如何将此 1 项列表分成多个列表？

Question

from urllib.request import urlopen
from bs4 import BeautifulSoup
import numpy as np
table_body = soup.findAll('tbody', class_ = lambda table_rows: table_rows != "thead")
table_data = [[td.getText() for td in table_body[i].findAll('td')]
                for i in range(len(table_body))]

我正在开展一个项目，该项目将从https://www.pro-football-reference.com/years/2021/passing.htm中删除数据。 我的用于抓取表格标题的代码可以正常工作，但是我在格式化表格主体时遇到了很多麻烦，因为它会将玩家统计信息分成几行。 当我运行print(table_data)时，我的结果是一个打印以下内容的单项列表：

[['Tom Brady*', 'TAM', '44', 'QB', '17', '17', '13-4-0', '485', '719', '67.5', '5316', '43', '6', '12', '1.7', '269', '62', '7.4', '7.8', '11.0', '312.7', '102.1', '68.1', '22', '144', '3', '6.98', '7.41', '3', '5', 'Justin Herbert*', 'LAC', '23', 'QB', '17', '17', '9-8-0', '443', '672', '65.9', '5014', '38', '5.7', '15', '2.2', '256', '72', '7.5', '7.6', '11.3', '294.9', '97.7', '65.6', '31', '214', '4.4', '6.83', '6.95', '5', '5', 'Matthew Stafford', 'LAR', '33', 'QB', '17', '17', '12-5-0', '404', '601', '67.2', '4886', '41', '6.8', '17', '2.8', '233', '79', '8.1', '8.2', '12.1', '287.4', '102.9', '63.8', '30', '243', '4.8', '7.36', '7.45', '3', '4',....]]

如何将这一项列表分成多个列表，以便实现我想要的输出：

[
['Tom Brady*', 'TAM', '44', 'QB', '17', '17', '13-4-0', '485', '719', '67.5', '5316', '43', '6', '12', '1.7', '269', '62', '7.4', '7.8', '11.0', '312.7', '102.1', '68.1', '22', '144', '3', '6.98', '7.41', '3', '5']
['Justin Herbert*', 'LAC', '23', 'QB', '17', '17', '9-8-0', '443', '672', '65.9', '5014', '38', '5.7', '15', '2.2', '256', '72', '7.5', '7.6', '11.3', '294.9', '97.7', '65.6', '31', '214', '4.4', '6.83', '6.95', '5', '5']
['Matthew Stafford', 'LAR', '33', 'QB', '17', '17', '12-5-0', '404', '601', '67.2', '4886', '41', '6.8', '17', '2.8', '233', '79', '8.1', '8.2', '12.1', '287.4', '102.9', '63.8', '30', '243', '4.8', '7.36', '7.45', '3', '4']
['Patrick Mahomes'...]
['Derek Carr'...]
]

Answer 1

迭代表的行，并为每一行遍历其<td>以获取其文本：

[[e.text for e in r.select('td')] for row in soup.select('tbody tr')]

