Question

我可能是pandas DataFrame的基本问题。在以下代码段中，我插入了一个计算列＆＃39; CAPACITY_CHECK＆＃39;然后我尝试根据它分组数据。但是我一直有以下错误：TypeError：unhashable type：＆＃39; numpy.ndarray＆＃39;

＆＃13;

TEMP['CAPACITY_CHECK'] = TEMP[['ADD_CAPACITY_ST', 'CAPACITY_ST', 'VOLUME_PER_SUPPLIER']].apply(lambda X: numpy.where(X[0]+X[1]<X[2],'Non OK', 'OK'), axis=1)
TEMP.groupby('CAPACITY_CHECK')['ID'].count()

＆＃13;

由于我没有尝试修改任何不可变对象，而新列的类型是＆＃34; Series＆＃34;，我不明白为什么我会遇到错误。

提前致谢

Answer 1

我认为您需要删除申请并仅使用numpy.where：

mask = (TEMP['ADD_CAPACITY_ST'] + TEMP['CAPACITY_ST']) < TEMP['VOLUME_PER_SUPPLIER']
TEMP['CAPACITY_CHECK'] = numpy.where(mask,'Non OK', 'OK')

<强>示例：

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

然后使用GroupBy.size或GroupBy.count：

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

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

Difference between count and size

熊猫不可动的类型：＆＃39; numpy.ndarray＆＃39;与熊猫groupby

1 个答案: