将累积平均函数应用于分组对象 [英] Applying cumulative mean function to a grouped object

问题描述

我有一个DataFrame df ，其中每个记录代表一个足球比赛。小组将出现不止一次。我需要为每个团队的分数计算某种滚动平均值（呃，不完全是这封信的滚动平均值）。

I have a DataFrame df where each record represents a soccer game. Teams will appear more than once. I need to compute some sort of a rolling mean for each team scores(well, not exactly the rolling mean to the letter).

     date           home           away       score_h  score_a
166  2013-09-01     Fulham         Chelsea       0      0
167  2013-09-03     Arsenal        Everton       0      2
164  2013-09-05     Arsenal        Swansea       5      1
165  2013-09-06     Fulham         Norwich       0      1
163  2013-09-18     Arsenal        Swansea       0      0

我需要计算的是每个球队（主场和客场）的平均分数。

What I need to calculate, is the mean score for each team (home and away).

为简洁起见，我们只需要做home栏：

For brevity, let's just do the home column:

grouped = df.groupby('home')
grouped = grouped.sort_index(by='date') # rows inside groups must be in asc order

结果如下：

    date    home    away    score_h     score_a
home                        
Arsenal     167     2013-09-03  Arsenal     Everton     0   2
            164     2013-09-05  Arsenal     Swansea     5   1
            163     2013-09-18  Arsenal     Swansea     0   0
Fulham      166     2013-09-01  Fulham      Chelsea     0   0
            165     2013-09-06  Fulham      Norwich     0   1

<问题从这里开始

现在，我需要计算团队的滚动平均值。让我们手动为名为 Arsenal 的组执行操作。最后，我们应该结束两列，让我们称它们为： rmean_h 和 rmean_a 。组中的第一条记录（ 167 ）的得分为 0 和 2 。这些 rmean 分别是 0 和 2 。对于组中的第二条记录（ 164 ），rmeans将是（0 + 5）/ 2 = 2.5 并且（2 + 1）/ 2 = 1.5 ，对于第三条记录，（0 + 5 + 0）/ 3 = 1.66 和（2 + 1 + 0）/ 3 = 1 。

Now, I need to compute "rolling mean" for teams. Let's do it by hand for the group named Arsenal. At the end of this we should wind up with 2 extra columns, let's call them: rmean_h and rmean_a. First record in the group (167) has scores of 0 and 2. The rmean of these is simply 0 and 2 respectively. For second record in the group (164), the rmeans will be (0+5)/2 = 2.5 and (2+1) / 2 = 1.5, and for the third record, (0+5+0)/3 = 1.66 and (2+1+0)/3 = 1.

我们的DataFrame现在应该如下所示：

Our DataFrame should now looks like this:

                    date       home         away    score_h score_a rmean_h rmean_a
home                        
Arsenal     167     2013-09-03  Arsenal     Everton     0  2    0       2
            164     2013-09-05  Arsenal     Swansea     5  1    2.5     1.5
            163     2013-09-18  Arsenal     Swansea     0  0    1.66    1
Fulham      166     2013-09-01  Fulham      Chelsea     0  0
            165     2013-09-06  Fulham      Norwich     0  1

我想为我的数据进行这些计算，请问您有什么建议吗？

I want to carry out these calculations for my data, do you have any suggestions please?

推荐答案

您可以应用 expanding_mean （请参阅

You can apply an expanding_mean (see docs) to each group:

grouped = df.sort(columns='date').groupby('home')
grouped['score_h'].apply(pd.expanding_mean)

这篇关于将累积平均函数应用于分组对象的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！