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Python 3.x 熊猫不易损坏类型:';numpy.ndarray和#x27;与熊猫群比_Python 3.x_Pandas_Dataframe_Pandas Groupby - Fatal编程技术网

Python 3.x 熊猫不易损坏类型:';numpy.ndarray和#x27;与熊猫群比

Python 3.x 熊猫不易损坏类型:';numpy.ndarray和#x27;与熊猫群比,python-3.x,pandas,dataframe,pandas-groupby,Python 3.x,Pandas,Dataframe,Pandas Groupby,我被困在熊猫数据帧的一个基本问题上。在下面的代码段中,我插入了一个计算列“CAPACITY\u CHECK”,然后尝试根据该列的数据进行分组。但我一直有以下错误:TypeError:unhabable类型:“numpy.ndarray” TEMP['CAPACITY\u CHECK']=TEMP['ADD\u CAPACITY\u ST',CAPACITY\u ST',VOLUME\u PER\u SUPPLIER']].apply(lambda X:numpy.where(X[0]+X[1]

我被困在熊猫数据帧的一个基本问题上。在下面的代码段中,我插入了一个计算列“CAPACITY\u CHECK”,然后尝试根据该列的数据进行分组。但我一直有以下错误:TypeError:unhabable类型:“numpy.ndarray”


TEMP['CAPACITY\u CHECK']=TEMP['ADD\u CAPACITY\u ST',CAPACITY\u ST',VOLUME\u PER\u SUPPLIER']].apply(lambda X:numpy.where(X[0]+X[1]我认为您需要删除apply并仅使用:

mask = (TEMP['ADD_CAPACITY_ST'] + TEMP['CAPACITY_ST']) < TEMP['VOLUME_PER_SUPPLIER']
TEMP['CAPACITY_CHECK'] = numpy.where(mask,'Non OK', 'OK')
TEMP = pd.DataFrame({'ADD_CAPACITY_ST':[10,20,30],
                     'CAPACITY_ST':[10,20,30],
                     'VOLUME_PER_SUPPLIER':[40,20,100]})

mask = (TEMP['ADD_CAPACITY_ST'] + TEMP['CAPACITY_ST']) < TEMP['VOLUME_PER_SUPPLIER']
TEMP['CAPACITY_CHECK'] = numpy.where(mask,'Non OK', 'OK')
print (TEMP)
   ADD_CAPACITY_ST  CAPACITY_ST  VOLUME_PER_SUPPLIER CAPACITY_CHECK
0               10           10                   40         Non OK
1               20           20                   20             OK
2               30           30                  100         Non OK              
TEMP.groupby('CAPACITY_CHECK')['ID'].size()

TEMP.groupby('CAPACITY_CHECK')['ID'].count()