使用python beautifulsoup获得NBA高级统计数据

我想获得NBA高级统计数据。首先，我只想能够刮取球队的名字，我有一个问题，它没有收集任何信息。我可能在find_all函数中查找错误的内容。感谢您的帮助

导入请求 从bs4导入BeautifulSoup url=https://stats.nba.com/teams/elbow-touch/?sort=ELBOW_TOUCHES&dir=-1 结果=requests.geturl c=结果。内容 soup=Beaut-ifulSoupc，html.parser title=soup.title.text 版名 teams=soup.find_all'td'，{'class'：'team'} 对于团队中的元素：

---

printelement.text站点是动态的，因此，您需要使用：

现在，final_数据存储所有团队结果：

[['Houston Rockets', '63', '38', '25', '242.0', '367.0', '8.8', '2.4', '3.8', '64.2', '0.4', '0.7', '62.8', '5.5', '-', '3.7', '-', '0.5', '14.0', '0.5', '5.4', '0.3', '-'], ['Milwaukee Bucks', '63', '48', '15', '241.2', '409.5', '9.5', '2.3', '3.6', '62.4', '0.7', '1.0', '73.3', '5.4', '-', '4.3', '-', '0.6', '13.0', '0.5', '5.2', '0.4', '-'], ['New York Knicks', '62', '13', '49', '241.6', '420.4', '9.5', '2.0', '3.4', '56.8', '0.7', '1.0', '69.8', '4.8', '-', '4.7', '-', '0.6', '13.7', '0.5', '5.3', '0.5', '-'], ['Charlotte Hornets', '63', '29', '34', '242.0', '409.7', '9.6', '1.7', '3.5', '50.0', '1.1', '1.5', '71.9', '4.7', '-', '4.6', '-', '0.7', '14.2', '0.4', '4.5', '0.7', '-'], ['Detroit Pistons', '62', '31', '31', '242.8', '437.0', '10.0', '1.6', '3.2', '51.3', '0.9', '1.2', '75.3', '4.4', '-', '5.0', '-', '0.9', '17.6', '0.7', '6.8', '0.6', '-'], ['Washington Wizards', '62', '25', '37', '243.2', '420.2', '10.5', '2.5', '4.3', '58.4', '0.9', '1.2', '76.4', '6.1', '-', '4.6', '-', '0.7', '15.5', '0.6', '5.6', '0.5', '-'], ['Atlanta Hawks', '64', '22', '42', '242.3', '434.9', '11.0', '2.2', '3.7', '58.6', '1.2', '1.5', '77.3', '5.7', '-', '5.3', '-', '0.7', '12.9', '0.7', '6.5', '0.7', '-'], ['Brooklyn Nets', '65', '32', '33', '243.8', '440.3', '11.2', '2.5', '4.4', '58.3', '1.2', '1.7', '70.8', '6.4', '-', '4.6', '-', '0.7', '14.9', '0.9', '7.9', '0.8', '-'], ['San Antonio Spurs', '64', '35', '29', '241.6', '402.3', '11.3', '2.3', '4.1', '55.5', '0.8', '1.0', '85.7', '5.6', '-', '5.8', '-', '1.1', '18.7', '0.5', '4.8', '0.4', '-'], ['Boston Celtics', '64', '38', '26', '241.6', '420.8', '11.5', '2.5', '4.2', '58.4', '0.5', '0.7', '71.7', '5.5', '-', '5.7', '-', '0.9', '15.0', '0.6', '5.6', '0.3', '-'], ['Toronto Raptors', '64', '46', '18', '242.3', '418.0', '11.5', '3.5', '5.9', '59.6', '1.2', '1.5', '78.1', '8.3', '-', '4.1', '-', '0.7', '16.3', '0.4', '3.7', '0.7', '-'], ['Portland Trail Blazers', '63', '39', '24', '241.6', '409.8', '11.8', '2.4', '4.6', '51.9', '1.2', '1.5', '80.2', '6.1', '-', '5.5', '-', '1.0', '18.8', '0.7', '5.7', '0.7', '-'], ['Utah Jazz', '61', '36', '25', '240.8', '435.9', '11.9', '2.0', '3.8', '51.1', '1.4', '2.2', '66.7', '5.4', '-', '5.9', '-', '1.0', '17.1', '0.7', '5.9', '1.0', '-'], ['Minnesota Timberwolves', '63', '29', '34', '241.6', '412.4', '12.0', '2.9', '5.0', '57.3', '1.3', '1.6', '79.8', '7.3', '-', '5.2', '-', '1.0', '19.5', '0.6', '5.2', '0.7', '-'], ['Chicago