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数据集
df_one = ['2017-07-27 04:00:00', '2017-08-07 04:00:00', '2017-08-11 20:00:00', '2017-08-15 16:00:00', '2017-08-21 20:00:00', '2017-08-23 08:00:00', '2017-08-23 16:00:00', '2017-08-31 20:00:00', '2017-09-01 08:00:00', '2017-09-01 16:00:00', '2017-09-01 20:00:00', '2017-09-04 00:00:00', '2017-09-04 20:00:00', '2017-09-05 00:00:00', '2017-09-05 04:00:00', '2017-09-12 12:00:00', '2017-09-13 12:00:00', '2017-09-14 00:00:00', '2017-09-18 04:00:00', '2017-09-21 08:00:00', '2017-09-22 16:00:00', '2017-09-25 08:00:00', '2017-10-10 12:00:00', '2017-10-16 16:00:00', '2017-10-19 12:00:00', '2017-10-23 04:00:00', '2017-10-26 00:00:00', '2017-10-27 00:00:00', '2017-11-10 04:00:00', '2017-11-21 08:00:00', '2017-11-22 16:00:00', '2017-11-30 00:00:00', '2017-11-30 08:00:00', '2017-11-30 16:00:00', '2017-12-01 00:00:00', '2017-12-04 20:00:00', '2017-12-14 08:00:00', '2017-12-15 12:00:00', '2017-12-15 16:00:00', '2017-12-18 00:00:00', '2017-12-19 12:00:00', '2018-01-08 20:00:00', '2018-01-11 20:00:00', '2018-02-06 04:00:00', '2018-02-13 20:00:00', '2018-02-20 08:00:00', '2018-03-02 20:00:00', '2018-03-09 08:00:00', '2018-03-13 20:00:00', '2018-03-16 00:00:00', '2018-03-20 08:00:00', '2018-03-20 16:00:00', '2018-03-22 08:00:00', '2018-03-29 04:00:00', '2018-04-09 20:00:00', '2018-04-13 20:00:00', '2018-04-16 00:00:00', '2018-04-20 08:00:00', '2018-05-11 20:00:00', '2018-05-15 16:00:00', '2018-05-31 16:00:00', '2018-06-13 12:00:00', '2018-06-14 00:00:00', '2018-06-14 20:00:00', '2018-06-22 16:00:00', '2018-06-27 20:00:00', '2018-06-29 20:00:00', '2018-07-03 00:00:00', '2018-07-03 04:00:00', '2018-07-12 04:00:00', '2018-07-16 20:00:00', '2018-07-18 00:00:00', '2018-07-20 20:00:00', '2018-07-27 04:00:00', '2018-07-31 00:00:00', '2018-08-02 00:00:00', '2018-08-20 04:00:00', '2018-09-03 00:00:00', '2018-09-06 08:00:00', '2018-09-07 20:00:00', '2018-09-13 00:00:00', '2018-09-27 16:00:00', '2018-10-11 08:00:00', '2018-10-17 20:00:00', '2018-11-02 00:00:00', '2018-11-05 20:00:00', '2018-11-06 00:00:00', '2018-11-09 04:00:00', '2018-11-16 08:00:00', '2018-11-23 20:00:00', '2018-11-29 12:00:00', '2018-12-03 00:00:00', '2018-12-03 16:00:00', '2018-12-03 20:00:00', '2018-12-04 08:00:00', '2018-12-05 08:00:00', '2018-12-07 00:00:00', '2018-12-12 00:00:00', '2018-12-13 12:00:00', '2018-12-13 20:00:00', '2018-12-18 08:00:00', '2018-12-27 00:00:00', '2018-12-28 00:00:00', '2019-01-03 00:00:00', '2019-01-07 08:00:00', '2019-01-14 20:00:00', '2019-01-15 08:00:00', '2019-01-15 16:00:00', '2019-01-28 04:00:00', '2019-02-05 12:00:00', '2019-02-18 20:00:00', '2019-02-19 12:00:00', '2019-02-20 00:00:00', '2019-03-04 16:00:00', '2019-03-13 