我想我会这样做:
创建一些数据进行测试
df = pd.DataFrame({'Id':np.random.randint(1,10,100),'Type':np.random.choice(list('ABCD'),100),'Guid':np.random.randint(10000,99999,100)})
print(df.head()
Id Type Guid
0 2 A 89247
1 4 B 39262
2 3 C 45522
3 1 B 99724
4 4 C 51322
选择 n 作为要返回的记录数并进行分组
n = 5
df_groups = df.groupby('Id')
使用 for 循环迭代 df_group 并打印
for name,group in df_groups:
print('ID: ' + str(name))
print(group.head(n))
print("\n")
Output:
ID: 1
Id Type Guid
3 1 B 99724
5 1 B 74182
37 1 D 49219
47 1 B 81464
65 1 C 84925
ID: 2
Id Type Guid
0 2 A 89247
6 2 A 16499
7 2 A 79956
34 2 C 56393
40 2 A 49883
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编辑要打印列表中每个 ID 的所有 Guid,您可以使用以下命令:
for name,group in df_groups:
print('ID: ' + str(name))
print(group.Guid.tolist())
print("\n")
Output:
ID: 1
[99724, 74182, 49219, 81464, 84925, 67834, 43275, 35743, 36478, 94662, 21183]
ID: 2
[89247, 16499, 79956, 56393, 49883, 97633, 11768, 14639, 88591, 31263, 98729]
ID: 3
[45522, 13971, 75882, 96489, 58414, 22051, 80304, 46144, 22481, 11278, 84622, 61145]
ID: 4
[39262, 51322, 76930, 83740, 60152, 90735, 42039, 22114, 76077, 83234, 96134, 93559, 87903, 98199, 76096, 64378]
ID: 5
[13444, 55762, 13206, 94768, 19665, 75761, 90755, 45737, 23506, 89345, 94912, 81200, 91868]
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