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from pyecharts import Pie, Page,Bar
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from spider import dbconnect
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#查询统计某城市菜品分类名
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def foodClass(city):
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#连接数据库
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mysql_db = dbconnect.DBHelper()
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mysql_db.connectDatabase();
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fsql = '''SELECT COUNT(mainCategoryName),mainCategoryName from dazhongoutput where city="%s" GROUP BY mainCategoryName;'''%(city)
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#查询获得菜品分类商店梳理、菜品分类名称数据返回
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listData = mysql_db.select(fsql)
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return listData
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#菜品分类画图函数
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def plotfoodclass():
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#查询统计济南的菜品分类以及数量
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list_address = []
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list_sum = []
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[list_sum.append(i[0]) for i in foodClass("济南")]
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[list_address.append(i[1]) for i in foodClass("济南")]
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print(list_address)
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print(list_sum)
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#定义页面
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page = Page()
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#添加饼图的数据和配置项
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fpie1 = Pie("济南菜品分类", title_pos='center')
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fpie1.add("", list_address, list_sum, radius=[30, 75], label_text_color=None,
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is_label_show=True, legend_orient='vertical',
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legend_pos='auto', is_legend_show=False)
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#添加柱状图的数据和配置型项
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fbar1 = Bar("济南菜品分类", "数据来源于大众点评TOP100",title_pos ='center')
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fbar1.add("济南", list_address, list_sum, mark_point=["max", "min"],legend_pos="right")
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# 查询统计青岛的菜品分类以及数量
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list_address = []
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list_sum = []
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[list_sum.append(i[0]) for i in foodClass("青岛")]
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[list_address.append(i[1]) for i in foodClass("青岛")]
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print(list_address)
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print(list_sum)
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# 添加饼图的数据和配置项
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fpie2 = Pie("青岛菜品分类", title_pos='center')
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fpie2.add("", list_address, list_sum, radius=[30, 75], label_text_color=None,
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is_label_show=True, legend_orient='vertical',
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legend_pos='auto', is_legend_show=False)
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# 添加柱状图的数据和配置型项
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fbar2 = Bar("青岛菜品分类", "数据来源于大众点评TOP100", title_pos='center')
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fbar2.add("青岛", list_address, list_sum, mark_point=["max", "min"], legend_pos="right")
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# 查询统计威海的菜品分类以及数量
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list_address = []
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list_sum = []
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[list_sum.append(i[0]) for i in foodClass("威海")]
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[list_address.append(i[1]) for i in foodClass("威海")]
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print(list_address)
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print(list_sum)
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# 添加饼图的数据和配置项
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fpie3 = Pie("威海菜品分类", title_pos='center')
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fpie3.add("", list_address, list_sum, radius=[30, 75], label_text_color=None,
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is_label_show=True, legend_orient='vertical',
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legend_pos='auto', is_legend_show=False)
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# 添加柱状图的数据和配置型项
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fbar3 = Bar("威海菜品分类", "数据来源于大众点评TOP100", title_pos='center')
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fbar3.add("威海", list_address, list_sum, mark_point=["max", "min"], legend_pos="right")
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#页面上添加图形
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page.add(fpie1)
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page.add(fbar1)
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page.add(fpie2)
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page.add(fbar2)
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page.add(fpie3)
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page.add(fbar3)
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page.render("山东3大城市菜品分类.html")
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if __name__ == '__main__':
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plotfoodclass()
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from pyecharts import Pie, Page,Bar
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from spider import dbconnect
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#查询统计某城市菜品分类名
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def foodClass(city):
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#连接数据库
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mysql_db = dbconnect.DBHelper()
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mysql_db.connectDatabase();
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fsql = '''SELECT COUNT(mainCategoryName),mainCategoryName from dazhongoutput where city="%s" GROUP BY mainCategoryName;'''%(city)
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#查询获得菜品分类商店梳理、菜品分类名称数据返回
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listData = mysql_db.select(fsql)
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return listData
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#菜品分类画图函数
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def plotfoodclass():
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#查询统计济南的菜品分类以及数量
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list_address = []
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list_sum = []
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[list_sum.append(i[0]) for i in foodClass("济南")]
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[list_address.append(i[1]) for i in foodClass("济南")]
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print(list_address)
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print(list_sum)
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#定义页面
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page = Page()
