济宁市房价数据集爬取代码
时间: 2023-11-14 07:00:25 浏览: 35
以下是使用Python爬取济宁市房价数据集的示例代码。
首先,我们需要导入必要的库:
```python
import requests
from bs4 import BeautifulSoup
import csv
```
然后,我们需要定义我们要爬取的页面URL和文件路径:
```python
url = "https://jining.anjuke.com/sale/"
file_path = "jining_house_prices.csv"
```
接下来,我们需要发送一个HTTP请求来获取页面内容,并使用BeautifulSoup库来解析HTML:
```python
response = requests.get(url)
soup = BeautifulSoup(response.content, "html.parser")
```
我们可以使用开发者工具来查看页面的HTML结构,以便我们定位页面上的房价数据。在此示例中,我们将使用以下代码来定位房价信息:
```python
house_items = soup.find_all("div", class_="house-details")
```
最后,我们可以将爬取的数据保存到CSV文件中:
```python
with open(file_path, mode="w", newline="") as file:
writer = csv.writer(file)
writer.writerow(["Title", "Location", "Price"])
for item in house_items:
title = item.find("a", class_="houseListTitle").get_text().strip()
location = item.find("div", class_="details-item").get_text().strip()
price = item.find("span", class_="price-det").get_text().strip()
writer.writerow([title, location, price])
```
完整的爬取代码如下:
```python
import requests
from bs4 import BeautifulSoup
import csv
url = "https://jining.anjuke.com/sale/"
file_path = "jining_house_prices.csv"
response = requests.get(url)
soup = BeautifulSoup(response.content, "html.parser")
house_items = soup.find_all("div", class_="house-details")
with open(file_path, mode="w", newline="") as file:
writer = csv.writer(file)
writer.writerow(["Title", "Location", "Price"])
for item in house_items:
title = item.find("a", class_="houseListTitle").get_text().strip()
location = item.find("div", class_="details-item").get_text().strip()
price = item.find("span", class_="price-det").get_text().strip()
writer.writerow([title, location, price])
```
请注意,本示例仅仅是一个入门级的爬虫示例,仅仅是为了演示如何使用Python爬取网页数据。在实际使用中,我们需要更加严谨和谨慎地处理爬取数据的问题,以避免违反相关法律法规和网站的使用协议。