Bulls', '63', '18', '45', '243.2', '411.3', '12.4', '2.8', '4.8', '57.9', '0.7', '0.9', '77.6', '6.4', '-', '6.3', '-', '0.8', '12.4', '0.6', '4.5', '0.4', '-'], ['LA Clippers', '65', '36', '29', '241.9', '430.4', '12.4', '2.9', '5.1', '56.9', '1.0', '1.5', '69.5', '7.0', '-', '5.4', '-', '0.9', '15.9', '0.7', '5.5', '0.6', '-'], ['Miami Heat', '62', '28', '34', '240.4', '426.1', '12.6', '2.0', '4.0', '50.2', '0.7', '1.3', '56.8', '4.9', '-', '7.0', '-', '1.1', '15.4', '0.4', '3.4', '0.5', '-'], ['New Orleans Pelicans', '65', '29', '36', '240.0', '435.0', '12.6', '3.5', '6.4', '54.8', '1.2', '1.6', '74.5', '8.4', '-', '4.4', '-', '0.9', '20.4', '0.7', '5.2', '0.8', '-'], ['Phoenix Suns', '64', '13', '51', '242.3', '435.8', '12.9', '2.8', '5.0', '56.7', '1.0', '1.3', '73.5', '6.8', '-', '6.2', '-', '0.8', '13.7', '0.6', '4.7', '0.6', '-'], ['Oklahoma City Thunder', '63', '39', '24', '242.0', '364.8', '13.6', '3.2', '5.8', '54.5', '1.0', '1.4', '65.9', '7.5', '-', '5.8', '-', '0.9', '14.7', '0.7', '4.8', '0.6', '-'], ['Dallas Mavericks', '62', '27', '35', '240.8', '435.4', '13.9', '1.8', '3.1', '55.9', '1.2', '1.6', '76.5', '5.0', '-', '8.6', '-', '1.1', '13.1', '0.8', '5.7', '0.7', '-'], ['Golden State Warriors', '63', '44', '19', '241.6', '442.3', '13.9', '2.8', '4.8', '57.0', '1.2', '1.5', '81.7', '6.9', '-', '7.2', '-', '1.6', '21.7', '0.8', '5.8', '0.7', '-'], ['Orlando Magic', '63', '28', '35', '241.2', '405.0', '14.0', '3.2', '5.7', '55.8', '1.1', '1.4', '80.9', '7.7', '-', '6.5', '-', '1.4', '21.8', '0.6', '4.0', '0.7', '-'], ['Los Angeles Lakers', '63', '30', '33', '241.6', '405.9', '14.2', '3.3', '5.7', '57.8', '1.1', '1.6', '67.0', '7.8', '-', '6.3', '-', '1.3', '20.7', '0.9', '6.3', '0.7', '-'], ['Denver Nuggets', '62', '42', '20', '240.8', '435.2', '15.0', '3.1', '5.3', '59.1', '1.1', '1.5', '72.5', '7.5', '-', '7.4', '-', '1.7', '22.3', '1.0', '6.4', '0.7', '-'], ['Indiana Pacers', '64', '41', '23', '240.4', '431.7', '15.3', '4.4', '7.2', '60.6', '1.4', '1.9', '74.2', '10.4', '-', '5.8', '-', '1.2', '20.9', '0.9', '6.0', '0.9', '-'], ['Cleveland Cavaliers', '64', '16', '48', '241.2', '407.3', '16.1', '2.3', '4.5', '51.6', '0.9', '1.1', '80.0', '5.6', '-', '10.0', '-', '1.2', '12.3', '0.5', '3.4', '0.4', '-'], ['Philadelphia 76ers', '63', '40', '23', '242.0', '446.9', '16.6', '2.5', '4.7', '52.7', '1.4', '1.7', '82.6', '6.6', '-', '9.6', '-', '1.8', '18.6', '0.7', '4.3', '0.7', '-'], ['Sacramento Kings', '62', '31', '31', '240.8', '425.2', '16.7', '3.2', '6.3', '50.3', '1.1', '1.6', '65.3', '7.5', '-', '8.0', '-', '1.5', '18.3', '1.0', '6.2', '0.7', '-'], ['Memphis Grizzlies', '65', '25', '40', '241.9', '452.1', '20.5', '3.4', '6.7', '51.3', '1.5', '1.9', '81.1', '8.6', '-', '11.2', '-', '1.6', '14.1', '0.8', '4.1', '0.8', '-']]

