【Python】Pyecharts数据可视化模块练习

python：Pyecharts数据可视化模块练习

# -*- coding: utf-8 -*- """ Created on Sun Aug 5 22:16:09 2018@author: A3 """ # ============================================================================= from pyecharts import Geodata = [("海门", 9),("鄂尔多斯", 12),("招远", 12),("舟山", 12),("齐齐哈尔", 14),("盐城", 15),("赤峰", 16),("青岛", 18),("乳山", 18),("金昌", 19),("泉州", 21),("莱西", 21),("日照", 21),("胶南", 22),("南通", 23),("拉萨", 24),("云浮", 24),("梅州", 25),("文登", 25),("上海", 25),("攀枝花", 25),("威海", 25),("承德", 25),("厦门", 26),("汕尾", 26),("潮州", 26),("丹东", 27),("太仓", 27),("曲靖", 27),("烟台", 28),("福州", 29),("瓦房店", 30),("即墨", 30),("抚顺", 31),("玉溪", 31),("张家口", 31),("阳泉", 31),("莱州", 32),("湖州", 32),("汕头", 32),("昆山", 33),("宁波", 33),("湛江", 33),("揭阳", 34),("荣成", 34),("连云港", 35),("葫芦岛", 35),("常熟", 36),("东莞", 36),("河源", 36),("淮安", 36),("泰州", 36),("南宁", 37),("营口", 37),("惠州", 37),("江阴", 37),("蓬莱", 37),("韶关", 38),("嘉峪关", 38),("广州", 38),("延安", 38),("太原", 39),("清远", 39),("中山", 39),("昆明", 39),("寿光", 40),("盘锦", 40),("长治", 41),("深圳", 41),("珠海", 42),("宿迁", 43),("咸阳", 43),("铜川", 44),("平度", 44),("佛山", 44),("海口", 44),("江门", 45),("章丘", 45),("肇庆", 46),("大连", 47),("临汾", 47),("吴江", 47),("石嘴山", 49),("沈阳", 50),("苏州", 50),("茂名", 50),("嘉兴", 51),("长春", 51),("胶州", 52),("银川", 52),("张家港", 52),("三门峡", 53),("锦州", 54),("南昌", 54),("柳州", 54),("三亚", 54),("自贡", 56),("吉林", 56),("阳江", 57),("泸州", 57),("西宁", 57),("宜宾", 58),("呼和浩特", 58),("成都", 58),("大同", 58),("镇江", 59),("桂林", 59),("张家界", 59),("宜兴", 59),("北海", 60),("西安", 61),("金坛", 62),("东营", 62),("牡丹江", 63),("遵义", 63),("绍兴", 63),("扬州", 64),("常州", 64),("潍坊", 65),("重庆", 66),("台州", 67),("南京", 67),("滨州", 70),("贵阳", 71),("无锡", 71),("本溪", 71),("克拉玛依", 72),("渭南", 72),("马鞍山", 72),("宝鸡", 72),("焦作", 75),("句容", 75),("北京", 79),("徐州", 79),("衡水", 80),("包头", 80),("绵阳", 80),("乌鲁木齐", 84),("枣庄", 84),("杭州", 84),("淄博", 85),("鞍山", 86),("溧阳", 86),("库尔勒", 86),("安阳", 90),("开封", 90),("济南", 92),("德阳", 93),("温州", 95),("九江", 96),("邯郸", 98),("临安", 99),("兰州", 99),("沧州", 100),("临沂", 103),("南充", 104),("天津", 105),("富阳", 106),("泰安", 112),("诸暨", 112),("郑州", 113),("哈尔滨", 114),("聊城", 116),("芜湖", 117),("唐山", 119),("平顶山", 119),("邢台", 119),("德州", 120),("济宁", 120),("荆州", 127),("宜昌", 130),("义乌", 132),("丽水", 133),("洛阳", 134),("秦皇岛", 136),("株洲", 143),("石家庄", 147),("莱芜", 148),("常德", 152),("保定", 153),("湘潭", 154),("金华", 157),("岳阳", 169),("长沙", 175),("衢州", 177),("廊坊", 193),("菏泽", 194),("合肥", 229),("武汉", 273),("大庆", 279)] geo = Geo("全国主要城市逾期情况", "data from 3dp", title_color="#fff",title_pos="center", width=1000,height=600, background_color='#404a59') attr, value = geo.cast(data) geo.add("", attr, value, visual_range=[0, 200], maptype='china',visual_text_color="#fff",symbol_size=10, is_visualmap=True) geo.render(r"C:\Users\A3\Desktop\全国主要城市逾期情况.html")#生成html文件 geo #geo地理信息定位# =============================================================================from pyecharts import Map districts = ['运河区', '新华区', '泊头市', '任丘市', '黄骅市', '河间市', '沧县', '青县', '东光县', '海兴县', '盐山县', '肃宁县', '南皮县', '吴桥县', '献县', '孟村回族自治县'] areas = [109.92, 109.47, 1006.5, 1023.0, 1544.7, 1333.0, 1104.0, 968.0, 730.0, 915.1, 796.0, 525.0, 794.0, 600.0, 1191.0, 387.0] map_1 = Map("沧州市图例－各区面积", width=1200, height=600) map_1.add("", districts, areas, maptype='沧州', is_visualmap=True, visual_range=[min(areas), max(areas)],visual_text_color='#000', is_map_symbol_show=False, is_label_show=True) map_1.render()from pyecharts import Mapvalue = [155, 10, 66, 78] attr = ["福建", "山东", "北京", "上海"] map = Map("全国地图示例", width=1200, height=600) map.add("", attr, value, maptype='china', is_label_show=True) map.render()value = [95.1, 23.2, 43.3, 66.4, 88.5] attr= ["China", "Canada", "Brazil", "Russia", "United States"] map = Map("世界地图示例", width=1200, height=600) map.add("", attr, value, maptype="world", is_visualmap=True,visual_text_color='#000') map.render()value = [155, 10, 66, 78] attr = ["福建", "山东", "北京", "上海"] map = Map("全国地图示例", width=1200, height=600) map.add("", attr, value, maptype='china',is_visualmap=True, is_piecewise=True,visual_text_color="#000",visual_range_text=["", ""],pieces=[{"max": 160, "min": 70, "label": "高数值"},{"max": 69, "min": 0, "label": "低数值"},]) map.render()# ============================================================================= from pyecharts import Barbar = Bar("我的第一个图表", "这里是副标题") bar.use_theme('dark') bar.add("服装", ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"], [5, 20, 36, 10, 75, 90]) # bar.print_echarts_options() # 该行只为了打印配置项，方便调试时使用 bar.render(r'C:\Users\A3\Desktop\test1.html') # 生成本地 HTML 文件# ============================================================================= from pyecharts import Bar, Line from pyecharts.engine import create_default_environment bar = Bar("我的第一个图表", "这里是副标题") bar.add("服装", ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"], [5, 20, 36, 10, 75, 90])line = Line("我的第一个图表", "这里是副标题") line.add("服装", ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"], [5, 20, 36, 10, 75, 90])env = create_default_environment("html") # 为渲染创建一个默认配置环境 # create_default_environment(filet_ype) # file_type: 'html', 'svg', 'png', 'jpeg', 'gif' or 'pdf'env.render_chart_to_file(bar, path='bar.html') env.render_chart_to_file(line, path='line.html') # ============================================================================= from pyecharts import Barattr = ["{}月".format(i) for i in range(1, 13)] v1 = [2.0, 4.9, 7.0, 23.2, 25.6, 76.7, 135.6, 162.2, 32.6, 20.0, 6.4, 3.3] v2 = [2.6, 5.9, 9.0, 26.4, 28.7, 70.7, 175.6, 182.2, 48.7, 18.8, 6.0, 2.3] bar = Bar("柱状图示例") bar.add("蒸发量", attr, v1, mark_line=["average"], mark_point=["max", "min"]) bar.add("降水量", attr, v2, mark_line=["average"], mark_point=["max", "min"]) bar.render()from pyecharts import Geodata = [("北京", 15), ("杭州", 20), ("大同", 5),("深圳", 2), ("青岛", 2), ("上海", 5), ("南京", 5), ("呼和浩特", 5),("太原", 5), ("嘉兴", 5), ("广州", 5), ("深圳", 5), ("合肥", 5), ("绍兴", 5), ("惠州", 5), ("朔州", 5)] geo = Geo("既然我们一起走了这么多 ", "那希望能用同一种颜色填满你心里的每一个角落", title_color="#fff",title_pos="center", width=1200,height=600, background_color='#404a59') attr, value = geo.cast(data) geo.add("", attr, value, type="effectScatter", is_random=True, effect_scale=5) geo.render(r'C:\Users\A3\Desktop\test.html') geo.render(path='snapshot.gif')# ============================================================================= from pyecharts import GeoLines, Stylestyle = Style(title_top="#fff",title_pos = "center",width=1200,height=600,background_color="#404a59" )data_beijing = [["北京", "杭州"],["北京", "青岛"],["北京", "长沙"],["北京", "上海"],["北京", "成都"],["北京", "吉林"],["北京", "大理"],["北京", "深圳"],["北京", "福州"],["北京", "武汉"] ]style_geo = style.add(is_label_show=True,line_curve=0.2,line_opacity=0.6,legend_text_color="#eee",legend_pos="right",geo_effect_symbol="plane",geo_effect_symbolsize=15,label_color=['#a6c84c', '#ffa022', '#46bee9'],label_pos="right",label_formatter="{b}",label_text_color="#eee", )geolines = GeoLines("从哪里相识，就从哪里散场", **style.init_style) geolines.add("从北京开始", data_beijing, **style_geo) geolines.render(r'C:\Users\A3\Desktop\test1.html') # ============================================================================= from pyecharts import GeoLines, Styledata_guangzhou = [["广州", "上海", 10],["广州", "北京", 20],["广州", "南京", 30],["广州", "重庆", 40],["广州", "兰州", 50],["广州", "杭州", 60], ] lines = GeoLines("GeoLines 示例", **style.init_style) lines.add("从广州出发", data_guangzhou, tooltip_formatter="{a} : {c}", **style_geo) lines.render(r'C:\Users\A3\Desktop\test2.html') # ===========================================================================

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