就是这么简单！Pyecharts绘制可视化地图专辑

pip install pyecharts
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pip install echarts-countries-pypkg
pip install echarts-china-provinces-pypkg
pip install echarts-china-cities-pypkg
pip install echarts-china-counties-pypkg
pip install echarts-china-misc-pypkg
pip install echarts-united-kingdom-pypkg
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pip install pyecharts -i http://pypi.douban.com/simple 
pip install -i https://pypi.tuna.tsinghua.edu.cn/simple echarts-countries-pypkg
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import pyecharts
print(pyecharts.__version__)
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from pyecharts.charts import Map
from pyecharts import options as opts
from pyecharts.globals import ThemeType, CurrentConfig

CurrentConfig.ONLINE_HOST = 'C:/python/pyecharts-assets-master/assets/'
# 参考 https://github.com/pyecharts/pyecharts-assets

df = starbuck['English']
data = df.value_counts()
datas = [(i, int(j)) for i, j in zip(data.index, data.values)]

# 实例化一个Map对象
map_ = Map(init_opts=opts.InitOpts(theme=ThemeType.PURPLE_PASSION))

# 世界地图
map_.add(series_name="门店数量", data_pair=datas, maptype="world")

# 设置系列配置项
map_.set_series_opts(label_opts=opts.LabelOpts(is_show=False))   # 不显示label
# 设置全局配置项
map_.set_global_opts(
     title_opts=opts.TitleOpts(title="星巴克门店数量在全球分布", 
                               pos_left='40%', 
                               pos_top='10'),   # 调整title位置
     legend_opts=opts.LegendOpts(is_show=False),
     visualmap_opts=opts.VisualMapOpts(
         max_=13608, 
         min_=1, 
         is_piecewise=True,
       pieces=[{"max": 9, "min": 1, "label": "1-9", "color": "#00FFFF"},
                 {"max": 99, "min": 10, "label": "10-99", "color": "#FF69B4"},
                 {"max": 499, "min": 100, "label": "100-499", "color": "#0000FF"},
                 {"max": 999, "min": 500, "label": "500-999", "color": "#00BFFF"},
                 {"max": 2000, "min": 1000, "label": "1000-2000", "color": "#228B22"},
                 {"max": 3000, "min": 2000, "label": "2000-3000", "color": "#FF0000"},
                 {"max": 20000, "min": 10000, "label": ">=10000", "color": "#FFD700"}
                ] # 分段  添加图例注释和颜色
     )
)
# 渲染在网页上   有交互性
map_.render('星巴克门店在全球的分布.html')
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Map(init_opts=opts.InitOpts(theme=ThemeType.PURPLE_PASSION))
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[('United States', 13608),
 ('China', 2734),
 ('Canada', 1468),
 ('Japan', 1237),
 ...
 ]
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.set_series_opts()
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from pyecharts.globals import GeoType    
GeoType.GeoType.EFFECT_SCATTER，GeoType.HEATMAP，GeoType.LINES
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import pandas as pd
from pyecharts.globals import ThemeType, CurrentConfig, GeoType
from pyecharts import options as opts
from pyecharts.charts import Geo

CurrentConfig.ONLINE_HOST = 'C:/python/pyecharts-assets-master/assets/'
# pandas读取csv文件数据
df = pd.read_csv('directory2.csv', encoding='utf-8')['城市']
data = df.value_counts()
#自定义各城市的经纬度
# geo_cities_coords = {df.iloc[i]['城市']:[df.iloc[i]['经度'],df.iloc[i]['纬度']] for i in range(len(df))}

datas = [(i, int(j)) for i, j in zip(data.index, data.values)]
print(datas)

geo = (Geo(init_opts=opts.InitOpts(width='1000px', 
                                   height='600px', 
                                   theme=ThemeType.PURPLE_PASSION),
           is_ignore_nonexistent_coord = True)
       .add_schema(maptype='china', 
                   label_opts=opts.LabelOpts(is_show=True))   # 显示label  省名
       .add('门店数量', 
            data_pair=datas, 
            type_=GeoType.EFFECT_SCATTER, 
            symbol_size=8,
            # geo_cities_coords=geo_cities_coords
           )
       .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
       .set_global_opts(
           title_opts=opts.TitleOpts(title='星巴克门店在中国的分布'),
           visualmap_opts=opts.VisualMapOpts(max_=550,
                                             is_piecewise=True,
                                             pieces=[
                     {"max": 50, "min": 0, "label": "0-50", "color": "#708090"},
                     {"max": 100, "min": 51, "label": "51-100", "color": "#00FFFF"},
                     {"max": 200, "min": 101, "label": "101-200", "color": "#FF69B4"},
                     {"max": 400, "min": 201, "label": "201-400", "color": "#FFD700"},
                     {"max": 800, "min": 600, "label": "600-800", "color": "#FF0000"},])
       )
      )

geo.render("星巴克门店在中国的分布.html")
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# 新增一个坐标点
.add_coordinate(    
    # 坐标地点名称    
    name: str,     
    # 经度    
    longitude: Numeric,     
    # 纬度    
    latitude: Numeric, )
# 新增 json 文件格式的坐标数据
.add_coordinate_json(
    # json 文件格式的坐标数据
    # 格式如下
    # {
    #   "阿城": [126.58, 45.32],
    #   "阿克苏": [80.19, 41.09]
    # }
    json_file: str # 坐标文件路径
)
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from pyecharts import options as opts
from pyecharts.charts import Geo
from pyecharts.globals import ChartType
CurrentConfig.ONLINE_HOST = 'C:/python/pyecharts-assets-master/assets/'