输出：

[['Tom Brady*', 'TAM', '44', 'QB', '17', '17', '13-4-0', '485', '719', '67.5', '5316', '43', '6', '12', '1.7', '269', '62', '7.4', '7.8', '11.0', '312.7', '102.1', '68.1', '22', '144', '3', '6.98', '7.41', '3', '5'], ['Justin Herbert*', 'LAC', '23', 'QB', '17', '17', '9-8-0', '443', '672', '65.9', '5014', '38', '5.7', '15', '2.2', '256', '72', '7.5', '7.6', '11.3', '294.9', '97.7', '65.6', '31', '214', '4.4', '6.83', '6.95', '5', '5'], ['Matthew Stafford', 'LAR', '33', 'QB', '17', '17', '12-5-0', '404', '601', '67.2', '4886', '41', '6.8', '17', '2.8', '233', '79', '8.1', '8.2', '12.1', '287.4', '102.9', '63.8', '30', '243', '4.8', '7.36', '7.45', '3', '4'], ['Patrick Mahomes*', 'KAN', '26', 'QB', '17', '17', '12-5-0', '436', '658', '66.3', '4839', '37', '5.6', '13', '2', '260', '75', '7.4', '7.6', '11.1', '284.6', '98.5', '62.2', '28', '146', '4.1', '6.84', '7.07', '3', '3'], ['Derek Carr', 'LVR', '30', 'QB', '17', '17', '10-7-0', '428', '626', '68.4', '4804', '23', '3.7', '14', '2.2', '217', '61', '7.7', '7.4', '11.2', '282.6', '94.0', '52.4', '40', '241', '6', '6.85', '6.60', '3', '6'], ['Joe Burrow', 'CIN', '25', 'QB', '16', '16', '10-6-0', '366', '520', '70.4', '4611', '34', '6.5', '14', '2.7', '202', '82', '8.9', '9.0', '12.6', '288.2', '108.3', '54.3', '51', '370', '8.9', '7.43', '7.51', '2', '3'], ['Dak Prescott', 'DAL', '28', 'QB', '16', '16', '11-5-0', '410', '596', '68.8', '4449', '37', '6.2', '10', '1.7', '227', '51', '7.5', '8.0', '10.9', '278.1', '104.2', '54.6', '30', '144', '4.8', '6.88', '7.34', '1', '2'], ['Josh Allen', 'BUF', '25', 'QB', '17', '17', '11-6-0', '409', '646', '63.3', '4407', '36', '5.6', '15', '2.3', '234', '61', '6.8', '6.9', '10.8', '259.2', '92.2', '60.7', '26', '164', '3.9', '6.31', '6.38', '', ''], ['Kirk Cousins*', 'MIN', '33', 'QB', '16', '16', '8-8-0', '372', '561', '66.3', '4221', '33', '5.9', '7', '1.2', '192', '64', '7.5', '8.1', '11.3', '263.8', '103.1', '52.3', '28', '197', '4.8', '6.83', '7.42', '3', '4'], ['Aaron Rodgers*+', 'GNB', '38', 'QB', '16', '16', '13-3-0', '366', '531', '68.9', '4115', '37', '7', '4', '0.8', '213', '75', '7.7', '8.8', '11.2', '257.2', '111.9', '69.1', '30', '188', '5.3', '7.00', '8.00', '1', '2'], ['Matt Ryan', 'ATL', '36', 'QB', '17', '17', '7-10-0', '375', '560', '67', '3968', '20', '3.6', '12', '2.1', '195', '64', '7.1', '6.8', '10.6', '233.4', '90.4', '46.1', '40', '274', '6.7', '6.16', '5.92', '3', '4'], ['Jimmy Garoppolo', 'SFO', '30', 'QB', '15', '15', '9-6-0', '301', '441', '68.3', '3810', '20', '4.5', '12', '2.7', '172', '83', '8.6', '8.3', '12.7', '254.0', '98.7', '53.3', '29', '201', '6.2', '7.68', '7.38', '3', '3'],...]

---

只是指出pandas.read_html()的替代方案，这将是该任务的一种简单而常见的方法，同时为您使用引擎盖下的beautifulsoup 。

例子

import pandas as pd

#read the first table from url into dataframe
df = pd.read_html('https://www.pro-football-reference.com/years/2021/passing.htm')[0]
#select only rows that are not subheaders
df[df['Rk'] != 'Rk'] 

输出

Rk	播放器	Tm值	年龄	位置	G	GS	Q布雷克	Cmp	攻击者	生产百分比	码	运输署	TD%	诠释	整数%	一维	液化天然气	是/A	是/一	Y/C	Y/G	速度	QBR	斯克	码数.1	百分比	纽约/美国	任何/一个	4QC	GWD
1	汤姆布雷迪*	谭	44	QB	17	17	13-4-0	485	719	67.5	5316	43	6	12	1.7	269	62	7.4	7.8	11	312.7	102.1	68.1	22	144	3	6.98	7.41	3	5
2	贾斯汀赫伯特*	拉丁美洲和加勒比	23	QB	17	17	9-8-0	443	672	65.9	5014	38	5.7	15	2.2	256	72	7.5	7.6	11.3	294.9	97.7	65.6	31	214	4.4	6.83	6.95	5	5
3	马修斯塔福德	拉尔	33	QB	17	17	12-5-0	404	601	67.2	4886	41	6.8	17	2.8	233	79	8.1	8.2	12.1	287.4	102.9	63.8	30	243	4.8	7.36	7.45	3	4
4	帕特里克·马霍姆斯*	菅直人	26	QB	17	17	12-5-0	436	658	66.3	4839	37	5.6	13	2	260	75	7.4	7.6	11.1	284.6	98.5	62.2	28	146	4.1	6.84	7.07	3	3
5	德里克·卡尔	LVR	30	QB	17	17	10-7-0	428	626	68.4	4804	23	3.7	14	2.2	217	61	7.7	7.4	11.2	282.6	94	52.4	40	241	6	6.85	6.6	3	6
6	乔·伯罗	CIN	25	QB	16	16	10-6-0	366	520	70.4	4611	34	6.5	14	2.7	202	82	8.9	9	12.6	288.2	108.3	54.3	51	370	8.9	7.43	7.51	2	3
7	达克普雷斯科特	达尔	28	QB	16	16	11-5-0	410	596	68.8	4449	37	6.2	10	1.7	227	51	7.5	8	10.9	278.1	104.2	54.6	30	144	4.8	6.88	7.34	1	2

...