[ns]
device_type              int8
session_id              int64
user_id                 int64
item_id                 int64
dtype: object

es = ft.EntitySet()
es = es.entity_from_dataframe(entity_id="train", 
                          dataframe=df_es_train,
                          index=df_es_train.index,
                          time_index="impression_time",
                          )

es = es.entity_from_dataframe(entity_id="viewlogs", 
                          dataframe=df_es_view_logs,
                          index=df_es_view_logs.index,
                          time_index="server_time",
                          )

es = es.entity_from_dataframe(entity_id="itemdata", 
                          dataframe=df_es_item_data,
                          index=df_es_item_data.index,
                          )

new_relationship = ft.Relationship(es["train"]["user_id"],
                               es["viewlogs"]["user_id"])
es = es.add_relationship(new_relationship)
new_relationship_1 = ft.Relationship(es["viewlogs"]["item_id"],
                               es["itemdata"]["item_id"])
es = es.add_relationship(new_relationship_1)

    ---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-32-81425e9b87c5> in <module>
      9                               dataframe=df_es_view_logs,
     10                               index=df_es_view_logs.index,
---> 11                               time_index="server_time",
     12                               )
     13 

D:\Anaconda3\envs\fastai\lib\site-packages\featuretools\entityset\entityset.py in entity_from_dataframe(self, entity_id, dataframe, index, variable_types, make_index, time_index, secondary_time_index, already_sorted)
    495             secondary_time_index=secondary_time_index,
    496             already_sorted=already_sorted,
--> 497             make_index=make_index)
    498         self.entity_dict[entity.id] = entity
    499         self.reset_data_description()

D:\Anaconda3\envs\fastai\lib\site-packages\featuretools\entityset\entity.py in __init__(self, id, df, entityset, variable_types, index, time_index, secondary_time_index, last_time_index, already_sorted, make_index, verbose)
     67         """
     68         _validate_entity_params(id, df, time_index)
---> 69         created_index, index, df = _create_index(index, make_index, df)
     70 
     71         self.id = id

D:\Anaconda3\envs\fastai\lib\site-packages\featuretools\entityset\entity.py in _create_index(index, make_index, df)
    547         # Case 3: user wanted to make index but column already exists
    548         raise RuntimeError("Cannot make index: index variable already present")
--> 549     elif index not in df.columns:
    550         if not make_index:
    551             # Case 4: user names index, it is not in df. does not specify

D:\Anaconda3\envs\fastai\lib\site-packages\pandas\core\indexes\base.py in __contains__(self, key)
   3917     @Appender(_index_shared_docs['contains'] % _index_doc_kwargs)
   3918     def __contains__(self, key):
-> 3919         hash(key)
   3920         try:
   3921             return key in self._engine

D:\Anaconda3\envs\fastai\lib\site-packages\pandas\core\indexes\base.py in __hash__(self)
   3932 
   3933     def __hash__(self):
-> 3934         raise TypeError("unhashable type: %r" % type(self).__name__)
   3935 
   3936     def __setitem__(self, key, value):

TypeError: unhashable type: 'Int64Index'

Answer 1

这是错误的，因为index参数应该是一个字符串，该字符串是DataFrame中作为索引的列的名称。不是索引值本身。