问 Pandas KeyError on pd.merge，即使在数据仓库中存在相同的列时

EN

我试图在多个列上加入两个数据格式。即使所有列都存在于两个数据格式中，我在执行pd.merge时也会得到一个关键错误。

当我尝试做一个 "ValueError: len(left_on) must equal the number of levels in the index of "right"" 时，我就得到了.join

Dataframe 1:

>>data.columns
Index(['weather.description', 'weather.icon', 'weather.id', 'weather.main',
       'dt', 'main.pressure', 'main.temp_min', 'main.temp_max', 'main.temp',
       'main.humidity', 'main.grnd_level', 'main.sea_level', 'wind.speed',
       'wind.deg', 'wind.gust', 'id', 'day', 'month', 'hour', 'dd', 'year'],
      dtype='object')
>>data.dtypes
weather.description     object
weather.icon            object
weather.id               int64
weather.main            object
dt                      object
main.pressure          float64
main.temp_min          float64
main.temp_max          float64
main.temp              float64
main.humidity            int32
main.grnd_level        float64
main.sea_level         float64
wind.speed             float64
wind.deg               float64
wind.gust              float64
id                     float64
day                     object
month                   object
year                    object
hour                    object
dd                      object
dtype: object

Dataframe 2:

>>df_crime.columns
Index(['beat', 'disposition', 'event_date', 'event_number', 'general_location',
       'location_1', 'map_x', 'map_y', 'type', 'type_description', 'ward',
       'day', 'year', 'month', 'dd', 'hour'],
      dtype='object')
>>df_crime.dtypes
beat                 object
disposition          object
event_date           object
event_number         object
general_location     object
location_1           object
map_x               float64
map_y               float64
type                 object
type_description     object
ward                float64
day                  object
year                 object
month                object