试试这个：

import pandas as pd
from itertools import product

house_types = [1,2,3,4]
realtors = [*'ABCDEF']
neighborhood = ['a']
zip_code = ['10018']
daily_data = product(house_types, realtors, neighborhood, zip_code)
dates = pd.date_range('2023-8-1', '2023-9-1')
data = product(dates, daily_data)
idx, data = zip(*data)
cols = ["House_type", "Realtor", "Neighborhood", "Zipcode"]
df = pd.DataFrame(data, index=idx, columns=cols).rename_axis('Date')
print(df)
>>>
           House_type   Realtor    Neighborhood  Zipcode
Date                
2023-08-01  1           A               a        10018
2023-08-01  1           B               a        10018
2023-08-01  1           C               a        10018
2023-08-01  1           D               a        10018
2023-08-01  1           E               a        10018
   ...     ...         ...             ...        ...
2023-09-01  4           B               a        10018
2023-09-01  4           C               a        10018
2023-09-01  4           D               a        10018
2023-09-01  4           E               a        10018
2023-09-01  4           F               a        10018

这听起来像笛卡尔积，我认为itertools中的product可以帮助：

from itertools import product
list(product(['a', 'b', 'c'], ['Alex', 'Maggie', 'Ginger', 'Pat'], range(3)))

[('a', 'Alex', 0),
 ('a', 'Alex', 1),
 ('a', 'Alex', 2),
 ('a', 'Maggie', 0),
 ('a', 'Maggie', 1),
 ('a', 'Maggie', 2),
 ('a', 'Ginger', 0),
 ('a', 'Ginger', 1),
 ('a', 'Ginger', 2),
 ('a', 'Pat', 0),
 ('a', 'Pat', 1),
 ('a', 'Pat', 2),
 ('b', 'Alex', 0),
 ('b', 'Alex', 1),
 ('b', 'Alex', 2),
 ('b', 'Maggie', 0),
...
]

您可以使用两个嵌套循环创建 Dataframe ：

• 第一个while循环迭代日期（您已经了解了这个循环）
• 第二个for循环迭代房地产经纪人列表

您可以简单地创建包含日期、房地产经纪人和房屋类型的临时 Dataframe df_temp（从numpy数组中读取），将它们附加到一个列表中，最后将此 Dataframe 列表连接到您的输出 Dataframe df中：

import numpy as np
import pandas as pd
from datetime import date,timedelta
delta = timedelta(days=1)
start = date(2023,8,1)
end=date(2023,9,1)
loop_date = start
realtors = ['Alex', 'Maggie', 'Ginger', 'Pat']

list_of_dataframes = []

while loop_date<=end:
    for realtor in realtors:
        df_temp = pd.DataFrame(columns={"Date", "House type", "Realtor"})
        df_temp['House type'] = pd.Series(np.arange(1,5))
        df_temp['Date'] = loop_date
        df_temp['Realtor'] = realtor
        list_of_dataframes.append(df_temp)
        loop_date+=delta
df = pd.concat(list_of_dataframes)

完成此操作后，剩下要做的唯一事情就是填充Neighborhood和Zipcode列！