京东文胸爬虫及数据分析

本文主要是介绍京东文胸爬虫及数据分析，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！

许久不来写文章了，最近夏令营搞的确实没时间。这次把上次直播讲的东西写成文字，带大家开波车。

爬虫代码

import requests
from lxml import etree
import time
import json
import re
import csvheaders = {'Cookie':'ipLoc-djd=1-72-2799-0; unpl=V2_ZzNtbRZXF0dwChEEfxtbV2IKFQ4RUBcSdg1PVSgZCVAyCkBVclRCFXMUR1NnGFkUZgoZXkpcQxNFCHZXchBYAWcCGllyBBNNIEwHDCRSBUE3XHxcFVUWF3RaTwEoSVoAYwtBDkZUFBYhW0IAKElVVTUFR21yVEMldQl2VH4RWAVmBxVeS19AEHUJR1x6GFsBYQEibUVncyVyDkBQehFsBFcCIh8WC0QcdQ1GUTYZWQ1jAxNZRVRKHXYNRlV6EV0EYAcUX3JWcxY%3d; __jdv=122270672|baidu-pinzhuan|t_288551095_baidupinzhuan|cpc|0f3d30c8dba7459bb52f2eb5eba8ac7d_0_e1ec43fa536c486bb6e62480b1ddd8c9|1496536177759; mt_xid=V2_52007VwMXWllYU14YShBUBmIDE1NVWVNdG08bbFZiURQBWgxaRkhKEQgZYgNFV0FRVFtIVUlbV2FTRgJcWVNcSHkaXQVhHxNVQVlXSx5BEl0DbAMaYl9oUmofSB9eB2YGElBtWFdcGA%3D%3D; __jda=122270672.14951056289241009006573.1495105629.1496491774.1496535400.5; __jdb=122270672.26.14951056289241009006573|5.1496535400; __jdc=122270672; 3AB9D23F7A4B3C9B=EJMY3ATK7HCS7VQQNJETFIMV7BZ5NCCCCSWL3UZVSJBDWJP3REWXTFXZ7O2CDKMGP6JJK7E5G4XXBH7UA32GN7EVRY; __jdu=14951056289241009006573','User-Agent':'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/57.0.2987.133 Safari/537.36'
}fp = open('C:/Users/luopan/Desktop/wenxiong1.csv','wt',newline='',encoding='utf-8')
writer = csv.writer(fp)
writer.writerow(('content','creationTime','productColor','productSize','userClientShow','userLevelName'))def get_id(url):html = requests.get(url, headers=headers)selector = etree.HTML(html.text)infos = selector.xpath('//ul[@class="gl-warp clearfix"]/li')for info in infos:try:id = info.xpath('@data-sku')[0]comment_url = 'https://sclub.jd.com/comment/productPageComments.action?callback=fetchJSON_comment98vv6&productId={}&score=0&sortType=5&page=0&pageSize=10&isShadowSku=0&fold=1'.format(id)get_comment_info(comment_url,id)except IndexError:passdef get_comment_info(url,id):html = requests.get(url,headers=headers)t = re.findall('fetchJSON_comment98vv6\((.*)\);', html.text)json_data = json.loads(t[0])page = json_data['maxPage']urls = ['https://sclub.jd.com/comment/productPageComments.action?callback=fetchJSON_comment98vv6&productId=%s&score=0&sortType=5&page={}&pageSize=10&isShadowSku=0&fold=1'.format(str(i)) for i in range(0,int(page))]for path in urls:html1 = requests.get(path%id, headers=headers)t1 = re.findall('fetchJSON_comment98vv6\((.*)\);', html1.text)json_data = json.loads(t1[0])for comment in json_data['comments']:content = comment['content']creationTime = comment['creationTime']productColor = comment['productColor']productSize = comment['productSize']userClientShow = comment['userClientShow']userLevelName = comment['userLevelName']# print(content,creationTime,productColor,productSize,userClientShow,userLevelName)writer.writerow((content,creationTime,productColor,productSize,userClientShow,userLevelName))time.sleep(2)if __name__ == '__main__':url = 'https://search.jd.com/Search?keyword=%E6%96%87%E8%83%B8&enc=utf-8&qrst=1&rt=1&stop=1&vt=2&suggest=1.his.0.0&page=1&s=1&click=0'get_id(url)

数据分析

首先导入相应的库文件和读入数据。

import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
from pylab import *  
mpl.rcParams['font.sans-serif'] = ['SimHei'] 
mpl.rcParams['axes.unicode_minus'] = False
bra = pd.read_csv(open(r'C:\Users\luopan\Desktop\wenxiong1.csv'))
bra

老司机大概感兴趣的就是文胸尺寸、颜色、和购买的时间，我们对这些列数据进行简单的清洗，以便之后的可视化。

购买时间
通过describe可以看到购买时间是字符的格式，我们需要把它进行数据格式的转化。具体代码如下。

bra['creationTime'] = pd.to_datetime(bra['creationTime'])
bra['hour'] = [i.hour for i in bra['creationTime']]
bra

我们提取购买的时间。通过可视化表现出来。

hour = bra.groupby('hour').size()
plt.xlim(0,25)
plt.plot(hour,linestyle='solid',color='royalblue',marker='8')

通过图可以看出妹子们都喜欢10点后购买文胸，刚上会班，就开始“不务正业”了。

罩杯情况
首先通过unique方法，看看有哪些罩杯.....

bra.productSize.unique()

对于广大男同胞来说，这些看着头都晕，我们需要通过python进行数据的清洗，把它弄成ABCDE，嘿嘿。

cup = bra.productSize.str.findall('[a-zA-Z]+').str[0]
cup2 = cup.str.replace('M','B')
cup3 = cup2.str.replace('L','C')
cup4 = cup3.str.replace('XC','D')
bra['cup'] = cup4
bra