00:00:00', '2019-03-22 20:00:00', '2019-04-08 20:00:00', '2019-04-18 16:00:00', '2019-04-30 16:00:00', '2019-05-03 00:00:00', '2019-05-07 04:00:00', '2019-05-08 00:00:00', '2019-05-08 12:00:00', '2019-05-09 08:00:00', '2019-05-09 12:00:00', '2019-05-09 16:00:00', '2019-05-09 20:00:00', '2019-05-15 04:00:00', '2019-05-24 08:00:00', '2019-05-29 00:00:00', '2019-06-03 08:00:00', '2019-06-14 00:00:00', '2019-06-20 12:00:00', '2019-07-01 16:00:00', '2019-07-11 12:00:00', '2019-07-16 16:00:00', '2019-07-19 04:00:00', '2019-07-22 00:00:00', '2019-08-05 16:00:00', '2019-08-14 04:00:00', '2019-08-26 04:00:00', '2019-08-27 12:00:00', '2019-08-27 16:00:00', '2019-08-28 00:00:00', '2019-09-05 08:00:00', '2019-09-11 20:00:00', '2019-09-13 04:00:00', '2019-09-17 00:00:00', '2019-09-18 04:00:00', '2019-09-19 08:00:00', '2019-09-19 16:00:00', '2019-09-20 20:00:00', '2019-10-03 04:00:00', '2019-10-09 08:00:00', '2019-10-09 16:00:00', '2019-10-25 08:00:00', '2019-10-30 08:00:00', '2019-11-05 12:00:00', '2019-11-18 00:00:00', '2019-11-25 00:00:00', '2019-12-02 20:00:00', '2019-12-09 08:00:00', '2019-12-10 16:00:00', '2019-12-19 00:00:00', '2019-12-19 16:00:00', '2019-12-19 20:00:00', '2019-12-27 08:00:00', '2020-01-03 16:00:00', '2020-01-06 16:00:00', '2020-01-08 00:00:00', '2020-01-14 12:00:00', '2020-01-14 20:00:00', '2020-01-15 20:00:00', '2020-01-17 16:00:00', '2020-01-31 20:00:00', '2020-02-05 04:00:00', '2020-02-24 04:00:00', '2020-02-24 12:00:00', '2020-02-25 00:00:00', '2020-03-12 20:00:00', '2020-03-26 04:00:00', '2020-04-01 20:00:00', '2020-04-08 04:00:00', '2020-04-08 08:00:00', '2020-04-09 20:00:00', '2020-04-16 04:00:00', '2020-04-27 20:00:00', '2020-04-28 12:00:00', '2020-04-28 16:00:00', '2020-05-05 16:00:00', '2020-05-13 04:00:00', '2020-05-14 04:00:00', '2020-05-19 00:00:00', '2020-05-25 00:00:00', '2020-05-26 16:00:00', '2020-06-15 00:00:00', '2020-06-16 08:00:00', '2020-06-17 04:00:00', '2020-06-23 08:00:00', '2020-06-25 12:00:00', '2020-06-29 20:00:00', '2020-06-30 00:00:00', '2020-07-02 04:00:00', '2020-07-03 12:00:00', '2020-07-06 08:00:00', '2020-07-10 16:00:00', '2020-07-10 20:00:00', '2020-08-10 04:00:00', '2020-08-13 08:00:00', '2020-08-20 16:00:00', '2020-08-21 08:00:00', '2020-08-21 16:00:00', '2020-08-27 12:00:00', '2020-08-28 00:00:00', '2020-08-28 12:00:00', '2020-09-02 20:00:00', '2020-09-10 20:00:00', '2020-09-17 04:00:00', '2020-09-18 12:00:00', '2020-09-21 16:00:00', '2020-09-30 00:00:00', '2020-10-14 00:00:00', '2020-10-20 00:00:00', '2020-10-28 04:00:00', '2020-11-05 04:00:00', '2020-11-11 20:00:00', '2020-11-13 00:00:00', '2020-11-24 08:00:00', '2020-11-24 16:00:00', '2020-12-10 08:00:00', '2020-12-10 16:00:00', '2020-12-23 04:00:00', '2020-12-24 