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

【问题标题】：TypeError: to_append should be a Series or list/tuple of Series, got DataFrameTypeError: to_append 应该是 Series 或 Series 的列表/元组，得到 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

标签： python pandas append concatenation

【解决方案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)

【讨论】：