要仅获得团队：

teams = [a for a, *_ in final_data]

输出：

['Houston Rockets', 'Milwaukee Bucks', 'New York Knicks', 'Charlotte Hornets', 'Detroit Pistons', 'Washington Wizards', 'Atlanta Hawks', 'Brooklyn Nets', 'San Antonio Spurs', 'Boston Celtics', 'Toronto Raptors', 'Portland Trail Blazers', 'Utah Jazz', 'Minnesota Timberwolves', 'Chicago Bulls', 'LA Clippers', 'Miami Heat', 'New Orleans Pelicans', 'Phoenix Suns', 'Oklahoma City Thunder', 'Dallas Mavericks', 'Golden State Warriors', 'Orlando Magic', 'Los Angeles Lakers', 'Denver Nuggets', 'Indiana Pacers', 'Cleveland Cavaliers', 'Philadelphia 76ers', 'Sacramento Kings', 'Memphis Grizzlies']

要获取特定的统计信息，最简单的方法是通过将标题值绑定到数据列表来创建字典列表：

data_attrs = [dict(zip(headers, i)) for i in final_data]
all_touches = [i['Touches'] for i in data_attrs]

---

网站是动态的，因此，您需要使用：

现在，final_数据存储所有团队结果：

[['Houston Rockets', '63', '38', '25', '242.0', '367.0', '8.8', '2.4', '3.8', '64.2', '0.4', '0.7', '62.8', '5.5', '-', '3.7', '-', '0.5', '14.0', '0.5', '5.4', '0.3', '-'], ['Milwaukee Bucks', '63', '48', '15', '241.2', '409.5', '9.5', '2.3', '3.6', '62.4', '0.7', '1.0', '73.3', '5.4', '-', '4.3', '-', '0.6', '13.0', '0.5', '5.2', '0.4', '-'], ['New York Knicks', '62', '13', '49', '241.6', '420.4', '9.5', '2.0', '3.4', '56.8', '0.7', '1.0', '69.8', '4.8', '-', '4.7', '-', '0.6', '13.7', '0.5', '5.3', '0.5', '-'], ['Charlotte Hornets', '63', '29', '34', '242.0', '409.7', '9.6', '1.7', '3.5', '50.0', '1.1', '1.5', '71.9', '4.7', '-', '4.6', '-', '0.7', '14.2', '0.4', '4.5', '0.7', '-'], ['Detroit Pistons', '62', '31', '31', '242.8', '437.0', '10.0', '1.6', '3.2', '51.3', '0.9', '1.2', '75.3', '4.4', '-', '5.0', '-', '0.9', '17.6', '0.7', '6.8', '0.6', '-'], ['Washington Wizards', '62', '25', '37', '243.2', '420.2', '10.5', '2.5', '4.3', '58.4', '0.9', '1.2', '76.4', '6.1', '-', '4.6', '-', '0.7', '15.5', '0.6', '5.6', '0.5', '-'], ['Atlanta Hawks', '64', '22', '42', '242.3', '434.9', '11.0', '2.2', '3.7', '58.6', '1.2', '1.5', '77.3', '5.7', '-', '5.3', '-', '0.7', '12.9', '0.7', '6.5', '0.7', '-'], ['Brooklyn Nets', '65', '32', '33', '243.8', '440.3', '11.2', '2.5', '4.4', '58.3', '1.2', '1.7', '70.8', '6.4', '-', '4.6', '-', '0.7', '14.9', '0.9', '7.9', '0.8', '-'], ['San Antonio Spurs', '64', '35', '29', '241.6', '402.3', '11.3', '2.3', '4.1', '55.5', '0.8', '1.0', '85.7', '5.6', '-', '5.8', '-', '1.1', '18.7', '0.5', '4.8', '0.4', '-'], ['Boston Celtics', '64', '38', '26', '241.6', '420.8', '11.5', '2.5', '4.2', '58.4', '0.5', '0.7', '71.7', '5.5', '-', '5.7', '-', '0.9', '15.0', '0.6', '5.6', '0.3', '-'], ['Toronto Raptors', '64', '46', '18', '242.3', '418.0', '11.5', '3.5', '5.9', '59.6', '1.2', '1.5', '78.1', '8.3', '-', '4.1', '-', '0.7', '16.3', '0.4', '3.7', '0.7', '-'], ['Portland Trail Blazers', '63', '39', '24', '241.6', '409.8', '11.8', '2.4', '4.6', '51.9', '1.2', '1.5', '80.2', '6.1', '-', '5.5', '-', '1.0', '18.8', '0.7', '5.7', '0.7', '-'], ['Utah Jazz', '61', '36', '25', '240.8', '435.9', '11.9', '2.0', '3.8', '51.1', '1.4', '2.2', '66.7', '5.4', '-', '5.9', '-', '1.0', '17.1', '0.7', '5.9', '1.0', '-'], ['Minnesota