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#添加饼图的数据和配置项
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fpie1 = Pie("济南菜品分类", title_pos='center')
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fpie1.add("", list_address, list_sum, radius=[30, 75], label_text_color=None,
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is_label_show=True, legend_orient='vertical',
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legend_pos='auto', is_legend_show=False)
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#添加柱状图的数据和配置型项
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fbar1 = Bar("济南菜品分类", "数据来源于大众点评TOP100",title_pos ='center')
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fbar1.add("济南", list_address, list_sum, mark_point=["max", "min"],legend_pos="right")
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# 查询统计青岛的菜品分类以及数量
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list_address = []
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list_sum = []
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[list_sum.append(i[0]) for i in foodClass("青岛")]
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[list_address.append(i[1]) for i in foodClass("青岛")]
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print(list_address)
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print(list_sum)
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# 添加饼图的数据和配置项
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fpie2 = Pie("青岛菜品分类", title_pos='center')
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fpie2.add("", list_address, list_sum, radius=[30, 75], label_text_color=None,
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is_label_show=True, legend_orient='vertical',
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legend_pos='auto', is_legend_show=False)
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# 添加柱状图的数据和配置型项
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fbar2 = Bar("青岛菜品分类", "数据来源于大众点评TOP100", title_pos='center')
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fbar2.add("青岛", list_address, list_sum, mark_point=["max", "min"], legend_pos="right")
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# 查询统计威海的菜品分类以及数量
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list_address = []
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list_sum = []
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[list_sum.append(i[0]) for i in foodClass("威海")]
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[list_address.append(i[1]) for i in foodClass("威海")]
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print(list_address)
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print(list_sum)
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# 添加饼图的数据和配置项
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fpie3 = Pie("威海菜品分类", title_pos='center')
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fpie3.add("", list_address, list_sum, radius=[30, 75], label_text_color=None,
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is_label_show=True, legend_orient='vertical',
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legend_pos='auto', is_legend_show=False)
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# 添加柱状图的数据和配置型项
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fbar3 = Bar("威海菜品分类", "数据来源于大众点评TOP100", title_pos='center')
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fbar3.add("威海", list_address, list_sum, mark_point=["max", "min"], legend_pos="right")
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#页面上添加图形
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page.add(fpie1)
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page.add(fbar1)
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page.add(fpie2)
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page.add(fbar2)
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page.add(fpie3)
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page.add(fbar3)
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page.render("山东3大城市菜品分类.html")
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if __name__ == '__main__':
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plotfoodclass()
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from pyecharts import Bar
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from spider import dbconnect
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# 统计一个城市各星级饭店数量函数
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def starshopCount(City):
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#连接数据库
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mysql_db = dbconnect.DBHelper()
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mysql_db.connectDatabase();
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#查询有哪些星级,返回唯一不同的星级
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starsql = "SELECT DISTINCT(shopPower) from dazhongoutput ;"
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data = mysql_db.select(starsql) #返回所有查询记录行，每一行是一个元组，所有行的元组再组装成一个元组data
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list_code = []
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for i in data:
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#选择该城市某个星级按照商铺ID统计商铺数量
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countsql = '''SELECT COUNT(shopId) from dazhongoutput where shopPower=%s and city="%s";''' % (i[0], City)
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countstar_city = mysql_db.select(countsql)
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#将所有星级和饭店数量放于list_code列表
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for m in countstar_city:
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list_code.append([i[0], m[0]])
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print(list_code)
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#返回商铺星级、数量
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return list_code
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# 所有城市各星级饭店统计函数
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def mianStar():
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#调用starshopCount(City)统计出下述城市各星级饭店数量
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shop1 = starshopCount("广州")
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shop2 = starshopCount("杭州")
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shop3 = starshopCount("南京")
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shop4 = starshopCount("成都")
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shop5 = starshopCount("武汉")
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shop6 = starshopCount("济南")
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shop7 = starshopCount("南宁")
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shop8 = starshopCount("合肥")
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shop9 = starshopCount("昆明")
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shop10 = starshopCount("西安")
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shop11 = starshopCount("北京")
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shop12 = starshopCount("上海")
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shop13 = starshopCount("深圳")
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shop14 = starshopCount("天津")
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shop15 = starshopCount("重庆")
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shop16 = starshopCount("青岛")
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shop17 = starshopCount("威海")
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shop18 = starshopCount("长春")
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shop19 = starshopCount("大连")
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shop20 = starshopCount("贵阳")
