我正在从已发布的属性列表中抓取信息。当尝试将此数据导出到CSV文件时，我遇到一个错误，

'All arrays must be of the same length.'

字符串
这是因为并非所有属性都包含我提取的相同信息。
因此，列在所有行中的数据量并不相同。我需要帮助来处理这种情况并完成代码，以便将缺少某些信息的产品填充为空值。您可以帮助我吗？

# Instalar las bibliotecas necesarias si no están instaladas
!pip install requests
!pip install beautifulsoup4
!pip install pandas

# Importar las bibliotecas
import requests
from bs4 import BeautifulSoup
import pandas as pd
from lxml import etree

link = 'https://listado.mercadolibre.cl/inmuebles/departamentos/venta/propiedades-usadas/_NoIndex_True#applied_filter_id%3DOPERATION_SUBTYPE%26applied_filter_name%3DModalidad%26applied_filter_order%3D5%26applied_value_id%3D244562%26applied_value_name%3DPropiedades+usadas%26applied_value_order%3D1%26applied_value_results%3D68139%26is_custom%3Dfalse'

r = requests.get(link)

r.status_code

soup = BeautifulSoup(r.content, 'html.parser')

dom=etree.HTML(str(soup))

titulos = soup.find_all('h2', attrs={"class":"ui-search-item__title"})
titulos = [i.text for i in titulos]

urls = soup.find_all('div',attrs={"class":"ui-search-item__group__element ui-search-item__title-grid"})
urls = [item.find('a')['href'] for item in urls]

moneda = soup.find_all('span', attrs={"class":"andes-money-amount__currency-symbol"})
moneda = [i.text for i in moneda]

precio = soup.find_all('span', attrs={"class":"andes-money-amount__fraction"})
precio = [i.text for i in precio]

dormitorio = dom.xpath('//div[@class="ui-search-item__attributes-container-grid"]/ul/li[contains(normalize-space(.), "dormitorios")]')
dormitorio = [i.text for i in dormitorio]

baño = dom.xpath('//div[@class="ui-search-item__attributes-container-grid"]/ul/li[contains(normalize-space(.), "baño")]')
baño = [i.text for i in baño]

m2 = dom.xpath('//div[@class="ui-search-item__attributes-container-grid"]/ul/li[contains(normalize-space(.), "m²")]')
m2 = [i.text for i in m2]

locacion = soup.find_all('span',attrs={"class":"ui-search-item__location-label"})
locacion = [i.text for i in locacion]

vendedor = soup.find_all('div',attrs={"class":"ui-search-item__official-store-grid"})
vendedor = [i.text for i in vendedor]
vendedor

# df = pd.DataFrame({"titulos" :titulos, "urs" :urls})

# df.to_csv('Ejemplo')

siguiente = dom.xpath('//div[@class="ui-search-pagination"]/nav/ul/li[contains(@class,"--next")]/a')[0].get('href')

ini = soup.find('span',attrs={"class":"andes-pagination__link"}).text
ini = int(ini)

can = soup.find('li',attrs={"class":"andes-pagination__page-count"})
can = int(can.text.split(" ")[1])

lista_titulos = []
lista_urls = []
lista_dormitorio = []
lista_baño = []
lista_m2 = []
lista_moneda = []
lista_precio = []
lista_vendedor = []
lista_locacion = []

siguiente = link
while True:
    r = requests.get(siguiente)
    if r.status_code == 200:
        soup = BeautifulSoup(r.content, 'html.parser')

        #titulos
        titulos = soup.find_all('h2', attrs={"class":"ui-search-item__title"})
        titulos = [i.text for i in titulos]
        lista_titulos.extend(titulos)

        #urls
        urls = soup.find_all('div',attrs={"class":"ui-search-item__group__element ui-search-item__title-grid"})
        urls = [item.find('a')['href'] for item in urls]
        lista_urls.extend(urls)

        #moneda
        moneda = soup.find_all('span', attrs={"class":"andes-money-amount__currency-symbol"})
        moneda = [i.text for i in moneda]
        lista_moneda.extend(moneda)

        #precio
        precio = soup.find_all('span', attrs={"class":"andes-money-amount__fraction"})
        precio = [i.text for i in precio]
        lista_precio.extend(precio)

        #dormitorios
        dormitorio = dom.xpath('//div[@class="ui-search-item__attributes-container-grid"]/ul/li[contains(normalize-space(.), "dormitorios")]')
        dormitorio = [i.text for i in dormitorio]
        lista_dormitorio.extend(dormitorio)

        #baños
        baño = dom.xpath('//div[@class="ui-search-item__attributes-container-grid"]/ul/li[contains(normalize-space(.), "baño")]')
        baño = [i.text for i in baño]
        lista_baño.extend(baño)

        #m2
        m2 = dom.xpath('//div[@class="ui-search-item__attributes-container-grid"]/ul/li[contains(normalize-space(.), "m²")]')
        m2 = [i.text for i in m2]
        lista_m2.extend(m2)

        #vendedor
        vendedor = soup.find_all('div',attrs={"class":"ui-search-item__official-store-grid"})
        vendedor = [i.text for i in vendedor]
        lista_vendedor.extend(vendedor)

        #locacion
        locacion = soup.find_all('span',attrs={"class":"ui-search-item__location-label"})
        locacion = [i.text for i in locacion]
        lista_locacion.extend(locacion)

        #inicial
        ini = soup.find('span',attrs={"class":"andes-pagination__link"}).text
        ini = int(ini)

        #cantidad
        dom=etree.HTML(str(soup))
        can = soup.find('li',attrs={"class":"andes-pagination__page-count"})
        can = int(can.text.split(" ")[1])

    else:
          break
    print(ini,can)
    if ini==can:
          break
    siguiente = dom.xpath('//div[@class="ui-search-pagination"]/nav/ul/li[contains(@class,"--next")]/a')[0].get('href')

print(len(lista_titulos))
print(len(lista_urls))
print(len(lista_dormitorio))
print(len(lista_baño))
print(len(lista_m2))
print(len(lista_locacion))
print(len(lista_vendedor))

df = pd.DataFrame({"titulos" :lista_titulos, "url" :lista_urls, "moneda" :lista_moneda, "precio" :lista_precio, "dormitorios" :lista_dormitorio, "baños" :lista_baño, "m2" :lista_m2})
df.to_csv('Venta_Departamentos_Usados_MasRelevantes')

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