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 csv



headers = {

    '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:

            pass



def 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

通过可视化可以看出，B的妹子是最多的，可我感觉哪里不对劲，后面再京东查看了部分商品，发现A断码或者有的商品没有A码，所以这可能导致A偏少了，扎心了，老铁。

• 购买颜色

统一进行清洗可视化，直接上图。

肤色的是最多的，大家知道原因么，嘿嘿。