Timberwolves', '63', '29', '34', '241.6', '412.4', '12.0', '2.9', '5.0', '57.3', '1.3', '1.6', '79.8', '7.3', '-', '5.2', '-', '1.0', '19.5', '0.6', '5.2', '0.7', '-'], ['Chicago Bulls', '63', '18', '45', '243.2', '411.3', '12.4', '2.8', '4.8', '57.9', '0.7', '0.9', '77.6', '6.4', '-', '6.3', '-', '0.8', '12.4', '0.6', '4.5', '0.4', '-'], ['LA Clippers', '65', '36', '29', '241.9', '430.4', '12.4', '2.9', '5.1', '56.9', '1.0', '1.5', '69.5', '7.0', '-', '5.4', '-', '0.9', '15.9', '0.7', '5.5', '0.6', '-'], ['Miami Heat', '62', '28', '34', '240.4', '426.1', '12.6', '2.0', '4.0', '50.2', '0.7', '1.3', '56.8', '4.9', '-', '7.0', '-', '1.1', '15.4', '0.4', '3.4', '0.5', '-'], ['New Orleans Pelicans', '65', '29', '36', '240.0', '435.0', '12.6', '3.5', '6.4', '54.8', '1.2', '1.6', '74.5', '8.4', '-', '4.4', '-', '0.9', '20.4', '0.7', '5.2', '0.8', '-'], ['Phoenix Suns', '64', '13', '51', '242.3', '435.8', '12.9', '2.8', '5.0', '56.7', '1.0', '1.3', '73.5', '6.8', '-', '6.2', '-', '0.8', '13.7', '0.6', '4.7', '0.6', '-'], ['Oklahoma City Thunder', '63', '39', '24', '242.0', '364.8', '13.6', '3.2', '5.8', '54.5', '1.0', '1.4', '65.9', '7.5', '-', '5.8', '-', '0.9', '14.7', '0.7', '4.8', '0.6', '-'], ['Dallas Mavericks', '62', '27', '35', '240.8', '435.4', '13.9', '1.8', '3.1', '55.9', '1.2', '1.6', '76.5', '5.0', '-', '8.6', '-', '1.1', '13.1', '0.8', '5.7', '0.7', '-'], ['Golden State Warriors', '63', '44', '19', '241.6', '442.3', '13.9', '2.8', '4.8', '57.0', '1.2', '1.5', '81.7', '6.9', '-', '7.2', '-', '1.6', '21.7', '0.8', '5.8', '0.7', '-'], ['Orlando Magic', '63', '28', '35', '241.2', '405.0', '14.0', '3.2', '5.7', '55.8', '1.1', '1.4', '80.9', '7.7', '-', '6.5', '-', '1.4', '21.8', '0.6', '4.0', '0.7', '-'], ['Los Angeles Lakers', '63', '30', '33', '241.6', '405.9', '14.2', '3.3', '5.7', '57.8', '1.1', '1.6', '67.0', '7.8', '-', '6.3', '-', '1.3', '20.7', '0.9', '6.3', '0.7', '-'], ['Denver Nuggets', '62', '42', '20', '240.8', '435.2', '15.0', '3.1', '5.3', '59.1', '1.1', '1.5', '72.5', '7.5', '-', '7.4', '-', '1.7', '22.3', '1.0', '6.4', '0.7', '-'], ['Indiana Pacers', '64', '41', '23', '240.4', '431.7', '15.3', '4.4', '7.2', '60.6', '1.4', '1.9', '74.2', '10.4', '-', '5.8', '-', '1.2', '20.9', '0.9', '6.0', '0.9', '-'], ['Cleveland Cavaliers', '64', '16', '48', '241.2', '407.3', '16.1', '2.3', '4.5', '51.6', '0.9', '1.1', '80.0', '5.6', '-', '10.0', '-', '1.2', '12.3', '0.5', '3.4', '0.4', '-'], ['Philadelphia 76ers', '63', '40', '23', '242.0', '446.9', '16.6', '2.5', '4.7', '52.7', '1.4', '1.7', '82.6', '6.6', '-', '9.6', '-', '1.8', '18.6', '0.7', '4.3', '0.7', '-'], ['Sacramento Kings', '62', '31', '31', '240.8', '425.2', '16.7', '3.2', '6.3', '50.3', '1.1', '1.6', '65.3', '7.5', '-', '8.0', '-', '1.5', '18.3', '1.0', '6.2', '0.7', '-'], ['Memphis Grizzlies', '65', '25', '40', '241.9', '452.1', '20.5', '3.4', '6.7', '51.3', '1.5', '1.9', '81.1', '8.6', '-', '11.2', '-', '1.6', '14.1', '0.8', '4.1', '0.8', '-']]

