Pandas Groupby计算ewm无法正常工作

时间:2018-09-22 17:57:51

标签: python pandas pandas-groupby

假设我有一个如下数据框

ema_features = df[['team']].copy()

for feature_name in df[['score','yards']]:
    span=10
    feature_ema = (df.groupby('team')[feature_name].rolling(window=span, min_periods=span).mean()[:span])
    rest = df[feature_name][span:]
    x = pd.concat([feature_ema, rest]).ewm(span=span, adjust=False).mean()


    ema_features[feature_name] = x

我正在尝试使用此帖子(Does Pandas calculate ewm wrong?)上针对“得分”和“码”列的手动方法计算ewm,但我注意到我的跨度无法按预期的方式用于每个分组球队。到目前为止,这就是我的代码了

ema_features

    team    score   yards
0   team1   NaN NaN
1   team1   NaN NaN
2   team1   NaN NaN
3   team1   NaN NaN
4   team1   NaN NaN
5   team1   NaN NaN
6   team1   NaN NaN
7   team1   NaN NaN
8   team1   NaN NaN
9   team1   NaN NaN
10  team1   6.500000    65.000000
11  team1   7.500000    75.000000
12  team1   8.500000    85.000000
13  team1   9.500000    95.000000
14  team2   7.954545    79.545455
15  team2   6.871901    68.719008
16  team2   6.167919    61.679189
17  team2   5.773752    57.737518
18  team2   5.633070    56.330696
19  team2   5.699784    56.997843
20  team2   5.936187    59.361871
21  team2   6.311426    63.114258
22  team2   6.800257    68.002575
23  team2   7.382029    73.820289
24  team2   8.039842    80.398418
25  team2   8.759871    87.598706
26  team2   9.530803    95.308032
27  team2   10.343384   103.433844

其输出如下

   ema_features

        team    score   yards
    0   team1   NaN NaN
    1   team1   NaN NaN
    2   team1   NaN NaN
    3   team1   NaN NaN
    4   team1   NaN NaN
    5   team1   NaN NaN
    6   team1   NaN NaN
    7   team1   NaN NaN
    8   team1   NaN NaN
    9   team1   NaN NaN
    10  team1   6.500000    65.000000
    11  team1   7.500000    75.000000
    12  team1   8.500000    85.000000
    13  team1   9.500000    95.000000
    14  team2   NaN NaN
    15  team2   NaN NaN
    16  team2   NaN NaN
    17  team2   NaN NaN
    18  team2   NaN NaN
    19  team2   NaN NaN
    20  team2   NaN NaN
    21  team2   NaN NaN
    22  team2   NaN NaN
    23  team2   6.500000    65.000000
    24  team2   7.500000    75.000000
    25  team2   8.500000    85.000000
    26  team2   9.500000    95.000000

我的问题是,如何使我的跨度也适用于第2队?而不是上面的输出,其中第2团队的ewm是与第1团队一起计算的。我希望每个团队的ewm相互独立地计算,这需要应用正确的跨度然后进行计算,就像我在下面期望的那样。

{{1}}

1 个答案:

答案 0 :(得分:2)

您可以尝试将GroupBy.apply与自定义功能一起使用。因此,调整您的docker login循环,尝试执行以下操作:

for