pandas Groupby Agg功能不会降低 [英] Pandas Groupby Agg Function Does Not Reduce
问题描述
我正在使用很长时间以来在我的工作中使用的聚合函数.想法是，如果传递给函数的Series的长度为1(即组中只有一个观察值)，则返回观察值.如果通过的系列的长度大于一，则观测值将以列表形式返回.
I am using an aggregation function that I have used in my work for a long time now. The idea is that if the Series passed to the function is of length 1 (i.e. the group only has one observation) then that observations is returned. If the length of the Series passed is greater than one, then the observations are returned in a list.
对于某些人来说，这似乎很奇怪，但这不是一个X，Y问题，我有充分的理由要执行与该问题无关的操作.
This may seem odd to some, but this is not an X,Y problem, I have good reason for wanting to do this that is not relevant to this question.
这是我一直在使用的功能:
This is the function that I have been using:
def MakeList(x):
""" This function is used to aggregate data that needs to be kept distinc within multi day
observations for later use and transformation. It makes a list of the data and if the list is of length 1
then there is only one line/day observation in that group so the single element of the list is returned.
If the list is longer than one then there are multiple line/day observations and the list itself is
returned."""
L = x.tolist()
if len(L) > 1:
return L
else:
return L[0]
现在由于某种原因，使用当前正在处理的数据集，我收到ValueError声明该函数不会减少.这是一些测试数据以及我正在使用的其余步骤:
Now for some reason, with the current data set I am working on I get a ValueError stating that the function does not reduce. Here is some test data and the remaining steps I am using:
import pandas as pd
DF = pd.DataFrame({'date': ['2013-04-02',
'2013-04-02',
'2013-04-02',
'2013-04-02',
'2013-04-02',
'2013-04-02',
'2013-04-02',
'2013-04-02',
'2013-04-02',
'2013-04-02'],
'line_code': ['401101',
'401101',
'401102',
'401103',
'401104',
'401105',
'401105',
'401106',
'401106',
'401107'],
's.m.v.': [ 7.760,
25.564,
25.564,
9.550,
4.870,
7.760,
25.564,
5.282,
25.564,
5.282]})
DFGrouped = DF.groupby(['date', 'line_code'], as_index = False)
DF_Agg = DFGrouped.agg({'s.m.v.' : MakeList})
在尝试调试此命令时，我将打印语句置于print L和print x.index的作用下，
输出如下:
In trying to debug this, I put a print statement to the effect of print L and print x.index and
the output was as follows:
[7.7599999999999998, 25.564]
Int64Index([0, 1], dtype='int64')
[7.7599999999999998, 25.564]
Int64Index([0, 1], dtype='int64')
由于某些原因，似乎agg两次将Series传递给该函数.据我所知，这根本不正常，大概是我的功能没有减少的原因.
For some reason it appears that agg is passing the Series twice to the function. This as far as I know is not normal at all, and is presumably the reason why my function is not reducing.
例如，如果我编写这样的函数:
For example if I write a function like this:
def test_func(x):
print x.index
return x.iloc[0]
这运行没有问题，并且打印语句为:
This runs without problem and the print statements are:
DF_Agg = DFGrouped.agg({'s.m.v.' : test_func})
Int64Index([0, 1], dtype='int64')
Int64Index([2], dtype='int64')
Int64Index([3], dtype='int64')
Int64Index([4], dtype='int64')
Int64Index([5, 6], dtype='int64')
Int64Index([7, 8], dtype='int64')
Int64Index([9], dtype='int64')
这表示每个组仅作为Series一次传递给该函数.
Which indicates that each group is only being passed once as a Series to the function.
任何人都可以帮助我了解为什么会失败吗?我已经在许多处理的数据集中成功使用了此功能....
Can anyone help me understand why this is failing? I have used this function with success in many many data sets I work with....
谢谢
推荐答案
我无法真正解释您的原因，但是根据我的经验，在pandas.DataFrame中的list并不能很好地发挥作用.
I can't really explain you why, but from my experience list in pandas.DataFrame don't work all that well.
我通常改用tuple.
会起作用的:
I usually use tuple instead.
That will work:
def MakeList(x):
T = tuple(x)
if len(T) > 1:
return T
else:
return T[0]
DF_Agg = DFGrouped.agg({'s.m.v.' : MakeList})
date line_code s.m.v.
0 2013-04-02 401101 (7.76, 25.564)
1 2013-04-02 401102 25.564
2 2013-04-02 401103 9.55
3 2013-04-02 401104 4.87
4 2013-04-02 401105 (7.76, 25.564)
5 2013-04-02 401106 (5.282, 25.564)
6 2013-04-02 401107 5.282
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