netkeibaの出馬表から各馬のページに遷移し
データを見比べるのが面倒なため、予想に必要な情報をcsvで出力するためのプログラムを組んでみた
書き方が汚いので改良の余地はありそう
import pandas as pd
import urllib
import requests
import re
import unicodedata
import csv

from webdriver_manager.chrome import ChromeDriverManager
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import Select
from bs4 import BeautifulSoup
from tqdm import tqdm

def main():

    site_url = input("データを取得したい出馬表のURLを入力してください(中央競馬のレースのみ対応):")
    browser = webdriver.Chrome(ChromeDriverManager().install())

    browser.get(site_url)

    browser.implicitly_wait(10) 
    link_list = []              

    link_list = make_horseURL(browser, link_list)

    df_RaceResult = pd.DataFrame()

    for url in tqdm(link_list):
    df_RaceResult = pd.concat([df_RaceResult, get_result(url)], axis=0)

    df_RaceResult.to_csv('./中間.csv', encoding='cp932', header=False, index=False, errors="ignore")

    file = open('./中間.csv',"r")
    out_file = open('./最終.csv',"w")

    lines = file.readlines()
    for line1 in lines:
        line = line1.split(',')
        if line[6] != "":
            line.pop(12)
            line.pop(16)
            line.pop(16)
        weight = line[21]
        if weight != "":
            horse_weight = re.split('[()]', weight)
            line.pop(21)
            line = line + horse_weight

        elif line[6] == "":
            line.pop(6)
            line.pop(6)
            line.pop(13)

        race_name = line[5]
        if '(' in race_name:
            grade_name = re.split('[()]', race_name)
            grade = grade_name[-2]
            line.insert(6,grade)
        else:
            line.insert(6,"")

        race_track2 = line[2]
        if "札幌" in race_track2:
            race_track = "札幌"
            line.pop(2)
            line.insert(2,race_track)
        elif "函館" in race_track2:
            race_track = "函館"
            line.pop(2)
            line.insert(2,race_track)
        elif "新潟" in race_track2:
            race_track = "新潟"
            line.pop(2)
            line.insert(2,race_track)
        elif "福島" in race_track2:
            race_track = "福島"
            line.pop(2)
            line.insert(2,race_track)
        elif "中山" in race_track2:
            race_track = "中山"
            line.pop(2)
            line.insert(2,race_track)
        elif "東京" in race_track2:
            race_track = "東京"
            line.pop(2)
            line.insert(2,race_track)
        elif "中京" in race_track2:
            race_track = "中京"
            line.pop(2)
            line.insert(2,race_track)
        elif "京都" in race_track2:
            race_track = "京都"
            line.pop(2)
            line.insert(2,race_track)
        elif "阪神" in race_track2:
            race_track = "阪神"
            line.pop(2)
            line.insert(2,race_track)
        elif "小倉" in race_track2:
            race_track = "小倉"
            line.pop(2)
            line.insert(2,race_track)


        result = ','.join(str(s) for s in line)
        out_file.write(result)

def make_horseURL(browser, link_list):
    print('取得したHTMLからレース結果のURLを抽出します')
    html = browser.page_source.encode('utf-8')      
    soup = BeautifulSoup(html, 'html.parser')       
    table_data = soup.find(class_='Shutuba_Table')  

    for element in table_data.find_all('a'):
        url = element.get('href') 

        link_url = urllib.parse.urljoin('https://db.netkeiba.com', url)

        word_list = ['jockey', 'trainer', 'popup', 'bookmark']

        tmp_list = link_url.split('/') 
        and_list = set(word_list) & set(tmp_list) 

        if len(and_list) == 0:
            link_list.append(link_url)

    return link_list


def get_result(url):
    res = requests.get(url)
    soup = BeautifulSoup(res.content, 'lxml')

    title = (soup.title.string.split(' '))
    horse_name = title[0]

    tables = soup.find('table', attrs={'class': 'db_h_race_results'})
    tables = tables.find_all('tr')

    indexs = tables[0].text.split('\n')

    tmp = []
    df = pd.DataFrame()
    df_tmp1 = pd.DataFrame()

    for table in tables[1:]:
        tmp = table.text.split('\n')
        df_tmp1 = pd.Series(tmp)
        df = pd.concat([df, df_tmp1], axis=1)

    df_tmp2 = pd.DataFrame()
    df_tmp3 = pd.DataFrame()
    for i in ( 1, 2, 3, 4, 5, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 20, 21, 22, 26, 27, 33, 34, 35, 36,):
        df_tmp2 = df.iloc[i]
        df_tmp3['馬名'] = horse_name
        df_tmp3 = pd.concat([df_tmp3, df_tmp2], axis=1)

    return df_tmp3

if __name__ == "__main__":
    main()