Очистка расширенной статистики NBA с помощью Python Beautifulsoup

Question

Я хочу очистить расширенную статистику НБА.Для начала я просто хочу иметь возможность вычеркнуть названия команд, и у меня возникла проблема, когда она не собирает какую-либо информацию.Я могу искать неправильную вещь в функции find_all.Любая помощь приветствуется!

import requests
from bs4 import BeautifulSoup

url = "https://stats.nba.com/teams/elbow-touch/?sort=ELBOW_TOUCHES&dir=-1"
result = requests.get(url)
c = result.content

soup = Beaut ifulSoup(c,"html.parser")

title = soup.title.text
print(title)

teams = soup.find_all('td',{'class':'team'})

for element in teams:
    print(element.text)

Сайт, который я хочу очистить:

Answer 1

Еще один способ сделать это - отправить запрос get в API сайта и получить ответ json.Изменяя параметры, вы можете получить разные результаты.

Вы можете найти, куда ваш браузер отправил запрос в инструменте разработчика Chrome.

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)

Answer 2

Вариант ответа @ Ajax1234 может привести к загрузке всей таблицы в кадр данных:

import pandas as pd

pd.read_html(str(s))

И вот ваша таблица.

Answer 3

Сайт динамический, поэтому вам нужно использовать selenium:

from selenium import webdriver
from bs4 import BeautifulSoup as soup 
d = webdriver.Chrome('/path/to/chromedriver')
d.get('https://stats.nba.com/teams/elbow-touch/?sort=ELBOW_TOUCHES&dir=-1')
s = soup(d.page_source, 'html.parser').find('table', {'class':'table'})
headers, [_, *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 len(i) > 1]

Теперь final_data сохраняет все результаты команды:

[['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', '-']]

Чтобы получить только команды:

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

Вывод:

['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']

Чтобы получить конкретную статистику, проще всего создать список словарей, привязав значения заголовков ксписки данных:

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