TypeError: to_append 应该是 Series 或 Series 的列表/元组，得到 DataFrame

Posted 2023-03-11

【中文标题】TypeError: to_append 应该是 Series 或 Series 的列表/元组，得到 DataFrame

【英文标题】：TypeError: to_append should be a Series or list/tuple of Series, got DataFrame

【发布时间】：2021-07-26 05:26:28

【问题描述】：

代码在早些时候运行，然后就停止了。

我不明白为什么，如果有人可以帮助我对这个主题有所了解，那就太棒了。

import urllib.request
from bs4 import BeautifulSoup as bs
import re
import pandas as pd
import requests


locations = ['las-vegas-nv','denver-co']
for location in locations:
    headers = 
        'User-Agent' : 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (Khtml, like Gecko) Chrome/90.0.4430.93 Safari/537.36'
    



    url = f'https://www.apartments.com/location/1-bedrooms/'
    page = requests.get(url, headers=headers)
    soup = bs(page.text, 'lxml')
    table = soup.find("table", class_="rentTrendGrid")
    rows = []

    for tr in table.find_all('tr'):
        rows.append([td.text for td in tr.find_all(['th', 'td'])])

#header_row = rows[0]
    rows = list(zip(*rows[0:])) # tranpose the table
    df = pd.DataFrame(rows[1:], columns=rows[0])
    df['City'] = location
    dfs.append(df)
    df = pd.concat(dfs).reset_index(drop = True)
print(df)

【问题讨论】：

什么是dfs？我没有看到它在任何地方定义。

我只是在搞乱代码...我知道它没有定义但是当 dfs 等于 df 时它仍然会抛出相同的错误

【参考方案1】：

原来我只需要从 for 循环中取出最后一部分

import urllib.request
from bs4 import BeautifulSoup as bs
import re
import pandas as pd
import requests


locations = ['las-vegas-nv','denver-co', 'lehi-ut']

dfs = []
for location in locations:
    headers = 
        'User-Agent' : 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/90.0.4430.93 Safari/537.36'
    



    url = f'https://www.apartments.com/location/1-bedrooms/'
    page = requests.get(url, headers=headers)
    soup = bs(page.text, 'lxml')
    table = soup.find("table", class_="rentTrendGrid")
    rows = []

    for tr in table.find_all('tr'):
        rows.append([td.text for td in tr.find_all(['th', 'td'])])

#header_row = rows[0]
    rows = list(zip(*rows[0:])) # tranpose the table
    df = pd.DataFrame(rows[1:], columns=rows[0])
    df['City'] = location
    dfs.append(df)
df = pd.concat(dfs).reset_index(drop = True)
print(df)