要仅获得团队：

teams = [a for a, *_ in final_data]

输出：

['Houston Rockets', 'Milwaukee Bucks', 'New York Knicks', 'Charlotte Hornets', 'Detroit Pistons', 'Washington Wizards', 'Atlanta Hawks', 'Brooklyn Nets', 'San Antonio Spurs', 'Boston Celtics', 'Toronto Raptors', 'Portland Trail Blazers', 'Utah Jazz', 'Minnesota Timberwolves', 'Chicago Bulls', 'LA Clippers', 'Miami Heat', 'New Orleans Pelicans', 'Phoenix Suns', 'Oklahoma City Thunder', 'Dallas Mavericks', 'Golden State Warriors', 'Orlando Magic', 'Los Angeles Lakers', 'Denver Nuggets', 'Indiana Pacers', 'Cleveland Cavaliers', 'Philadelphia 76ers', 'Sacramento Kings', 'Memphis Grizzlies']

要获取特定的统计信息，最简单的方法是通过将标题值绑定到数据列表来创建字典列表：

data_attrs = [dict(zip(headers, i)) for i in final_data]
all_touches = [i['Touches'] for i in data_attrs]

---

另一种方法是向站点API发送get请求并接收json响应。通过改变参数，可以得到不同的结果

您可以在chrome developer工具下查找浏览器发送请求的位置

import requests

url = "https://stats.nba.com/stats/leaguedashptstats?"

headers = {
    "User-Agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/72.0.3626.119 Safari/537.36"
}

params = {
    "PerMode": "PerGame",
    "PlayerOrTeam": "Team",
    "PtMeasureType": "ElbowTouch",
    "Season": "2018-19",
    "SeasonType": "Regular Season",
    "StarterBench": "",
    "PlayerPosition": "",
    "PlayerExperience": "",
    "GameScope": "",
    "VsConference": "",
    "VsDivision": "",
    "DateFrom": "",
    "DateTo": "",
    "SeasonSegment": "",
    "Location": "",
    "Outcome": "",
    "LastNGames": "0",
    "Month": "0",
    "OpponentTeamID": "0"
}

r = requests.get(url, params=params, headers=headers)
data = r.json()
results = data['resultSets'][0]['rowSet']

for result in results:
    print(result)

