1. 2D 세계지도 생성

from pyecharts import options as opts
from pyecharts.charts import Map
from pyecharts.faker import Faker

world_map = (
    Map(init_opts=opts.InitOpts(width='1500px', height='1200px', bg_color='#E0EEEE'))
    .add("국가별 데이터", [list(z) for z in zip(Faker.country, Faker.values())], "world")
    .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
    .set_global_opts(
        title_opts=opts.TitleOpts(title="세계 지도 예시"),
        visualmap_opts=opts.VisualMapOpts(max_=200)
    )
    .render("global_map.html")
)

이 코드는 전 세계 국가의 가상 데이터를 기반으로 2D 지도를 렌더링합니다.

2. 중국 3D 행정 구역 지도

from pyecharts import options as opts
from pyecharts.charts import Map3D
from pyecharts.globals import ChartType

china_3d_map = (
    Map3D(init_opts=opts.InitOpts(width='1300px', height='1300px', bg_color='#EBEBEB'))
    .add_schema(
        itemstyle_opts=opts.ItemStyleOpts(
            color="#CDBA96",
            opacity=1,
            border_width=0.8,
            border_color="rgb(62,215,213)",
        ),
        map3d_label=opts.Map3DLabelOpts(
            is_show=True,
            text_style=opts.TextStyleOpts(
                color="#104E8B", font_size=16, background_color="rgba(0,0,0,0)"
            ),
        ),
        emphasis_label_opts=opts.LabelOpts(is_show=True),
        light_opts=opts.Map3DLightOpts(
            main_color="#FFEBCD",
            main_intensity=1.2,
            is_main_shadow=False,
            main_alpha=55,
            main_beta=10,
            ambient_intensity=0.3,
        ),
    )
    .add(series_name="", data_pair="", maptype=ChartType.MAP3D)
    .set_global_opts(
        title_opts=opts.TitleOpts(title="중국 행정구역 3D 지도"),
        visualmap_opts=opts.VisualMapOpts(is_show=False),
        tooltip_opts=opts.TooltipOpts(is_show=True),
    )
    .render("china_map3d.html")
)

3. 귀주성 3D 지도 표현

example_coordinates = [
    [[106.70722, 26.59820, 1000], [106.63024, 26.64702, 1000]],
    [[104.83023, 26.59336], [106.92723, 27.72545]],
    [[105.30504, 27.29847], [107.52034, 26.29322]],
    [[107.89868, 26.52881], [104.948571, 25.077502]],
    [[105.9462, 26.25367], [109.18099, 27.69066]],
]

guizhou_3d = (
    Map3D(init_opts=opts.InitOpts(width='1200px', height='1200px'))
    .add_schema(
        maptype="귀주",
        itemstyle_opts=opts.ItemStyleOpts(
            color="rgb(5,101,123)",
            opacity=1,
            border_width=0.8,
            border_color="rgb(62,215,213)",
        ),
        light_opts=opts.Map3DLightOpts(
            main_color="#fff",
            main_intensity=1.2,
            is_main_shadow=True,
            main_alpha=55,
            main_beta=10,
            ambient_intensity=0.3,
        ),
        view_control_opts=opts.Map3DViewControlOpts(center=[-10, 0, 10]),
        post_effect_opts=opts.Map3DPostEffectOpts(is_enable=True),
    )
    .add(
        series_name="경로 데이터",
        data_pair=example_coordinates,
        type_=ChartType.LINES3D,
        effect=opts.Lines3DEffectOpts(
            is_show=True,
            period=4,
            trail_width=3,
            trail_length=0.5,
            trail_color="#f00",
            trail_opacity=1,
        ),
        label_opts=opts.LabelOpts(is_show=True),
    )
    .set_global_opts(title_opts=opts.TitleOpts(title="귀주성 3D 경로 지도"))
    .render("guizhou_lines3d.html")
)

4. 3D 지구 시각화 (지구촌)

import pyecharts.options as opts
from pyecharts.charts import MapGlobe
from pyecharts.faker import POPULATION

population_data = [x for _, x in POPULATION[1:]]
min_val, max_val = min(population_data), max(population_data)

earth_globe = (
    MapGlobe(init_opts=opts.InitOpts(width='1000px', height='1000px', bg_color='#FFFAFA'))
    .add_schema()
    .add(
        maptype="world",
        series_name="세계 인구 분포",
        data_pair=POPULATION[1:],
        is_map_symbol_show=True,
        label_opts=opts.LabelOpts(is_show=True),
    )
    .set_global_opts(
        title_opts=opts.TitleOpts(title="3D 지구 시각화 예제"),
        visualmap_opts=opts.VisualMapOpts(
            min_=min_val,
            max_=max_val,
            range_text=["최대", "최소"],
            is_calculable=True,
            range_color=["lightskyblue", "yellow", "orangered"],
        )
    )
    .render("earth_population.html")
)