我用 Python 分析了一波热卖年货，原来大家都在买这些东西？

pip install selenium

# coding=utf8import refrom selenium.webdriver.chrome.options import Optionsfrom selenium import webdriverimport timeimport csv

# 搜索商品，获取商品页码def search_product(key_word):    # 定位输入框    browser.find_element_by_id("q").send_keys(key_word)    # 定义点击按钮，并点击    browser.find_element_by_class_name('btn-search').click()    # 最大化窗口：为了方便我们扫码    browser.maximize_window()    # 等待15秒，给足时间我们扫码    time.sleep(15)    # 定位这个“页码”，获取“共100页这个文本”    page_info = browser.find_element_by_xpath('//div[@class="total"]').text    # 需要注意的是：findall()返回的是一个列表，虽然此时只有一个元素它也是一个列表。    page = re.findall("(\d+)", page_info)[0]    return page

# 获取数据def get_data():    # 通过页面分析发现：所有的信息都在items节点下    items = browser.find_elements_by_xpath('//div[@class="items"]/div[@class="item J_MouserOnverReq  "]')    for item in items:        # 参数信息        pro_desc = item.find_element_by_xpath('.//div[@class="row row-2 title"]/a').text        # 价格        pro_price = item.find_element_by_xpath('.//strong').text        # 付款人数        buy_num = item.find_element_by_xpath('.//div[@class="deal-cnt"]').text        # 旗舰店        shop = item.find_element_by_xpath('.//div[@class="shop"]/a').text        # 发货地        address = item.find_element_by_xpath('.//div[@class="location"]').text        # print(pro_desc, pro_price, buy_num, shop, address)        with open('{}.csv'.format(key_word), mode='a', newline='', encoding='utf-8-sig') as f:            csv_writer = csv.writer(f, delimiter=',')            csv_writer.writerow([pro_desc, pro_price, buy_num, shop, address])

def main():    browser.get('https://www.taobao.com/')    page = search_product(key_word)    print(page)    get_data()    page_num = 1    while int(page) != page_num:        print("*" * 100)        print("正在爬取第{}页".format(page_num + 1))        browser.get('https://s.taobao.com/search?q={}&s={}'.format(key_word, page_num * 44))        browser.implicitly_wait(25)        get_data()        page_num += 1    print("数据爬取完毕！")

if __name__ == '__main__':    key_word = input("请输入你要搜索的商品：")    option = Options()    browser = webdriver.Chrome(chrome_options=option,                               executable_path=r"C:\Users\cherich\AppData\Local\Google\Chrome\Application\chromedriver.exe")    main()

import pandas as pdimport matplotlib as mplmpl.rcParams['font.family'] = 'SimHei'from wordcloud import WordCloudfrom ast import literal_evalimport matplotlib.pyplot as pltdatas = pd.read_csv('./年货.csv',encoding='gbk')datas

li = []for each in datas['关键词'].values:    new_list = str(each).split(',')    li.extend(new_list)def func_pd(words):    count_result = pd.Series(words).value_counts()    return count_result.to_dict()
frequencies = func_pd(li)frequencies.pop('其他')
plt.figure(figsize = (10,4),dpi=80)wordcloud = WordCloud(font_path="STSONG.TTF",background_color='white', width=700,height=350).fit_words(frequencies)plt.imshow(wordcloud)plt.axis("off")plt.show()

# plt.pie(x,lables,autopct,shadow,startangle,colors,explode)food_type = datas.groupby('价格区间').size()plt.figure(figsize=(8,4),dpi=80)explodes= [0,0,0,0,0.2,0.1]size = 0.3plt.pie(food_type, radius=1,labels=food_type.index, autopct='%.2f%%', colors=['#F4A460','#D2691E','#CDCD00','#FFD700','#EEE5DE'],       wedgeprops=dict(width=size, edgecolor='w'))plt.title('年货价格区间占比情况',fontsize=18)plt.legend(food_type.index,bbox_to_anchor=(1.5, 1.0))plt.show()

foods = datas.groupby(by='类别')['销量'].sum().sort_values(ascending=False).head(10)foods.sort_values(ascending=True,inplace=True)plt.figure(figsize = (10,4),dpi=80)plt.xlabel('销量')plt.title('年货推荐购买排行榜',fontsize=18)colors = ['#F4A460','#D2691E','#CDCD00','#CD96CD','#EEE5DE', '#EEB4B4', '#FFA07A', '#FFD700']plt.barh(foods.index,foods.values, color=colors,height=1)plt.show()