Pycharm爬取数据时，索引出错，报错keyerror,请问应该怎么重置？

代码：

# _*_ coding=utf-8 _*_
import requests as rq
from bs4 import BeautifulSoup
import pandas as pd
import numpy as np
import time
import concurrent.futures
from multiprocessing.dummy import Pool as pool

limit = 10000  # 热门歌单播放量筛选下限
headers = {
    'Referer': 'http://music.163.com/',
    'Host': 'music.163.com',
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/62.0.3202.75 Safari/537.36',
    'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8'
}
headers1 = {
    'Referer': 'http://music.163.com/',
    'Host': 'music.163.com',
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/62.0.3202.75 Safari/537.36',
    'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.9'
}
finallist = []
url_list = []
count = 0
LABEL = '网易云音乐-爬取歌单数据'


def getHTMLText(url, headers):  # 通用的获取网站内容的框架
    try:
        r = rq.get(url, headers=headers)
        r.raise_for_status()
        r.encoding = r.apparent_encoding
        return r.text
    except:
        return "网络解析错误"


def get_url(cat, depth):  # 获取首页该分类下面的歌单url，形成url_list
    depth = 1
    start_url = 'https://music.163.com/discover/playlist/?order=hot&cat=' + cat
    for i in range(depth):
        try:
            url = start_url + '&limit=35' + '&offset=' + str(35 * (i + 1))
            html = getHTMLText(url, headers)
            parse_main(html)
        except:
            print('失败')
            continue


def parse_main(html):  # 解析单个url
    soup = BeautifulSoup(html, 'html.parser')
    c = soup.find_all('li')
    for unit in c:
        try:
            name_url = unit.find('a', {'class': "tit f-thide s-fc0"})  # m这里有URL，名字的信息
            number = eval(unit.find('span', {'class': 'nb'}).text.replace('万', '0000'))  # 这里获取的是播放量的信息,用于初步筛选
            list1 = [name_url['title'].replace(u'\xa0', u' '), number, name_url['href']]
            url_list.append(list1)
        except:
            continue


def parse_single(listid):  # 进入歌单内部解析，获取播放量，收藏量，标签等信息
    global count
    count += 1
    # print(count)
    # print('\0')
    singleurl = 'https://music.163.com' + listid
    # print(singleurl)
    # print('\0')
    singletext = getHTMLText(singleurl, headers=headers1)
    # print("**")
    soup = BeautifulSoup(singletext, 'html.parser')
    try:
        play_count = eval(soup.find('strong', {'class': 's-fc6'}).text)
        fav = soup.find('a', {'class': 'u-btni u-btni-fav'}).i.text.strip('(').strip(')')
        if ('万') in fav:
            fav = eval(fav.replace('万', '0000'))
        share = eval(soup.find('a', {'class': 'u-btni u-btni-share'}).i.text.strip('(').strip(')'))
        comment = eval(soup.find('a', {'data-res-action': 'comment'}).i.span.text)
        length = eval(soup.find('span', {'id': 'playlist-track-count'}).text)
        date = soup.find('span', {'class': 'time s-fc4'}).text[:10]
        name = soup.find('h2', {"class": 'f-ff2 f-brk'}).text.replace(u'\xa0', u' ')
        tags = soup.find_all('a', {'class': 'u-tag'})
        p = len(tags)
        tag1 = 'nan'
        tag2 = 'nan'
        tag3 = 'nan'
        if p >= 1:
            tag1 = tags[0].text.replace(u'\xa0', u' ')
        if p >= 2:
            tag2 = tags[1].text.replace(u'\xa0', u' ')
        if p == 3:
            tag3 = tags[2].text.replace(u'\xa0', u' ')
        list1 = [name, date, play_count, fav, share, comment, length, tag1, tag2, tag3]
        finallist.append(list1)
        print('解析第{}个歌单成功'.format(count))
    except:
        print('解析第{}个歌单失败'.format(count))
        return


def main(type, depth=38):
    get_url(type, depth=depth)
    print("歌单列表获取完成")
    print(url_list)
    a = pd.DataFrame(url_list)
    b = list(a[2])
    with concurrent.futures.ThreadPoolExecutor() as executor:
        executor.map(parse_single, b)
    # 多线程
    print(finallist)
    a = pd.DataFrame(finallist)
    b = pd.DataFrame(url_list)
    title_list = ['名称', '创建日期', '播放次数', '收藏量', '转发量', '评论数', '歌单长度', 'tag1', 'tag2', 'tag3']
    c = pd.Series(title_list)
    a.columns = c
    a.to_excel(r'C:\Users\YTRoski2\Desktop\毕业论文\{}.xlsx'.format(type))
    # 数据输出到Excel


main(LABEL, depth=5)
# depth就是总共爬取多少页的，打开网站可以发现每页上有30多个，总共有38页。

报错：

Traceback (most recent call last):
  File "C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexes\base.py", line 2895, in get_loc
    return self._engine.get_loc(casted_key)
  File "pandas\_libs\index.pyx", line 70, in pandas._libs.index.IndexEngine.get_loc
歌单列表获取完成
[]
  File "pandas\_libs\index.pyx", line 101, in pandas._libs.index.IndexEngine.get_loc
  File "pandas\_libs\hashtable_class_helper.pxi", line 1675, in pandas._libs.hashtable.PyObjectHashTable.get_item
  File "pandas\_libs\hashtable_class_helper.pxi", line 1683, in pandas._libs.hashtable.PyObjectHashTable.get_item
KeyError: 2

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "C:/Users/YTRoski2/PycharmProjects/Scrapy/scrapy_first/download_playlist/music163.py", line 124, in <module>
    main(LABEL, depth=5)
  File "C:/Users/YTRoski2/PycharmProjects/Scrapy/scrapy_first/download_playlist/music163.py", line 110, in main
    b = list(a[2])
  File "C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\frame.py", line 2902, in __getitem__
    indexer = self.columns.get_loc(key)
  File "C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexes\base.py", line 2897, in get_loc
    raise KeyError(key) from err
KeyError: 2

这是因为a是DataFrame数据类型，它在行/列选取时不支持a[2]的取法，若需要提取第二行的数据，可以通过DataFrame的iloc语法来实现

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