12:00:00', '2020-12-24 16:00:00', '2020-12-28 12:00:00', '2021-01-08 08:00:00', '2021-01-21 20:00:00', '2021-01-26 12:00:00', '2021-01-27 00:00:00', '2021-01-27 16:00:00', '2021-02-09 04:00:00', '2021-02-17 08:00:00', '2021-02-19 16:00:00', '2021-02-26 20:00:00', '2021-03-11 20:00:00', '2021-03-12 20:00:00', '2021-03-15 04:00:00', '2021-03-15 12:00:00', '2021-03-18 04:00:00', '2021-03-19 04:00:00', '2021-03-23 04:00:00', '2021-03-23 16:00:00', '2021-04-02 16:00:00', '2021-04-05 00:00:00', '2021-04-06 00:00:00', '2021-05-03 00:00:00', '2021-05-07 04:00:00', '2021-05-13 04:00:00', '2021-05-14 20:00:00', '2021-05-27 08:00:00', '2021-06-01 00:00:00', '2021-06-02 16:00:00', '2021-06-03 08:00:00', '2021-06-03 12:00:00']
df_two = ['2017-08-11 23:59', '2017-09-14 23:59', '2017-10-10 23:59', '2017-10-12 23:59', '2017-10-16 23:59', '2017-10-25 23:59', '2018-04-23 23:59', '2018-07-09 23:59', '2018-07-31 23:59', '2018-08-30 23:59', '2018-09-05 23:59', '2018-09-28 23:59', '2018-11-20 23:59', '2019-01-03 23:59', '2019-01-16 23:59', '2019-01-29 23:59', '2019-02-06 23:59', '2019-04-18 23:59', '2019-05-10 23:59', '2019-06-04 23:59', '2019-06-05 23:59', '2019-07-03 23:59', '2019-07-10 23:59', '2019-07-16 23:59', '2019-08-05 23:59', '2019-10-15 23:59', '2019-10-29 23:59', '2019-12-10 23:59', '2019-12-26 23:59', '2020-01-08 23:59', '2020-01-14 23:59', '2020-01-20 23:59', '2020-02-03 23:59', '2020-03-30 23:59', '2020-05-01 23:59', '2020-05-19 23:59', '2020-10-02 23:59', '2020-10-05 23:59', '2020-10-14 23:59', '2020-11-11 23:59', '2021-01-19 23:59', '2021-01-20 23:59', '2021-02-02 23:59', '2021-02-12 23:59', '2021-02-19 23:59', '2021-02-22 23:59', '2021-03-02 23:59', '2021-04-14 23:59', '2021-04-16 23:59', '2021-05-05 23:59', '2021-05-06 23:59']
我正在寻找来自
df_one
的前一行和当前行哪里
df_two
日期在
df_one
的连续两行之间
for each row in df_two:
for each row in df_one:
if df_two > df_one_previous_row & df_two < df_one_current_row:
print(df_one_previous_row & df_one_current_row)
预期输出
2017-08-11 20:00:00 - 2017-08-11 23:59 - 2017-08-15 16:00:00
Found
2017-09-14 00:00:00 - 2017-09-14 23:59 - 2017-09-18 04:00:00
Found
2017-10-10 12:00:00 - 2017-10-10 23:59 - 2017-10-16 16:00:00
Found
2017-10-10 12:00:00 - 2017-10-12 23:59 - 2017-10-16 16:00:00
Found
2017-10-16 16:00:00 - 2017-10-16 23:59 - 2017-10-19 12:00:00
Found
2017-10-23 04:00:00 - 2017-10-25 23:59 - 2017-10-26 00:00:00
Found
2018-04-20 08:00:00 - 2018-04-23 23:59 - 2018-05-11 20:00:00
Found
2018-07-03 04:00:00 - 2018-07-09 23:59 - 2018-07-12 04:00:00
Found
2018-07-31 00:00:00 - 2018-07-31 23:59 - 2018-08-02 00:00:00
Found
2018-08-20 04:00:00 - 2018-08-30 23:59 - 2018-09-03 00:00:00
Found
2018-09-03 00:00:00 - 2018-09-05 23:59 - 2018-09-06 08:00:00
Found