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#定义X轴和Y轴显示数据列表，开始为NULL
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list_x = []
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list_y1, list_y2, list_y3, list_y4, list_y5, list_y6, list_y7, list_y8, list_y9, list_y10,list_y11, list_y12, list_y13, list_y14, list_y15, list_y16, list_y17, list_y18, list_y19, list_y20 = [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], []
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#数据列表赋值,zip将所有城市星级饭店列表，打包为一个包含多个元组的zip迭代对象，多变量循环
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for data1, data2, data3, data4, data5, data6, data7, data8, data9, data10, data11, data12, data13, data14, data15, data16, data17, data18, data19, data20 in zip(
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shop1, shop2, shop3, shop4, shop5, shop6, shop7, shop8, shop9, shop10,
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shop11, shop12, shop13, shop14, shop15, shop16, shop17, shop18, shop19, shop20
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):
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#提取星级，建立X轴列表
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if data1[0] == '30':
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list_x.append("三星级")
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elif data1[0] == '35':
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list_x.append("三星半")
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elif data1[0] == '40':
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list_x.append("四星级")
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elif data1[0] == '45':
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list_x.append("四星半")
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else:
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list_x.append("五星级")
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#20城市不同星级饭店数量
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list_y1.append(data1[1])
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list_y2.append(data2[1])
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list_y3.append(data3[1])
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list_y4.append(data4[1])
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list_y5.append(data5[1])
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list_y6.append(data6[1])
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list_y7.append(data7[1])
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list_y8.append(data8[1])
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list_y9.append(data9[1])
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list_y10.append(data10[1])
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list_y11.append(data11[1])
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list_y12.append(data12[1])
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list_y13.append(data13[1])
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list_y14.append(data14[1])
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list_y15.append(data15[1])
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list_y16.append(data16[1])
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list_y17.append(data17[1])
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list_y18.append(data18[1])
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list_y19.append(data19[1])
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list_y20.append(data20[1])
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print(list_x, list_y1, list_y2, list_y3, list_y4, list_y5, list_y6, list_y7, list_y8, list_y9, list_y10,
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list_y11, list_y12, list_y13, list_y14, list_y15, list_y16, list_y17, list_y18, list_y19, list_y20
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)
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# 饭店星级排行画图
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plotstar(list_x, list_y1, list_y2, list_y3, list_y4, list_y5, list_y6, list_y7, list_y8, list_y9, list_y10,
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list_y11, list_y12, list_y13, list_y14, list_y15, list_y16, list_y17, list_y18, list_y19, list_y20
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)
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# 饭店星级排行画图函数
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def plotstar(list_x, list_y1, list_y2, list_y3, list_y4, list_y5, list_y6, list_y7, list_y8, list_y9, list_y10,
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list_y11, list_y12, list_y13, list_y14, list_y15, list_y16, list_y17, list_y18, list_y19, list_y20):
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attr = list_x
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#设置柱状图大小标题,可根据实际数据情况统计
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starbar = Bar("20个大中城市饭店星级统计", "数据来源于大众点评TOP100",width=1300,height=500)
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##添加柱状图数据和配置项，标记最大值和最小值，最右侧设置工具栏，可对图进行更多操作，图例位置
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starbar.add("广州", attr, list_y1, mark_point=["max", "min"])
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starbar.add("杭州", attr, list_y2, mark_point=["max", "min"])
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starbar.add("南京", attr, list_y3, mark_point=["max", "min"])
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starbar.add("成都", attr, list_y4, mark_point=["max", "min"])
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starbar.add("武汉", attr, list_y5, mark_point=["max", "min"])
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starbar.add("济南", attr, list_y6, mark_point=["max", "min"])
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starbar.add("南宁", attr, list_y7, mark_point=["max", "min"])
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starbar.add("合肥", attr, list_y8, mark_point=["max", "min"])
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starbar.add("昆明", attr, list_y9, mark_point=["max", "min"])
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starbar.add("西安", attr, list_y10, mark_point=["max", "min"])
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starbar.add("北京", attr, list_y11, mark_point=["max", "min"])
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starbar.add("上海", attr, list_y12, mark_point=["max", "min"])
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starbar.add("深圳", attr, list_y13, mark_point=["max", "min"])
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starbar.add("天津", attr, list_y14, mark_point=["max", "min"])
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starbar.add("重庆", attr, list_y15, mark_point=["max", "min"])
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starbar.add("青岛", attr, list_y16, mark_point=["max", "min"])
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starbar.add("威海", attr, list_y17, mark_point=["max", "min"])
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starbar.add("长春", attr, list_y18, mark_point=["max", "min"])
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starbar.add("大连", attr, list_y19, mark_point=["max", "min"])
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starbar.add("贵阳", attr, list_y20, mark_point=["max", "min"], is_more_utils=True, legend_top='bottom')
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#生成html文件数据可视化展示
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starbar.render("20个大中城市饭店星级排名.html")
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if __name__ == '__main__':
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mianStar()
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+1643
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