Python 创建一个数据帧，包括分组和合计

我有以下数据框：

    Race Course                 Horse  Year  Month  Day  Amount Won/Lost
0       Aintree               Red Rum  2017      5   12   11.58      won
1   Punchestown               Camelot  2016     12   22  122.52      won
2       Sandown        Beef of Salmon  2016     11   17   20.00     lost
3           Ayr              Corbiere  2016     11    3   25.00     lost
4    Fairyhouse               Red Rum  2016     12    2   65.75      won
5           Ayr               Camelot  2017      3   11   12.05      won
6       Aintree         Hurricane Fly  2017      5   12   11.58      won
7   Punchestown        Beef or Salmon  2016     12   22  112.52      won
8       Sandown              Aldaniti  2016     11   17   10.00     lost
9           Ayr   Henry the Navigator  2016     11    1   15.00     lost
10   Fairyhouse               Jumanji  2016     10    2   65.75      won
11          Ayr           Came Second  2017      3   11   12.05      won
12      Aintree                Murder  2017      5   12    5.00     lost
13  Punchestown           King Arthur  2016      6   22   52.52      won
14      Sandown         Filet of Fish  2016     11   17   20.00     lost
15          Ayr                Denial  2016     11    3   25.00     lost
16   Fairyhouse          Don't Gamble  2016     12   12  165.75      won
17          Ayr               Ireland  2017      1   11   22.05      won

我正在尝试创建另一个数据帧，其中仅包括所有比赛（行）和所有获胜比赛的总和。理想情况下，它将如下所示：

total races     18
total won       11

然而，我所能做的就是按计数分组，计算总赢和总输。这就是我所尝试的：

df = df.groupby(['Won/Lost']).size().add_prefix('total')

这就是它的回报：

Won/Lost
total lost     7
total won     11
dtype: int64

---

我正处于死胡同，无法找到简单的解决方案。

假设

races.csv的内容是：

Race Course,Horse,Year,Month,Day,Amount,Won/Lost
Aintree,Red Rum,2017,5,12,11.58,won
Punchestown,Camelot,2016,12,22,122.52,won
Sandown,Beef of Salmon,2016,11,17,20.00,lost
Ayr,Corbiere,2016,11,3,25.00,lost
Fairyhouse,Red Rum,2016,12,2,65.75,won
Ayr,Camelot,2017,3,11,12.05,won
Aintree,Hurricane Fly,2017,5,12,11.58,won
Punchestown,Beef or Salmon,2016,12,22,112.52,won
Sandown,Aldaniti,2016,11,17,10.00,lost
Ayr,Henry the Navigator,2016,11,1,15.00,lost
Fairyhouse,Jumanji,2016,10,2,65.75,won
Ayr,Came Second,2017,3,11,12.05,won
Aintree,Murder,2017,5,12,5.00,lost
Punchestown,King Arthur,2016,6,22,52.52,won
Sandown,Filet of Fish,2016,11,17,20.00,lost
Ayr,Denial,2016,11,3,25.00,lost
Fairyhouse,Don't Gamble,2016,12,12,165.75,won
Ayr,Ireland,2017,1,11,22.05,won

获取新数据帧的步骤：

>>> races_df = pd.read_csv('races.csv')
>>> races_df
    Race Course                Horse  Year  Month  Day  Amount Won/Lost
0       Aintree              Red Rum  2017      5   12   11.58      won
1   Punchestown              Camelot  2016     12   22  122.52      won
2       Sandown       Beef of Salmon  2016     11   17   20.00     lost
3           Ayr             Corbiere  2016     11    3   25.00     lost
4    Fairyhouse              Red Rum  2016     12    2   65.75      won
5           Ayr              Camelot  2017      3   11   12.05      won
6       Aintree        Hurricane Fly  2017      5   12   11.58      won
7   Punchestown       Beef or Salmon  2016     12   22  112.52      won
8       Sandown             Aldaniti  2016     11   17   10.00     lost
9           Ayr  Henry the Navigator  2016     11    1   15.00     lost
10   Fairyhouse              Jumanji  2016     10    2   65.75      won
11          Ayr          Came Second  2017      3   11   12.05      won
12      Aintree               Murder  2017      5   12    5.00     lost
13  Punchestown          King Arthur  2016      6   22   52.52      won
14      Sandown        Filet of Fish  2016     11   17   20.00     lost
15          Ayr               Denial  2016     11    3   25.00     lost
16   Fairyhouse         Don't Gamble  2016     12   12  165.75      won
17          Ayr              Ireland  2017      1   11   22.05      won
>>>
>>> total_races = len(races_df)
>>>
>>> total_win = races_df[races_df['Won/Lost'] == 'won']['Won/Lost'].count()
>>>
>>> new_df = pd.DataFrame({'total_races': total_races, 'total_win': total_win}, index=pd.RangeIndex(1))
>>>
>>> new_df
   total_races  total_win
0           18         11

因此，总比赛数将是
len（df）
，总获胜数是
（df['won/Lost']='won'）。sum（）
？不起作用，它返回相同值的6行数据帧，同时总获胜数返回0Hi@TomWalsh，我现在编辑的'won/Lost'列名搞错了。另外，我刚刚测试了将数据存储到csv文件中，从中创建一个数据帧
races_df
，并运行上述代码，它给了我完美的结果。能否检查“赢/输”值中是否没有多余的空格。另外，您的原始数据的格式是什么？嗨，原始数据是一个csv文件，我已经读取并存储在数据框中。您认为“赢/输”值中有额外的空格是正确的。这可能会解决我在使用此数据集时遇到的许多问题。至于“new_df”，它仍然是由6行相同的行创建的，关于为什么会这样，有什么想法吗？所以我已经弄明白了，正如在对我的原始问题的评论中正确指出的那样，total_win的解决方案是（df['Won/Lost']='Won'）。sum（），你的种族解决方案[races_df['Won/Lost']='Won'].count（）。值返回了一个数组。另外，您的数据帧声明没有索引，并且使用标量值，因此会抛出错误。很好，您的问题已经解决了！根据您的反馈，我对代码进行了轻微修改，并再次发布了代码，以及用于测试的csv文件。希望能有帮助。