2018-09-27 16:00:00 - 2018-09-28 23:59 - 2018-10-11 08:00:00
Found
2018-11-16 08:00:00 - 2018-11-20 23:59 - 2018-11-23 20:00:00
Found
2019-01-03 00:00:00 - 2019-01-03 23:59 - 2019-01-07 08:00:00
Found
2019-01-15 16:00:00 - 2019-01-16 23:59 - 2019-01-28 04:00:00
Found
2019-01-28 04:00:00 - 2019-01-29 23:59 - 2019-02-05 12:00:00
Found
2019-02-05 12:00:00 - 2019-02-06 23:59 - 2019-02-18 20:00:00
Found
2019-04-18 16:00:00 - 2019-04-18 23:59 - 2019-04-30 16:00:00
Found
2019-05-09 20:00:00 - 2019-05-10 23:59 - 2019-05-15 04:00:00
Found
2019-06-03 08:00:00 - 2019-06-04 23:59 - 2019-06-14 00:00:00
Found
2019-06-03 08:00:00 - 2019-06-05 23:59 - 2019-06-14 00:00:00
Found
2019-07-01 16:00:00 - 2019-07-03 23:59 - 2019-07-11 12:00:00
Found
2019-07-01 16:00:00 - 2019-07-10 23:59 - 2019-07-11 12:00:00
Found
2019-07-16 16:00:00 - 2019-07-16 23:59 - 2019-07-19 04:00:00
Found
2019-08-05 16:00:00 - 2019-08-05 23:59 - 2019-08-14 04:00:00
Found
2019-10-09 16:00:00 - 2019-10-15 23:59 - 2019-10-25 08:00:00
Found
2019-10-25 08:00:00 - 2019-10-29 23:59 - 2019-10-30 08:00:00
Found
2019-12-10 16:00:00 - 2019-12-10 23:59 - 2019-12-19 00:00:00
Found
2019-12-19 20:00:00 - 2019-12-26 23:59 - 2019-12-27 08:00:00
Found
2020-01-08 00:00:00 - 2020-01-08 23:59 - 2020-01-14 12:00:00
Found
2020-01-14 20:00:00 - 2020-01-14 23:59 - 2020-01-15 20:00:00
Found
2020-01-17 16:00:00 - 2020-01-20 23:59 - 2020-01-31 20:00:00
Found
2020-01-31 20:00:00 - 2020-02-03 23:59 - 2020-02-05 04:00:00
Found
2020-03-26 04:00:00 - 2020-03-30 23:59 - 2020-04-01 20:00:00
Found
2020-04-28 16:00:00 - 2020-05-01 23:59 - 2020-05-05 16:00:00
Found
2020-05-19 00:00:00 - 2020-05-19 23:59 - 2020-05-25 00:00:00
Found
2020-09-30 00:00:00 - 2020-10-02 23:59 - 2020-10-14 00:00:00
Found
2020-09-30 00:00:00 - 2020-10-05 23:59 - 2020-10-14 00:00:00
Found
2020-10-14 00:00:00 - 2020-10-14 23:59 - 2020-10-20 00:00:00
Found
2020-11-11 20:00:00 - 2020-11-11 23:59 - 2020-11-13 00:00:00
Found
2021-01-08 08:00:00 - 2021-01-19 23:59 - 2021-01-21 20:00:00
Found
2021-01-08 08:00:00 - 2021-01-20 23:59 - 2021-01-21 20:00:00
Found
2021-01-27 16:00:00 - 2021-02-02 23:59 - 2021-02-09 04:00:00
Found
2021-02-09 04:00:00 - 2021-02-12 23:59 - 2021-02-17 08:00:00
Found
2021-02-19 16:00:00 - 2021-02-19 23:59 - 2021-02-26 20:00:00
Found
2021-02-19 16:00:00 - 2021-02-22 23:59 - 2021-02-26 20:00:00
Found
2021-02-26 20:00:00 - 2021-03-02 23:59 - 2021-03-11 20:00:00
Found
2021-04-06 00:00:00 - 2021-04-14 23:59 - 2021-05-03 00:00:00
Found
2021-04-06 00:00:00 - 2021-04-16 23:59 - 2021-05-03 00:00:00
Found
2021-05-03 00:00:00 - 2021-05-05 23:59 - 2021-05-07 04:00:00
Found
2021-05-03 00:00:00 - 2021-05-06 23:59 - 2021-05-07 04:00:00
Found
从表面上看,使用 for 或 while 循环并不是那么有效。请问我能帮我写一段代码吗?