# pandas读取csv文件数据
df = pd.read_csv('directory2.csv', encoding='utf-8')['城市']
data = df.value_counts()

datas = [(i, int(j)) for i, j in zip(data.index, data.values)]
print(datas)
geo = (
    Geo(init_opts=opts.InitOpts(width='1000px', 
                                height='600px', 
                                theme=ThemeType.DARK),
        is_ignore_nonexistent_coord=True)
    .add_schema(maptype="china")                       #maptype选择地图种类
    .add(series_name="门店数量",      # 系列名称
         data_pair=datas,          # 数据项 (坐标点名称，坐标点值)
         blur_size=20,
         symbol_size= 5,
         type_=ChartType.HEATMAP  #类型选为热力图
         )
    .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
    .set_global_opts(
        visualmap_opts=opts.VisualMapOpts(max_=800,is_piecewise=True),
        title_opts=opts.TitleOpts(title="星巴克门店在中国的分布热力图"))
)
geo.render( '星巴克门店在中国的分布热力图.html')
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from pyecharts import options as opts
from pyecharts.charts import Geo
from pyecharts.faker import Faker
from pyecharts.globals import ChartType, SymbolType, CurrentConfig
import  random

datas = []
for _ in range(6):
    datas.append(tuple(random.sample(Faker.provinces, 2)))
    
CurrentConfig.ONLINE_HOST = 'C:/python/pyecharts-assets-master/assets/'
geo = (
    Geo(init_opts=opts.InitOpts(width='1000px', 
                                height='600px', 
                                theme=ThemeType.CHALK))
    .add_schema(
        maptype="china",
        itemstyle_opts=opts.ItemStyleOpts(color="#323c48", border_color="#111"),
        label_opts=opts.LabelOpts(is_show=True)
    )
    .add(
        "",
        [list(z) for z in zip(Faker.provinces, Faker.values())],
        type_=ChartType.EFFECT_SCATTER,
        color="white",
    )
    .add(
        "出差",
        data_pair = datas,
        type_=ChartType.LINES,
        effect_opts=opts.EffectOpts(
            symbol=SymbolType.DIAMOND, symbol_size=6, color="blue"
        ),
        linestyle_opts=opts.LineStyleOpts(curve=0.2),
    )
    .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
    .set_global_opts(title_opts=opts.TitleOpts(title="动态轨迹图"))
    .render("动态轨迹图.html")
)
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.add('旅游',
     [('上海','拉萨'),('拉萨','大理'),('大理','成都'),('成都','海口')],
     type_=ChartType.LINES,
     effect_opts=opts.EffectOpts(
         symbol=SymbolType.ARROW, symbol_size=6, color="orange"),
     linestyle_opts=opts.LineStyleOpts(curve=0.5)
    )
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from pyecharts import options as opts
from pyecharts.charts import Map3D
from pyecharts.globals import ChartType
from pyecharts.commons.utils import JsCode

c = (
    Map3D(init_opts=opts.InitOpts(width='1000px', 
                                height='600px', 
                                theme=ThemeType.VINTAGE))
    # 地图类型
    .add_schema(
        itemstyle_opts=opts.ItemStyleOpts( # 图形的颜色
            color="#00BFFF", # 或 'rgb(128, 128, 128)'
            opacity=1, # 图形透明度
            border_width=0.8, # 描边宽度
            border_color="#708090", # 描边颜色
        ),
        # Map3D 的 Label 设置
        map3d_label=opts.Map3DLabelOpts(
            is_show=False,
            formatter=JsCode("function(data){return data.name + " " + data.value[2];}"),
        ),
        
        # 高亮标签配置项
        emphasis_label_opts=opts.LabelOpts(
            is_show=False,
            color="#fff",
            font_size=10,
            background_color="rgba(0,23,11,0)",
        ),
        
        # 光照相关的设置。
        light_opts=opts.Map3DLightOpts(
            main_color="#fff",
            main_intensity=1.2,
            main_shadow_quality="high",
            is_main_shadow=False,
            main_beta=10,
            ambient_intensity=0.3,
        ),
    )
    .add(
        series_name="门店数量",
        data_pair=datas,
        # 叠加图的类型
        type_=ChartType.BAR3D,
        bar_size=1,
        
        # 三维地图中三维图形的着色效果。
        shading="lambert",
        label_opts=opts.LabelOpts(
            is_show=False,
            formatter=JsCode("function(data){return data.name + ' ' + data.value[2];}"),
        ),
    )
    .set_global_opts(title_opts=opts.TitleOpts(title="星巴克门店在中国的分布3D图"))
    .render("map3d_with_bar3d.html")
)
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