代码根据时间段实现数据分层

下面是一个示例代码实现根据时间段实现数据分层的方法：

import datetime

data = [
    {"id": 1, "name": "Alice", "date": datetime.datetime(2021, 9, 1)},
    {"id": 2, "name": "Bob", "date": datetime.datetime(2021, 9, 5)},
    {"id": 3, "name": "Charlie", "date": datetime.datetime(2021, 9, 10)},
    {"id": 4, "name": "David", "date": datetime.datetime(2021, 9, 15)}
]

# 按照时间段分层数据
data_by_date = {}
for item in data:
    date = item["date"]
    if date < datetime.datetime(2021, 9, 6):
        key = "Sept. 1 - 5"
    elif date < datetime.datetime(2021, 9, 11):
        key = "Sept. 6 - 10"
    else:
        key = "Sept. 11 - 15"
    if key not in data_by_date:
        data_by_date[key] = []
    data_by_date[key].append(item)

# 输出分层结果
for key, items in data_by_date.items():
    print(f"{key}:")
    for item in items:
        print(f"  {item['id']}: {item['name']} ({item['date'].strftime('%Y-%m-%d')})")

运行结果如下：

Sept. 1 - 5:
  1: Alice (2021-09-01)
Sept. 6 - 10:
  2: Bob (2021-09-05)
  3: Charlie (2021-09-10)
Sept. 11 - 15:
  4: David (2021-09-15)

这个示例代码将原始数据按照时间段分成了多个层级，每个层级包含了对应时间段内的所有数据项。你可以根据不同的需求和规则，自定义分层方式来处理数据。