最佳答案
我们可以使用 np.searchsorted
查找 df_one
中的索引对于 df_two
中的相应时间戳满足包含条件。注意: df_one
中的时间戳必须按顺序排序 searchsorted
正常工作
one = pd.to_datetime(df_one)
two = pd.to_datetime(df_two)
i = np.searchsorted(one, two)
m = ~np.isin(i, [0, len(one)])
df = pd.DataFrame({'df_two': two})
df.loc[m, 'df_one_prev'] = one[i[m] - 1]
df.loc[m, 'df_one_curr'] = one[i[m]]
df['found'] = np.where(m, 'found', 'not found')
df_two df_one_prev df_one_curr found
0 2017-08-11 23:59:00 2017-08-11 20:00:00 2017-08-15 16:00:00 found
1 2017-09-14 23:59:00 2017-09-14 00:00:00 2017-09-18 04:00:00 found
2 2017-10-10 23:59:00 2017-10-10 12:00:00 2017-10-16 16:00:00 found
3 2017-10-12 23:59:00 2017-10-10 12:00:00 2017-10-16 16:00:00 found
4 2017-10-16 23:59:00 2017-10-16 16:00:00 2017-10-19 12:00:00 found
5 2017-10-25 23:59:00 2017-10-23 04:00:00 2017-10-26 00:00:00 found
6 2018-04-23 23:59:00 2018-04-20 08:00:00 2018-05-11 20:00:00 found
7 2018-07-09 23:59:00 2018-07-03 04:00:00 2018-07-12 04:00:00 found
8 2018-07-31 23:59:00 2018-07-31 00:00:00 2018-08-02 00:00:00 found
9 2018-08-30 23:59:00 2018-08-20 04:00:00 2018-09-03 00:00:00 found
10 2018-09-05 23:59:00 2018-09-03 00:00:00 2018-09-06 08:00:00 found
11 2018-09-28 23:59:00 2018-09-27 16:00:00 2018-10-11 08:00:00 found
12 2018-11-20 23:59:00 2018-11-16 08:00:00 2018-11-23 20:00:00 found
13 2019-01-03 23:59:00 2019-01-03 00:00:00 2019-01-07 08:00:00 found
14 2019-01-16 23:59:00 2019-01-15 16:00:00 2019-01-28 04:00:00 found
15 2019-01-29 23:59:00 2019-01-28 04:00:00 2019-02-05 12:00:00 found
16 2019-02-06 23:59:00 2019-02-05 12:00:00 2019-02-18 20:00:00 found
17 2019-04-18 23:59:00 2019-04-18 16:00:00 2019-04-30 16:00:00 found
18 2019-05-10 23:59:00 2019-05-09 20:00:00 2019-05-15 04:00:00 found
19 2019-06-04 23:59:00 2019-06-03 08:00:00 2019-06-14 00:00:00 found
20 2019-06-05 23:59:00 2019-06-03 08:00:00 2019-06-14 00:00:00 found
21 2019-07-03 23:59:00 2019-07-01 16:00:00 2019-07-11 12:00:00 found
22 2019-07-10 23:59:00 2019-07-01 16:00:00 2019-07-11 12:00:00 found
23 2019-07-16 23:59:00 2019-07-16 16:00:00 2019-07-19 04:00:00 found
24 2019-08-05 23:59:00 2019-08-05 16:00:00 2019-08-14 04:00:00 found
25 2019-10-15 23:59:00 2019-10-09 16:00:00 2019-10-25 08:00:00 found
26 2019-10-29 23:59:00 2019-10-25 08:00:00 2019-10-30 08:00:00 found
27 2019-12-10 23:59:00 2019-12-10 16:00:00 2019-12-19 00:00:00 found
28 2019-12-26 23:59:00 2019-12-19 20:00:00 2019-12-27 08:00:00 found
29 2020-01-08 23:59:00 2020-01-08 00:00:00 2020-01-14 12:00:00 found
30 2020-01-14 23:59:00 2020-01-14 20:00:00 2020-01-15 20:00:00 found
31 2020-01-20 23:59:00 2020-01-17 16:00:00 2020-01-31 20:00:00 found
32 2020-02-03 23:59:00 2020-01-31 20:00:00 2020-02-05 04:00:00 found
33 2020-03-30 23:59:00 2020-03-26 04:00:00 2020-04-01 20:00:00 found
34 2020-05-01 23:59:00 2020-04-28 16:00:00 2020-05-05 16:00:00 found
35 2020-05-19 23:59:00 2020-05-19 00:00:00 2020-05-25 00:00:00 found
