其他
多图“预警”（二）
本文作者：钱梦璇
文字编辑：孙晓玲
技术总编：张 邯
爬虫俱乐部将于2020年1月5日至11日在湖北武汉举行为期一周的Stata编程技术定制培训，此次采取初级班和高级班分批次培训。课程通过案例教学模式，旨在帮助大家在短期内掌握Stata软件编程、金融计量知识和实证分析方法，使大家熟悉Stata核心的爬虫技术，以及Stata与其他软件交互的高端技术。目前正在火热招生中~详细培训大纲及报名方式，请点击《爬虫俱乐部2020第一期Stata编程训练营开始报名啦！》或点击文末阅读原文呦~
import requestsimport json
url='https://movie.douban.com/j/search_subjects?type=movie&tag=%E7%83%AD%E9%97%A8&sort=recommend&page_limit=20&page_start=0'headers={ 'Accept':'*/*', 'Accept-Encoding':'gzip, deflate, br', 'Accept-Language':'zh-CN,zh;q=0.9', 'Connection':'keep-alive', 'Cookie':'bid=GG64rKF1uSo; ll="118254"; __utmz=30149280.1574226060.1.1.utmcsr=(direct)|utmccn=(direct)|utmcmd=(none); __utmz=223695111.1574226060.1.1.utmcsr=(direct)|utmccn=(direct)|utmcmd=(none); _vwo_uuid_v2=D20958CEF499378872990726113CB0E21|0b07de9babe9417544bca3ba22160c95; __yadk_uid=NIu4zXoawDz9m1KQRjtxprXcTPzJ88sL; ap_v=0,6.0; _pk_ses.100001.4cf6=*; __utma=30149280.561143398.1574226060.1574226060.1574241149.2; __utmb=30149280.0.10.1574241149; __utmc=30149280; __utma=223695111.1869265892.1574226060.1574226060.1574241149.2; __utmb=223695111.0.10.1574241149; __utmc=223695111; _pk_id.100001.4cf6=b4251776f0f5c706.1574226060.2.1574241187.1574226148.', 'Host':'movie.douban.com', 'Referer':'https://movie.douban.com/explore', 'User-Agent':'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/63.0.3239.132 Safari/537.36', 'X-Requested-With':'XMLHttpRequest' }result=requests.get(url,headers=headers)data=json.loads(result.text)['subjects']#print(data)
movie=[]rate=[]for index in range(0,20): movie.append(data[index]['title']) rate.append(data[index]['rate'])print("电影名称：%s" % movie)print("豆瓣评分：%s" % rate)顺序多图Page
1.默认布局
from pyecharts import options as optsfrom pyecharts.charts import Bar,EffectScatter,Pagefrom pyecharts.globals import ThemeType #引入主题from pyecharts.globals import SymbolType #导入涟漪特效图形符号bar=( Bar(init_opts=opts.InitOpts(theme=ThemeType.MACARONS)) #创建Bar实例 .add_xaxis(movie) .add_yaxis("豆瓣评分",rate) .set_global_opts(title_opts=opts.TitleOpts(title = "豆瓣电影-柱状图",subtitle = "按热度排序的前20名电影") ,legend_opts=opts.LegendOpts(pos_top="6%") ,xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=45))))Scatter=( EffectScatter() .add_xaxis(movie) .add_yaxis("豆瓣评分",rate,symbol=SymbolType.ARROW) .set_global_opts(title_opts=opts.TitleOpts(title = "豆瓣电影-动态散点图",subtitle = "按热度排序的前20名电影") ,xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=45))))page=( Page() .add(Scatter,bar))page.render_notebook()from pyecharts import options as optsfrom pyecharts.charts import Bar,EffectScatter,Page,Line,Piefrom pyecharts.globals import ThemeType from pyecharts.globals import SymbolType bar=( Bar(init_opts=opts.InitOpts(theme=ThemeType.MACARONS,width="500px",height="500px")) #创建Bar实例 .add_xaxis(movie) .add_yaxis("豆瓣评分",rate) .set_global_opts(title_opts=opts.TitleOpts(title = "豆瓣电影-最近热门电影",subtitle = "按热度排序的前20名电影") ,legend_opts=opts.LegendOpts(pos_top="6%") ,xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=45)) ))Scatter=( EffectScatter(init_opts=opts.InitOpts(width="500px",height="500px")) .add_xaxis(movie) .add_yaxis("豆瓣评分",rate,symbol=SymbolType.ARROW) .set_global_opts(title_opts=opts.TitleOpts(title = "豆瓣电影-最近热门电影",subtitle = "按热度排序的前20名电影") ,xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=45))))line=( Line(init_opts=opts.InitOpts(width="500px",height="500px")) .add_xaxis(movie) .add_yaxis("豆瓣电影",rate,color="#675bba",label_opts=opts.LabelOpts(is_show=False)) .set_global_opts(xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=45))))
