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累积条件计数

作者:互联网

我有以下数据框.

df = pd.DataFrame(
    {
        "drive": [1,1,2,2,2,3,3,3,4,4,4,5,5,6,6,7,7],
        "team": ['home','home','away','away','away','home','home','home','away',
                 'away','away','home','home','away','away','home','home'],
        "home_comfy_lead": [0,0,0,0,0,0,0,1,0,0,0,1,1,0,0,1,1],
        "home_drives": [1,1,0,0,0,2,2,2,0,0,0,3,3,0,0,4,4],
        'home_drives_with_comfy_lead': [0,0,0,0,0,0,0,1,0,0,0,2,2,0,0,3,3]
    })

我正在尝试制作两列:

> home_drives列,该列唯一地计算来自
车队依据车队的“主场”称号
柱.
>一个home_drives_with_comfy_lead列,该列唯一地计算
home_drives根据home_comfy_lead是否为true来驱动值.

我想要的输出是:

    drive  team  home_comfy_lead  home_drives  home_drives_with_comfy_lead
0       1  home                0            1                            0
1       1  home                0            1                            0
2       2  away                0            0                            0
3       2  away                0            0                            0
4       2  away                0            0                            0
5       3  home                0            2                            0
6       3  home                0            2                            0
7       3  home                1            2                            1
8       4  away                0            0                            0
9       4  away                0            0                            0
10      4  away                0            0                            0
11      5  home                1            3                            2
12      5  home                1            3                            2
13      6  away                0            0                            0
14      6  away                0            0                            0
15      7  home                1            4                            3
16      7  home                1            4                            3

有人能帮忙吗?我已经为此苦苦挣扎了几天.

解决方法:

使用.where屏蔽,然后使用groupby ngroup.在这里,我们很幸运为NaN组分配了-1,并且您还想从1开始计数,因此同时添加了两个固定值.

df['home_drives'] = df.where(df.team == 'home').groupby('drive').ngroup()+1
df['hdwcl'] = df.where(df.home_comfy_lead == 1).groupby('home_drives').ngroup()+1

输出:

    drive  team  home_comfy_lead  home_drives  hdwcl
0       1  home                0            1      0
1       1  home                0            1      0
2       2  away                0            0      0
3       2  away                0            0      0
4       2  away                0            0      0
5       3  home                0            2      0
6       3  home                0            2      0
7       3  home                1            2      1
8       4  away                0            0      0
9       4  away                0            0      0
10      4  away                0            0      0
11      5  home                1            3      2
12      5  home                1            3      2
13      6  away                0            0      0
14      6  away                0            0      0
15      7  home                1            4      3
16      7  home                1            4      3

标签:pandas-groupby,pandas,data-science,python,numpy
来源: https://codeday.me/bug/20191211/2106416.html