Ausgabe
Ich kam heute mit einer Frage zu diesem Projekt, die super schnell beantwortet wurde, also bin ich wieder da. Der folgende Code kratzt durch die bereitgestellte Website, ruft die Daten ab und fügt eine Spalte für die Instanz der Tabelle hinzu, die geschabt wird. Der nächste Kampf, dem ich damit gegenüberstehe, besteht darin, alle Instanzen der Spielneuheit mit einer Spalte in die big_df zu laden, um zu replizieren, was das Drop-down-Menü der Spielneuheit derzeit anzeigt. Wenn mir jemand beim letzten Teil meines Puzzles helfen könnte, wäre ich sehr dankbar.
https://www.fantasypros.com/daily-fantasy/nba/fanduel-defense-vs-position.php
from selenium import webdriver
from selenium.webdriver.chrome.service import Service
from selenium.webdriver.chrome.options import Options
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
import time as t
import pandas as pd
pd.set_option('display.max_columns', None)
pd.set_option('display.max_colwidth', None)
big_df = pd.DataFrame()
chrome_options = Options()
chrome_options.add_argument("--no-sandbox")
chrome_options.add_argument('disable-notifications')
chrome_options.add_argument("window-size=1280,720")
webdriver_service = Service(r'chromedriver\chromedriver') ## path to where you saved chromedriver binary
driver = webdriver.Chrome(service=webdriver_service, options=chrome_options)
wait = WebDriverWait(driver, 20)
url = "https://www.fantasypros.com/daily-fantasy/nba/fanduel-defense-vs-position.php"
driver.get(url)
sleep(60)
tables_list = wait.until(EC.presence_of_all_elements_located((By.XPATH, '//ul[@class="pills pos-filter pull-left"]/li')))
for x in tables_list:
x.click()
print('selected', x.text)
t.sleep(2)
table = wait.until(EC.element_to_be_clickable((By.XPATH, '//table[@id="data-table"]')))
df = pd.read_html(table.get_attribute('outerHTML'))[0]
df['Category'] = x.text.strip()
big_df = pd.concat([big_df, df], axis=0, ignore_index=True)
print('done, moving to next table')
print(big_df)
big_df.to_csv('fanduel.csv')
Lösung
So können Sie Ihr Endziel erreichen:
from selenium import webdriver
from selenium.webdriver.chrome.service import Service
from selenium.webdriver.chrome.options import Options
from selenium.webdriver.support.ui import Select
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
import time as t
import pandas as pd
pd.set_option('display.max_columns', None)
pd.set_option('display.max_colwidth', None)
big_df = pd.DataFrame()
chrome_options = Options()
chrome_options.add_argument("--no-sandbox")
chrome_options.add_argument('disable-notifications')
chrome_options.add_argument("window-size=1280,720")
webdriver_service = Service("chromedriver/chromedriver") ## path to where you saved chromedriver binary
driver = webdriver.Chrome(service=webdriver_service, options=chrome_options)
wait = WebDriverWait(driver, 20)
url = "https://www.fantasypros.com/daily-fantasy/nba/fanduel-defense-vs-position.php"
driver.get(url)
select_recency_options = [x.text for x in wait.until(EC.presence_of_all_elements_located((By.XPATH, '//select[@class="game-change"]/option')))]
for option in select_recency_options:
select_recency = Select(WebDriverWait(driver, 20).until(EC.element_to_be_clickable((By.XPATH, '//select[@class="game-change"]'))))
select_recency.select_by_visible_text(option)
print('selected', option)
t.sleep(2)
tables_list = wait.until(EC.presence_of_all_elements_located((By.XPATH, '//ul[@class="pills pos-filter pull-left"]/li')))
for x in tables_list:
x.click()
print('selected', x.text)
t.sleep(2)
table = wait.until(EC.element_to_be_clickable((By.XPATH, '//table[@id="data-table"]')))
df = pd.read_html(table.get_attribute('outerHTML'))[0]
df['Category'] = x.text.strip()
df['Recency'] = option
big_df = pd.concat([big_df, df], axis=0, ignore_index=True)
print('done, moving to next table')
display(big_df)
big_df.to_csv('fanduel.csv')
Das Ergebnis ist ein (größerer) Datenrahmen:
Team PTS REB AST 3PM STL BLK TO FD PTS Category Recency
0 HOUHouston Rockets 23.54 9.10 5.10 2.54 1.88 1.15 2.65 48.55 ALL Season
1 OKCOklahoma City Thunder 22.22 9.61 5.19 2.70 1.67 1.18 2.52 47.57 ALL Season
2 PORPortland Trail Blazers 22.96 8.92 5.31 2.74 1.63 0.99 2.65 46.84 ALL Season
3 SACSacramento Kings 23.00 9.10 5.03 2.58 1.61 0.95 2.50 46.65 ALL Season
4 ORLOrlando Magic 22.35 9.39 4.94 2.62 1.57 1.04 2.50 46.36 ALL Season
... ... ... ... ... ... ... ... ... ... ... ...
715 TORToronto Raptors 23.33 13.97 2.77 0.57 0.84 1.88 3.38 49.03 C Last 30
716 NYKNew York Knicks 19.78 15.40 2.94 0.53 0.90 1.92 2.17 48.96 C Last 30
717 BKNBrooklyn Nets 19.69 13.60 3.16 0.86 1.10 2.25 2.06 48.74 C Last 30
718 BOSBoston Celtics 17.79 11.95 3.75 0.41 1.66 1.80 2.54 45.60 C Last 30
719 MIAMiami Heat 17.41 14.19 2.16 0.50 1.01 1.52 1.75 43.52 C Last 30
720 rows × 11 columns
Beantwortet von – Barry der Platipus
Antwort geprüft von – Terry (FixError Volunteer)