Pie=( Pie(init_opts=opts.InitOpts(width="500px",height="500px")) .add("",[("男",46.54),("女",53.46)]) .set_global_opts(title_opts=opts.TitleOpts(title="观影性别占比")) .set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}%")) )#page=Page()page=Page(layout=Page.SimplePageLayout) # 需要自行调整每个 chart 的 height/width，显示效果在不同的显示器上可能不同page.add(bar,Scatter,line,Pie)page.render(r'E:\ Page-SimplePageLayout.html') from pyecharts import options as optsfrom pyecharts.charts import Bar,EffectScatter,Page,Line,Pie,Tabfrom pyecharts.components import Tablefrom pyecharts.globals import ThemeType from pyecharts.globals import SymbolType bar=( Bar(init_opts=opts.InitOpts(theme=ThemeType.MACARONS,width="500px",height="500px")) #创建Bar实例 .add_xaxis(movie) .add_yaxis("豆瓣评分",rate) .set_global_opts(title_opts=opts.TitleOpts(title = "豆瓣电影-最近热门电影",subtitle = "按热度排序的前20名电影") ,legend_opts=opts.LegendOpts(pos_top="6%") ,xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=45)) ))Scatter=( EffectScatter(init_opts=opts.InitOpts(width="500px",height="500px")) .add_xaxis(movie) .add_yaxis("豆瓣评分",rate,symbol=SymbolType.ARROW) .set_global_opts(title_opts=opts.TitleOpts(title = "豆瓣电影-最近热门电影",subtitle = "按热度排序的前20名电影") ,xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=45))))line=( Line(init_opts=opts.InitOpts(width="500px",height="500px")) .add_xaxis(movie) .add_yaxis("豆瓣电影",rate,color="#675bba",label_opts=opts.LabelOpts(is_show=False)) .set_global_opts(xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=45))))
Pie=( Pie(init_opts=opts.InitOpts(width="500px",height="500px")) .add("",[("男",46.54),("女",53.46)]) .set_global_opts(title_opts=opts.TitleOpts(title="观影性别占比")) .set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}%")) #格式化标签输出内容 b代表数据项名称，c代表数值)headers=["电影名称","豆瓣评分"]rows=[['小丑',8.9],['小小的愿望',5.1],['克劳斯：圣诞节的秘密',8.4],['鹿皮',7.0],['最普通的恋爱',7.2],['罗小黑战记',8.2],['犯罪现场',6.5],['双子杀手',7.1],['寄生虫',8.7],['续命之徒：绝命毒师电影',8.1],['别告诉她',7.5],['哪吒之魔童降世',8.5],['我在雨中等你',8.2],['友情以上',6.3],['陈情令之生魂',4.5],['天使陷落',6.4],['好小子们',7.2],['送我上青云',7.1],['青春期猪头少年不做怀梦少女的梦',8.7],['小丑回魂2',6.4]]table=( Table() .add(headers,rows) .set_global_opts(title_opts=opts.ComponentTitleOpts(title="豆瓣电影-最近热门电影")) )
#page=Page()page=Page(layout=Page.DraggablePageLayout) # 需要自行调整每个 chart 的 height/width，显示效果在不同的显示器上可能不同page.add(bar,Scatter,line,Pie,table)page.render(r'E:\ Page-DraggablePageLayout.html')from pyecharts import options as optsfrom pyecharts.charts import Bar,EffectScatter,Page,Line,Pie,Tabfrom pyecharts.components import Tablefrom pyecharts.globals import ThemeType from pyecharts.globals import SymbolType bar=( Bar(init_opts=opts.InitOpts(theme=ThemeType.MACARONS)) .add_xaxis(movie) .add_yaxis("豆瓣评分",rate) .set_global_opts(title_opts=opts.TitleOpts(title = "豆瓣电影-最近热门电影",subtitle = "按热度排序的前20名电影") ,legend_opts=opts.LegendOpts(pos_top="6%") ,xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=45)) ))Scatter=( EffectScatter() .add_xaxis(movie) .add_yaxis("豆瓣评分",rate,symbol=SymbolType.ARROW) .set_global_opts(title_opts=opts.TitleOpts(title = "豆瓣电影-最近热门电影",subtitle = "按热度排序的前20名电影") ,xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=45))))line=( Line() .add_xaxis(movie) .add_yaxis("豆瓣电影",rate,color="#675bba",label_opts=opts.LabelOpts(is_show=False)) .set_global_opts(xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=45))))Pie=( Pie() .add("",[("男",46.54),("女",53.46)]) .set_global_opts(title_opts=opts.TitleOpts(title="观影性别占比")) .set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}%")) )headers=["电影名称","豆瓣评分"]rows=[['小丑',8.9],['小小的愿望',5.1],['克劳斯：圣诞节的秘密',8.4],['鹿皮',7.0],['最普通的恋爱',7.2],['罗小黑战记',8.2],['犯罪现场',6.5],['双子杀手',7.1],['寄生虫',8.7],['续命之徒：绝命毒师电影',8.1],['别告诉她',7.5],['哪吒之魔童降世',8.5],['我在雨中等你',8.2],['友情以上',6.3],['陈情令之生魂',4.5],['天使陷落',6.4],['好小子们',7.2],['送我上青云',7.1],['青春期猪头少年不做怀梦少女的梦',8.7],['小丑回魂2',6.4]]table=( Table() .add(headers,rows) .set_global_opts(title_opts=opts.ComponentTitleOpts(title="豆瓣电影-最近热门电影")) )tab=Tab()tab.add(bar,"柱状图示例")tab.add(Scatter,"散点图示例")tab.add(line, "线图示例")tab.add(Pie, "饼图示例")tab.add(table, "表格示例")tab.render(r'E:\Tab选项卡多图.html')from example.commons import Faker from pyecharts import options as optsfrom pyecharts.charts import Map,Timelinetl = Timeline()for i in range(2015, 2020): map=( Map() .add("商家", [list(z) for z in zip(Faker.provinces, Faker.values())],"china") .set_global_opts( title_opts=opts.TitleOpts(title="Map-{}年某些数据".format(i)), visualmap_opts=opts.VisualMapOpts(max_=200), ) ) tl.add(map,"{}年".format(i))tl.render(r'E:\时间线轮播多图.html')“气功”研究哪家强
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