pyecharts/test/test_geo.py
2017-08-13 08:52:37 +01:00

234 lines
6.3 KiB
Python

#!/usr/bin/env python
#coding=utf-8
from __future__ import unicode_literals
from pyecharts import Geo
def test_geo():
# geo_0
data = [
("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("全国主要城市空气质量", "data from pm2.5", title_color="#fff", title_pos="center", width=1200, height=600,
background_color='#404a59')
attr, value = geo.cast(data)
geo.add("", attr, value, visual_range=[0, 200], visual_text_color="#fff", symbol_size=15, is_visualmap=True)
geo.show_config()
geo.render()
# geo_0_1
geo = Geo("全国主要城市空气质量", "data from pm2.5", title_color="#fff", title_pos="center", width=1200, height=600,
background_color='#404a59')
attr, value = geo.cast(data)
geo.add("", attr, value, type="heatmap", is_visualmap=True, visual_range=[0, 300], visual_text_color='#fff')
geo.show_config()
geo.render()
# geo_1
data = [("海门", 9), ("鄂尔多斯", 12), ("招远", 12), ("舟山", 12), ("齐齐哈尔", 14), ("盐城", 15)]
geo = Geo("全国主要城市空气质量", "data from pm2.5", 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.show_config()
geo.render()
# geo_with_noexist_city
data = [("海门", 9), ("鄂尔多斯", 12), ("招远", 12), ("舟山", 12), ("齐齐哈尔", 14), ("伦敦", 15)]
geo = Geo("全国主要城市空气质量", "data from pm2.5", 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.show_config()
geo.render()