---

另一种方法是向站点API发送get请求并接收json响应。通过改变参数，可以得到不同的结果

您可以在chrome developer工具下查找浏览器发送请求的位置

import requests

url = "https://stats.nba.com/stats/leaguedashptstats?"

headers = {
    "User-Agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/72.0.3626.119 Safari/537.36"
}

params = {
    "PerMode": "PerGame",
    "PlayerOrTeam": "Team",
    "PtMeasureType": "ElbowTouch",
    "Season": "2018-19",
    "SeasonType": "Regular Season",
    "StarterBench": "",
    "PlayerPosition": "",
    "PlayerExperience": "",
    "GameScope": "",
    "VsConference": "",
    "VsDivision": "",
    "DateFrom": "",
    "DateTo": "",
    "SeasonSegment": "",
    "Location": "",
    "Outcome": "",
    "LastNGames": "0",
    "Month": "0",
    "OpponentTeamID": "0"
}

r = requests.get(url, params=params, headers=headers)
data = r.json()
results = data['resultSets'][0]['rowSet']

for result in results:
    print(result)

---

@Ajax1234答案的一个变体可以将整个表加载到数据帧中：

import pandas as pd

pd.read_html(str(s))

---

这是您的表。

对@Ajax1234答案的修改可以将整个表加载到数据帧中：

import pandas as pd

pd.read_html(str(s))

---

这是您的桌子。

谢谢您的帮助。你能告诉我你在这些行中做了什么吗：标题，[[uu，*data]=[i.text for i in s.find_all'th]，[[i.text for i in b.find_all'td']for b in s.find_all'tr']final_data=[i for i in data if leni>1]*不知道如何格式化这也是一个注释，如何使用这段代码访问特定的统计数据？@Brennamosher这些行由列表理解组成，从bs4对象形成表数据。[[i.text for i in b.find_all'td']for b in s.find_all'tr']是一种嵌套理解，它将表数据创建为列表列表，而[i for i in data if leni>1]则通过检查子列表的长度来删除解析过程中发现的所有无关元素。有关列表理解的更多信息，请参阅。要访问特定的统计信息，请查看我最近的编辑。@Ajax1234-如果你有时间和精力，请解释一下“[[ux，*data]”的作用？@JackFleeting没问题。[u，*data]被称为解包，因为它的赋值结果[[i.text代表b中的i.find_all'td']代表s.find_all'tr']中的b，它有一个空列表作为头上迭代结果的第一个元素，而利用u，a是一种更干净的方法来删除它并将剩余结果存储在列表中。请参阅更多有关打开包装的信息谢谢您的帮助。你能告诉我你在这些行中做了什么吗：标题，[[uu，*data]=[i.text for i in s.find_all'th]，[[i.text for i in b.find_all'td']for b in s.find_all'tr']final_data=[i for i in data if leni>1]*不知道如何格式化这也是一个注释，如何使用这段代码访问特定的统计数据？@Brennamosher这些行由列表理解组成，从bs4对象形成表数据。[[i.text for i in b.find_all'td']for b in s.find_all'tr']是一种嵌套理解，它将表数据创建为列表列表，而[i for i in data if leni>1]则通过检查子列表的长度来删除解析过程中发现的所有无关元素。有关列表理解的更多信息，请参阅。要访问特定的统计信息，请查看我最近的编辑。@Ajax1234-如果你有时间和精力，请解释一下“[[ux，*data]”的作用？@JackFleeting没问题。[u，*data]被称为解包，因为它的赋值结果[[i.text代表b中的i.find_all'td']代表s.find_all'tr']中的b，它有一个空列表作为头上迭代结果的第一个元素，而利用u，a是一种更干净的方法来删除它并将剩余结果存储在列表中。请参阅有关解包的更多信息