问题描述
date date_block_num shop_id item_id item_price item_cnt_day
0 02.01.2013 0 59 22154 999.00 1.0
1 03.01.2013 0 25 2552 899.00 1.0
2 05.01.2013 0 25 2552 899.00 -1.0
3 06.01.2013 0 25 2554 1709.05 1.0
4 15.01.2013 0 25 2555 1099.00 1.0
我想使用shop_id
并通过过滤,映射和归约来获取每个指定商店的结果。
所以我尝试了:
each_shop = filter(lambda n: n==transactions.shop_id,transactions)
results = map(lambda n: transactions.item_price*transactions.item_cnt_day,each_shop)
for result in results:
print(result)
但是得到了:
/opt/conda/lib/python3.6/site-packages/pandas/core/ops.py:798: FutureWarning: elementwise comparison Failed; returning scalar instead,but in the future will perform elementwise comparison
result = getattr(x,name)(y)
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-21-4e86d47b9f0d> in <module>()
3 each_shop = filter(lambda n: n==transactions.shop_id,transactions)
4 results = map(lambda n: transactions.item_price*transactions.item_cnt_day,each_shop)
----> 5 for result in results:
6 print(result)
7
<ipython-input-21-4e86d47b9f0d> in <lambda>(n)
1 # YOUR CODE GOES HERE
2 # map
----> 3 each_shop = filter(lambda n: n==transactions.shop_id,each_shop)
5 for result in results:
/opt/conda/lib/python3.6/site-packages/pandas/core/ops.py in wrapper(self,other,axis)
859
860 with np.errstate(all='ignore'):
--> 861 res = na_op(values,other)
862 if is_scalar(res):
863 raise TypeError('Could not compare %s type with Series' %
/opt/conda/lib/python3.6/site-packages/pandas/core/ops.py in na_op(x,y)
798 result = getattr(x,name)(y)
799 if result is NotImplemented:
--> 800 raise TypeError("invalid type comparison")
801 except AttributeError:
802 result = op(x,y)
TypeError: invalid type comparison
解决方法
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