毕业设计基于Python豆瓣电影数据爬取及可视化源码.zip

import random from pyecharts import options as opts from pyecharts.charts import * from pyecharts.globals import CurrentConfig CurrentConfig.ONLINE_HOST = "https://cdn.kesci.com/lib/pyecharts_assets/" province = [ '广东', '湖北', '湖南', '四川', '重庆', '黑龙江', '浙江', '山西', '河北', '安徽', '河南', '山东', '西藏'] data = [(i, random.randint(50, 150)) for i in province] geo = ( Geo() .add_schema(maptype="china") .add("", data) # 网址：https://www.heywhale.com/mw/project/5eb7958f366f4d002d783d4a # 在中间引入这段代码即可 .set_series_opts(label_opts=opts.LabelOpts(position="right")) .render('中国地图.html') ) # 虚假数据 data = [[i, j, random.randint(0, 100)] for i in range(24) for j in range(7)] hour_list = [str(i) for i in range(24)] week_list = ['周日', '周一', '周二', '周三', '周四', '周五', '周六'] heat = (HeatMap() .add_xaxis(hour_list) .add_yaxis("", week_list, data) .set_series_opts(label_opts=opts.LabelOpts(position="right")) .render('方格图.html') ) data = [(random.randint(0, 100), random.randint(0, 100), random.randint(0, 100)) for _ in range(100)] scatter3D = (Scatter3D() .add("", data) # 网址：https://www.heywhale.com/mw/project/5eb7958f366f4d002d783d4a # 在中间引入这段代码即可 .set_series_opts(label_opts=opts.LabelOpts(position="right")) .render('3D散点图.html') ) data = [[i, j, random.randint(0, 100)] for i in range(24) for j in range(7)] hour_list = [str(i) for i in range(24)] week_list = ['周日', '周一', '周二', '周三', '周四', '周五', '周六'] bar3D = ( Bar3D() .add( "", data, xaxis3d_opts=opts.Axis3DOpts(hour_list, type_="category"), yaxis3d_opts=opts.Axis3DOpts(week_list, type_="category"), zaxis3d_opts=opts.Axis3DOpts(type_="value"), ) # 在中间引入这段代码即可 .set_series_opts(label_opts=opts.LabelOpts(position="right")) .render('3D直方图.html') ) from pyecharts.faker import POPULATION mapglobe = ( MapGlobe() .add_schema() .add( series_name="", maptype="world", data_pair=POPULATION[1:] ) # 在中间引入这段代码即可 .set_series_opts(label_opts=opts.LabelOpts(position="right")) .render('3D地球.html') ) # 虚假数据 x_data = [random.randint(0, 100) for _ in range(20)] y_data = [random.randint(0, 100) for _ in range(20)] # 将x轴设置为数值类型 scatter = (Scatter() .add_xaxis(x_data) .add_yaxis('', y_data) .set_global_opts(xaxis_opts=opts.AxisOpts(type_='value')) # 在中间引入这段代码即可 .set_series_opts(label_opts=opts.LabelOpts(position="right")) .render('坐标轴类型.html') ) # 虚假数据 x_data = list(range(1990,2020)) y_data_1 = [random.randint(0, 100) for _ in x_data] y_data_2 = [random.randint(0, 100) for _ in x_data] bar = ( Bar() .add_xaxis(x_data) .add_yaxis('图例1', y_data_1) .add_yaxis('图例2', y_data_2) .set_global_opts(datazoom_opts=opts.DataZoomOpts(orient="vertical")) # 在中间引入这段代码即可 .set_series_opts(label_opts=opts.LabelOpts(position="right")) .render('缩放Y轴.html') ) # 虚假数据 x_data = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu'] y_data_1 = [123, 153, 89, 107, 98, 23] y_data_2 = [231, 321, 135, 341, 245, 167] y_data_3 = [223, 453, 189, 207, 221, 123] # 注意区分 line = (Line() .add_xaxis(x_data) .add_yaxis('1', y_data_1, color='green') .add_yaxis('2', y_data_2, color='green', linestyle_opts=opts.LineStyleOpts(color='black')) .add_yaxis('3', y_data_3, linestyle_opts=opts.LineStyleOpts(color='black')) # 在中间引入这段代码即可 .set_series_opts(label_opts=opts.LabelOpts(position="right")) .render('折线图.html') ) # 虚假数据 x_data = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu'] y_data_1 = [123, 153, 89, 107, 98, 23] y_data_2 = [231, 321, 135, 341, 245, 167] effectScatter = (EffectScatter() .add_xaxis(x_data) .add_yaxis('', y_data_1, effect_opts=opts.EffectOpts(scale=10, period=5)) .add_yaxis('', y_data_2, effect_opts=opts.EffectOpts(scale=5, period=10)) # 在中间引入这段代码即可 .set_series_opts(label_opts=opts.LabelOpts(position="right")) .render('范围 & 周期.html') )