您好,我有以下数据框:
Fruit metric
0 Apple NaN
1 Apple 100.0
2 Apple NaN
3 Peach 70.0
4 Pear 120.0
5 Pear 100.0
6 Pear NaN
我的目标是按水果分组并按顺序将 metric
的每个非空值添加到具有自己单独列的累积列表中,如下所示:
Fruit metric metric_cum
0 Apple NaN []
1 Apple 100.0 [100]
2 Apple NaN [100]
3 Peach 70.0 [70]
4 Pear 120.0 [120]
5 Pear 100.0 [120, 100]
6 Pear NaN [120, 100]
我试过这样做:
df['metric1'] = df['metric'].astype(str)
df.groupby('Fruit')['metric1'].cumsum()
但这会导致 DataError: No numeric types to aggregate
。
我也试过这样做:
df.groupby('Fruit')['metric'].apply(list)
导致:
Fruit
Apple [nan, 100.0, nan]
Peach [70.0]
Pear [120.0, 100.0, nan]
Name: metric, dtype: object
但这不是累加的,不能做成专栏。 感谢您的帮助
最佳答案
使用:
df['metric'] = df['metric'].apply(lambda x: [] if pd.isnull(x) else [int(x)])
df['metric_cum'] = df.groupby('Fruit')['metric'].apply(lambda x: x.cumsum())
print (df)
Fruit metric metric_cum
0 Apple [] []
1 Apple [100] [100]
2 Apple [] [100]
3 Peach [70] [70]
4 Pear [120] [120]
5 Pear [100] [120, 100]
6 Pear [] [120, 100]
或者:
a = df['metric'].apply(lambda x: [] if pd.isnull(x) else [int(x)])
df['metric_cum'] = a.groupby(df['Fruit']).apply(lambda x: x.cumsum())
print (df)
Fruit metric metric_cum
0 Apple NaN []
1 Apple 100.0 [100]
2 Apple NaN [100]
3 Peach 70.0 [70]
4 Pear 120.0 [120]
5 Pear 100.0 [120, 100]
6 Pear NaN [120, 100]
关于python - 使用 groupby 的列的累积列表,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/44719855/