vote_fox.py

import bs4
import requests
import pandas as pd

def scrape(state):
    soup = bs4.BeautifulSoup(requests.get(f"https://www.foxnews.com/elections/2020/general-results/state/{state}").content.decode("utf-8"))
    section = soup.find_all("section", class_="is-president")[0]
    section = section.find_all("div", class_="race-table")[0]
    tables = section.find_all("table")
    
    results = []
    for table in tables:
        county = table.find_all("span", class_="county")[0].decode_contents().strip()
        candidates = table.find_all("tr", class_="candidate")

        result = {"state": state, "county": county}
        for candidate in candidates:
            name = candidate.find_all("span", class_="is-short")[0].decode_contents().strip()
            count = int(candidate.find_all("span", class_="count")[0].decode_contents().strip().replace(",", ""))
            result[name] = count

        result["percent"] = float(table.find_all("span", class_="percent-in")[0].decode_contents().strip().replace("Reporting ", "").replace("% in", ""))
        results.append(result)
    
    return pd.DataFrame(results)
  
def margin(df):
    votes = df.drop(labels=["state", "county", "percent"], axis=1)
    df["current"] = votes.sum(axis=1)
    df["final"] = df.current / df.percent * 100
    for candidate in votes.columns:
        df[candidate] *= (df.final / df.current)
        
    return df.drop(labels=["state", "county", "percent", "current", "final"], axis=1).sum()