爬虫学习
路劲表达式
import requests
from lxml import html
import pandas as pd
from matplotlib import pyplot as plt
plt.rcParams["font.sans-serif"] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False
def spider_dangdang(isbn):
book_list = []
# 目标站点地址
url = 'http://search.dangdang.com/?key={}&act=input'.format(isbn)
# print(url)
# 获取站点str类型的响应
headers = {"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.142 Safari/537.36"}
resp = requests.get(url, headers=headers)
html_data = resp.text
# 将html页面写入本地
# with open('dangdang.html', 'w', encoding='utf-8') as f:
# f.write(html_data)
# 提取目标站的信息
selector = html.fromstring(html_data)
ul_list = selector.xpath('//div[@id="search_nature_rg"]/ul/li')
print('您好,共有{}家店铺售卖此图书'.format(len(ul_list)))
# 遍历 ul_list
for li in ul_list:
# 图书名称
title = li.xpath('./a/@title')[0].strip()
# print(title)
# 图书购买链接
link = li.xpath('a/@href')[0]
# print(link)
# 图书价格
price = li.xpath('./p[@class="price"]/span[@class="search_now_price"]/text()')[0]
price = float(price.replace('¥',''))
# print(price)
# 图书卖家名称
store = li.xpath('./p[@class="search_shangjia"]/a/text()')
# if len(store) == 0:
# store = '当当自营'
# else:
# store = store[0]
store = '当当自营' if len(store) == 0 else store[0]
# print(store)
# 添加每一个商家的图书信息
book_list.append({
'title':title,
'price':price,
'link':link,
'store':store
})
# 按照价格进行排序
book_list.sort(key=lambda x:x['price'])
# 遍历booklist
for book in book_list:
print(book)
# 展示价格最低的前10家 柱状图
# 店铺的名称
top10_store = [book_list[i] for i in range(10)]
# x = []
# for store in top10_store:
# x.append(store['store'])
x = [x['store'] for x in top10_store]
print(x)
# 图书的价格
y = [x['price'] for x in top10_store]
print(y)
# plt.bar(x, y)
plt.barh(x, y)
plt.show()
# 存储成csv文件
df = pd.DataFrame(book_list)
df.to_csv('dangdang.csv')
实战演示
import requests
from lxml import html
import pandas as pd
from matplotlib import pyplot as plt
plt.rcParams["font.sans-serif"] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False
def spider_dianying():
film_list = []
url = 'https://movie.douban.com/cinema/later/chongqing/'
print(url)
headers = {"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.142 Safari/537.36"}
resp = requests.get(url, headers=headers)
html_data = resp.text
with open('dianying.html', 'w', encoding='utf-8') as f:
f.write(html_data)
selector = html.fromstring(html_data)
ul_list = selector.xpath('//div[@id="showing-soon"]/div')
print('即将上映的电影'.format(len(ul_list)))
for li in ul_list:
title=li.xpath('./div/h3/a/text()')[0]
#日期
date=li.xpath('./div/ul/li[1]/text()')[0]
type=li.xpath('./div/ul/li[2]/text()')[0]
country=li.xpath('./div/ul/li[3]/text()')[0]
number=li.xpath('./div/ul/li[4]/span/text()')[0]
number=int(number.replace("人想看",""))
film_list.append({
'title': title,
'date': date,
'type': type,
'country':country,
'number':number
})
film_list.sort(key=lambda x: x['number'],reverse=True)
counts = {}
for movie in film_list:
counts[movie['country']] = counts.get(movie['country'], 0) + 1
countrys = []
countrys_count = []
for k, v in counts.items():
countrys.append(k)
countrys_count.append(v)
plt.pie(countrys_count, labels=countrys, autopct='%1.1f%%')
plt.show()
for book in film_list:
print(book)
# 展示最多的前5名电影 柱状图
# 电影的名称
top5_store = [film_list[i] for i in range(5)]
# x = []
# for store in top10_store:
# x.append(store['store'])
x = [x['title'] for x in top5_store]
print(x)
# 电影人数
y = [x['number'] for x in top5_store]
print(y)
# plt.bar(x, y)
plt.barh(x, y)
plt.show()
spider_dianying()//调用方法
柱状图
饼图
![4HIAZ4$0[]]KR@HBCC)L7D.png