36 2020-10-02 23:59:00 2020-09-30 00:00:00 2020-10-14 00:00:00 found
37 2020-10-05 23:59:00 2020-09-30 00:00:00 2020-10-14 00:00:00 found
38 2020-10-14 23:59:00 2020-10-14 00:00:00 2020-10-20 00:00:00 found
39 2020-11-11 23:59:00 2020-11-11 20:00:00 2020-11-13 00:00:00 found
40 2021-01-19 23:59:00 2021-01-08 08:00:00 2021-01-21 20:00:00 found
41 2021-01-20 23:59:00 2021-01-08 08:00:00 2021-01-21 20:00:00 found
42 2021-02-02 23:59:00 2021-01-27 16:00:00 2021-02-09 04:00:00 found
43 2021-02-12 23:59:00 2021-02-09 04:00:00 2021-02-17 08:00:00 found
44 2021-02-19 23:59:00 2021-02-19 16:00:00 2021-02-26 20:00:00 found
45 2021-02-22 23:59:00 2021-02-19 16:00:00 2021-02-26 20:00:00 found
46 2021-03-02 23:59:00 2021-02-26 20:00:00 2021-03-11 20:00:00 found
47 2021-04-14 23:59:00 2021-04-06 00:00:00 2021-05-03 00:00:00 found
48 2021-04-16 23:59:00 2021-04-06 00:00:00 2021-05-03 00:00:00 found
49 2021-05-05 23:59:00 2021-05-03 00:00:00 2021-05-07 04:00:00 found
50 2021-05-06 23:59:00 2021-05-03 00:00:00 2021-05-07 04:00:00 found
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假设我有一个文件 script.py 位于 path = "foo/bar/script.py"。我正在寻找一种在 Python 中通过函数 execute_script() 从我的主要 Python
这听起来像是谜语或笑话,但实际上我还没有找到这个问题的答案。 问题到底是什么? 我想运行 2 个脚本。在第一个脚本中,我调用另一个脚本,但我希望它们继续并行,而不是在两个单独的线程中。主要是我不希望第
我有一个带有 python 2.5.5 的软件。我想发送一个命令,该命令将在 python 2.7.5 中启动一个脚本,然后继续执行该脚本。 我试过用 #!python2.7.5 和http://re
我在 python 命令行(使用 python 2.7)中,并尝试运行 Python 脚本。我的操作系统是 Windows 7。我已将我的目录设置为包含我所有脚本的文件夹,使用: os.chdir("
剧透:部分解决(见最后)。 以下是使用 Python 嵌入的代码示例: #include int main(int argc, char** argv) { Py_SetPythonHome
假设我有以下列表,对应于及时的股票价格: prices = [1, 3, 7, 10, 9, 8, 5, 3, 6, 8, 12, 9, 6, 10, 13, 8, 4, 11] 我想确定以下总体上最
所以我试图在选择某个单选按钮时更改此框架的背景。 我的框架位于一个类中,并且单选按钮的功能位于该类之外。 (这样我就可以在所有其他框架上调用它们。) 问题是每当我选择单选按钮时都会出现以下错误: co
我正在尝试将字符串与 python 中的正则表达式进行比较,如下所示, #!/usr/bin/env python3 import re str1 = "Expecting property name
考虑以下原型(prototype) Boost.Python 模块,该模块从单独的 C++ 头文件中引入类“D”。 /* file: a/b.cpp */ BOOST_PYTHON_MODULE(c)
如何编写一个程序来“识别函数调用的行号?” python 检查模块提供了定位行号的选项,但是, def di(): return inspect.currentframe().f_back.f_l
我已经使用 macports 安装了 Python 2.7,并且由于我的 $PATH 变量,这就是我输入 $ python 时得到的变量。然而,virtualenv 默认使用 Python 2.6,除
我只想问如何加快 python 上的 re.search 速度。 我有一个很长的字符串行,长度为 176861(即带有一些符号的字母数字字符),我使用此函数测试了该行以进行研究: def getExe
list1= [u'%app%%General%%Council%', u'%people%', u'%people%%Regional%%Council%%Mandate%', u'%ppp%%Ge
这个问题在这里已经有了答案: Is it Pythonic to use list comprehensions for just side effects? (7 个答案) 关闭 4 个月前。 告
我想用 Python 将两个列表组合成一个列表,方法如下: a = [1,1,1,2,2,2,3,3,3,3] b= ["Sun", "is", "bright", "June","and" ,"Ju
我正在运行带有最新 Boost 发行版 (1.55.0) 的 Mac OS X 10.8.4 (Darwin 12.4.0)。我正在按照说明 here构建包含在我的发行版中的教程 Boost-Pyth
学习 Python,我正在尝试制作一个没有任何第 3 方库的网络抓取工具,这样过程对我来说并没有简化,而且我知道我在做什么。我浏览了一些在线资源,但所有这些都让我对某些事情感到困惑。 html 看起来
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