小编OCa*_*OCa的帖子

conda install jupyter尝试从 Anaconda 提示符处安装 jupyter ，引发pin-1 in not installable because it requires python 3.12

我安装了python 3.11，我安装的miniconda版本使用python 3.11。

还有其他方法安装jupyter吗？

完整的错误回溯：

Collecting package metadata (repodata.json): done\nSolving environment: / warning  libmamba Added empty dependency for problem type SOLVER_RULE_UPDATE\nfailed\n\nLibMambaUnsatisfiableError: Encountered problems while solving:\n  - package jupyter-1.0.0-py27_4 requires python >=2.7,<2.8.0a0, but none of the providers can be installed\n\nCould not solve for environment specs\nThe following packages are incompatible\n\xe2\x94\x9c\xe2\x94\x80 jupyter is installable with the potential options\n\xe2\x94\x82  \xe2\x94\x9c\xe2\x94\x80 jupyter 1.0.0 would …

我的数据框结构如下：

   group  maybe_start  maybe_end
0    ABC        False      False
1    ABC         True      False
2    ABC        False      False
3    ABC        False      False
4    ABC         True      False
5    ABC        False      False
6    ABC        False       True
7    ABC        False      False
8    DEF        False      False
9    DEF        False      False
10   DEF         True      False
11   DEF        False      False
12   DEF        False       True
13   DEF        False      False
14   DEF        False      False
15   DEF        False       True
16   DEF         True      False
17   DEF        False      False
18   DEF        False       True …

我正在使用 pandas 版本 1.0.5

下面的示例数据框列出了三天内记录的时间间隔，我寻找每天都有哪些时间间隔重叠的地方。

例如，所有三个日期（黄色突出显示）的重叠时间之一是 1:16 - 2:13。另一个（蓝色突出显示）为 18:45 - 19:00

所以我的预期输出是这样的：[57,15]因为

• 57 - 1:16 - 2:13 之间的分钟。
• 18:45 - 19:00 之间 15 分钟

请使用输入数据帧的生成器：

import pandas as pd
dat1 = [
    ['2023-12-27','2023-12-27 00:00:00','2023-12-27 02:14:00'],
    ['2023-12-27','2023-12-27 03:16:00','2023-12-27 04:19:00'],
    ['2023-12-27','2023-12-27 18:11:00','2023-12-27 20:13:00'],
    ['2023-12-28','2023-12-28 01:16:00','2023-12-28 02:14:00'],
    ['2023-12-28','2023-12-28 02:16:00','2023-12-28 02:28:00'],
    ['2023-12-28','2023-12-28 02:30:00','2023-12-28 02:56:00'],
    ['2023-12-28','2023-12-28 18:45:00','2023-12-28 19:00:00'],
    ['2023-12-29','2023-12-29 01:16:00','2023-12-29 02:13:00'],
    ['2023-12-29','2023-12-29 04:16:00','2023-12-29 05:09:00'],
    ['2023-12-29','2023-12-29 05:11:00','2023-12-29 05:14:00'],
    ['2023-12-29','2023-12-29 18:00:00','2023-12-29 19:00:00']
       ]
df = pd.DataFrame(dat1,columns = ['date','Start_tmp','End_tmp'])
df["Start_tmp"] = pd.to_datetime(df["Start_tmp"])
df["End_tmp"] …