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# %load doc2ver.py
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import re
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import pandas
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import requests
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from bs4 import BeautifulSoup
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import matplotlib.pyplot as plt
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from matplotlib import font_manager
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def get_html(url):
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try:
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r = requests.get(url) # 使用get来获取网页数据
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r.raise_for_status() # 如果返回参数不为200，抛出异常
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r.encoding = r.apparent_encoding # 获取网页编码方式
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return r.text # 返回获取的内容
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except:
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return '错误'
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def save(html):
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# 解析网页
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soup = BeautifulSoup(html, 'html.parser') # 指定Beautiful的解析器为“html.parser”
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with open('./data/B_data.txt', 'r+', encoding='UTF-8') as f:
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f.write(soup.text)
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# 定义好相关列表准备存储相关信息
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TScore = [] # 综合评分
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name = [] # 动漫名字
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bfl = [] # 播放量
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pls = [] # 评论数
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scs = [] # 收藏数
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# ******************************************** 动漫名字存储
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for tag in soup.find_all('div', class_='info'):
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# print(tag)
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bf = tag.a.string
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name.append(str(bf))
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print(name)
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# ******************************************** 播放量存储
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for tag in soup.find_all('div', class_='detail'):
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# print(tag)
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bf = tag.find('span', class_='data-box').get_text()
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# 统一单位为‘万’
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if '亿' in bf:
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num = float(re.search(r'\d(.\d)?', bf).group()) * 10000
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# print(num)
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bf = num
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else:
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bf = re.search(r'\d*(\.)?\d', bf).group()
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bfl.append(float(bf))
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print(bfl)
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# ******************************************** 评论数存储
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for tag in soup.find_all('div', class_='detail'):
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# pl = tag.span.next_sibling.next_sibling
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pl = tag.find('span', class_='data-box').next_sibling.next_sibling.get_text()
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# *********统一单位
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if '万' not in pl:
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pl = '%.1f' % (float(pl) / 10000)
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# print(123, pl)
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else:
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pl = re.search(r'\d*(\.)?\d', pl).group()
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pls.append(float(pl))
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print(pls)
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# ******************************************** 收藏数
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for tag in soup.find_all('div', class_='detail'):
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sc = tag.find('span', class_='data-box').next_sibling.next_sibling.next_sibling.next_sibling.get_text()
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sc = re.search(r'\d*(\.)?\d', sc).group()
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scs.append(float(sc))
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print(scs)
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# ******************************************** 综合评分
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for tag in soup.find_all('div', class_='pts'):
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zh = tag.find('div').get_text()
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TScore.append(int(zh))
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print('综合评分', TScore)
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# 存储至excel表格中
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info = {'动漫名': name, '播放量(万)': bfl, '评论数(万)': pls, '收藏数(万)': scs, '综合评分': TScore}
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dm_file = pandas.DataFrame(info)
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dm_file.to_excel('Dongman.xlsx', sheet_name="动漫数据分析")
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# 将所有列表返回
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return name, bfl, pls, scs, TScore
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def view(info):
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my_font = font_manager.FontProperties(fname='./data/STHeiti Medium.ttc') # 设置中文字体（图标中能显示中文）
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dm_name = info[0] # 番剧名
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dm_play = info[1] # 番剧播放量
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dm_review = info[2] # 番剧评论数
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dm_favorite = info[3] # 番剧收藏数
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dm_com_score = info[4] # 番剧综合评分
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# print(dm_com_score)
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# 为了坐标轴上能显示中文
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plt.rcParams['font.sans-serif'] = ['SimHei']
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plt.rcParams['axes.unicode_minus'] = False
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# **********************************************************************综合评分和播放量对比
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# *******综合评分条形图
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fig, ax1 = plt.subplots()
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plt.bar(dm_name, dm_com_score, color='red') #设置柱状图
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plt.title('综合评分和播放量数据分析', fontproperties=my_font) # 表标题
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ax1.tick_params(labelsize=6)
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plt.xlabel('番剧名') # 横轴名
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plt.ylabel('综合评分') # 纵轴名
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plt.xticks(rotation=90, color='green') # 设置横坐标变量名旋转度数和颜色
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# *******播放量折线图
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ax2 = ax1.twinx() # 组合图必须加这个
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ax2.plot(dm_play, color='cyan') # 设置线粗细，节点样式
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plt.ylabel('播放量') # y轴
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plt.plot(1, label='综合评分', color="red", linewidth=5.0) # 图例
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plt.plot(1, label='播放量', color="cyan", linewidth=1.0, linestyle="-") # 图例
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plt.legend()
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plt.savefig(r'E:1.png', dpi=1000, bbox_inches='tight') #保存至本地
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# plt.show()
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# **********************************************************************评论数和收藏数对比
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# ********评论数条形图
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fig, ax3 = plt.subplots()
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plt.bar(dm_name, dm_review, color='green')
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plt.title('番剧评论数和收藏数分析')
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plt.ylabel('评论数（万）')
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ax3.tick_params(labelsize=6)
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plt.xticks(rotation=90, color='green')
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# *******收藏数折线图
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ax4 = ax3.twinx() # 组合图必须加这个
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ax4.plot(dm_favorite, color='yellow') # 设置线粗细，节点样式
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plt.ylabel('收藏数（万）')
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plt.plot(1, label='评论数', color="green", linewidth=5.0)
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plt.plot(1, label='收藏数', color="yellow", linewidth=1.0, linestyle="-")
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plt.legend()
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plt.savefig(r'E:2.png', dpi=1000, bbox_inches='tight')
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# **********************************************************************综合评分和收藏数对比
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# *******综合评分条形图
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fig, ax5 = plt.subplots()
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plt.bar(dm_name, dm_com_score, color='red')
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plt.title('综合评分和收藏数量数据分析')
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plt.ylabel('综合评分')
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ax5.tick_params(labelsize=6)
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plt.xticks(rotation=90, color='green')
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# *******收藏折线图
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ax6 = ax5.twinx() # 组合图必须加这个
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ax6.plot(dm_favorite, color='yellow') # 设置线粗细，节点样式
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plt.ylabel('收藏数（万）')
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plt.plot(1, label='综合评分', color="red", linewidth=5.0)
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plt.plot(1, label='收藏数', color="yellow", linewidth=1.0, linestyle="-")
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plt.legend()
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plt.savefig(r'E:3.png', dpi=1000, bbox_inches='tight')
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# **********************************************************************播放量和评论数对比
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# *******播放量条形图
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fig, ax7 = plt.subplots()
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plt.bar(dm_name, dm_play, color='cyan')
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plt.title('播放量和评论数 数据分析')
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plt.ylabel('播放量（万）')
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ax7.tick_params(labelsize=6)
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plt.xticks(rotation=90, color='green')
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# *******评论数折线图
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ax8 = ax7.twinx() # 组合图必须加这个
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ax8.plot(dm_review, color='green') # 设置线粗细，节点样式
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plt.ylabel('评论数（万）')
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plt.plot(1, label='播放量', color="cyan", linewidth=5.0)
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plt.plot(1, label='评论数', color="green", linewidth=1.0, linestyle="-")
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plt.legend()
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plt.savefig(r'E:4.png', dpi=1000, bbox_inches='tight')
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plt.show()
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def main():
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url = 'https://www.bilibili.com/v/popular/rank/bangumi' # 网址
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html = get_html(url) # 获取返回值
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# print(html)
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info = save(html)
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view(info)
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if __name__ == '__main__':
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main()
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