Python是一種流行的編程語言，它擁有強大的數據處理能力和靈活的編程方式。Python可以輕松完成爬取數據的操作，比如抓取省市區數據。

import requests
from bs4 import BeautifulSoup
url = 'http://www.stats.gov.cn/tjsj/tjbz/tjyqhdmhcxhfdm/2019/'
response = requests.get(url)
response.encoding = 'gbk'
soup = BeautifulSoup(response.text, 'html.parser')
provinces = soup.select('tr.provincetr td a')
for p in provinces:
province_url = url + p['href']
province_code = p.get_text()
province_response = requests.get(province_url)
province_response.encoding = 'gbk'
province_soup = BeautifulSoup(province_response.text, 'html.parser')
cities = province_soup.select('tr.citytr')
for c in cities:
city_code = c.select('td')[0].get_text()
city_name = c.select('td')[1].get_text()
city_url = province_url.rsplit('/', maxsplit=1)[0] + '/' + city_code + '.html'
city_response = requests.get(city_url)
city_response.encoding = 'gbk'
city_soup = BeautifulSoup(city_response.text, 'html.parser')
areas = city_soup.select('tr.countytr')
for a in areas:
area_code = a.select('td')[0].get_text()
area_name = a.select('td')[1].get_text()
print(province_code, city_code, area_code, area_name)

以上代碼使用了第三方庫requests和beautifulsoup4。首先，我們通過requests.get方法獲取網頁內容，并指定編碼方式為gbk。然后，使用BeautifulSoup解析網頁內容。soup.select方法可以選擇頁面中的元素，類似于CSS選擇器。接著，我們進一步抓取每個城市和區的網頁鏈接并解析出相應的數據。

最終，我們可以得到每個省市區的代碼和名稱。