假設我有一個具有兩個索引級別的多索引 Pandas 資料框：month_begin 和 month_end
import pandas as pd
multi_index = pd.MultiIndex.from_tuples([("2022-03-01", "2022-03-31"),
("2022-04-01", "2022-04-30"),
("2022-05-01", "2022-05-31"),
("2022-06-01", "2022-06-30")])
multi_index.names = ['month_begin', 'month_end']
df = pd.DataFrame(np.random.rand(4,100), index=multi_index)
df
0 1 ... 98 99
month_begin month_end ...
2022-03-01 2022-03-31 0.322032 0.205307 ... 0.975128 0.673460
2022-04-01 2022-04-30 0.113813 0.278981 ... 0.951049 0.090765
2022-05-01 2022-05-31 0.777918 0.842734 ... 0.667831 0.274189
2022-06-01 2022-06-30 0.221407 0.555711 ... 0.745158 0.648246
我想對資料進行重新采樣，以在相應月份的每個小時獲得一個月內的值：
0 1 ... 98 99
...
2022-03-01 00:00 0.322032 0.205307 ... 0.975128 0.673460
2022-03-01 01:00 0.322032 0.205307 ... 0.975128 0.673460
2022-03-01 02:00 0.322032 0.205307 ... 0.975128 0.673460
...
2022-06-30 22:00 0.221407 0.555711 ... 0.745158 0.648246
2022-06-30 23:00 0.221407 0.555711 ... 0.745158 0.648246
我知道我可以使用resample()，但我正在努力解決如何做到這一點。有人有線索嗎？
uj5u.com熱心網友回復：
IIUC，使用 list_comprehension 和explodewith試試這個pd.date_range：
df['Date'] = [pd.date_range(s, e, freq='H') for s, e in df.index]
df_out = df.explode('Date').set_index('Date')
輸出：
0 1 ... 98 99
Date ...
2022-03-01 00:00:00 0.396311 0.138263 ... 0.637640 0.106366
2022-03-01 01:00:00 0.396311 0.138263 ... 0.637640 0.106366
2022-03-01 02:00:00 0.396311 0.138263 ... 0.637640 0.106366
2022-03-01 03:00:00 0.396311 0.138263 ... 0.637640 0.106366
2022-03-01 04:00:00 0.396311 0.138263 ... 0.637640 0.106366
... ... ... ... ... ...
2022-06-29 20:00:00 0.129921 0.654878 ... 0.619212 0.142297
2022-06-29 21:00:00 0.129921 0.654878 ... 0.619212 0.142297
2022-06-29 22:00:00 0.129921 0.654878 ... 0.619212 0.142297
2022-06-29 23:00:00 0.129921 0.654878 ... 0.619212 0.142297
2022-06-30 00:00:00 0.129921 0.654878 ... 0.619212 0.142297
[2836 rows x 100 columns]
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