炫酷地图
前期我们介绍了很多的地图模板，不管是全球的还是中国的，其实我感觉都十分的炫酷，哈哈哈，可是还有更加神奇的，更加炫酷的地图模板，下面让我们一起一饱眼福吧！
3D炫酷地图模板系列
重庆市3D地图展示
from pyecharts import options as opts
from pyecharts.charts import Map3D
from pyecharts.globals import ChartType
# 经纬度
example_data = [
[[119.107078, 36.70925, 1000], [116.587245, 35.415393, 1000]],
[[117.000923, 36.675807], [120.355173, 36.082982]],
[[118.047648, 36.814939], [118.66471, 37.434564]],
[[121.391382, 37.539297], [119.107078, 36.70925]],
[[116.587245, 35.415393], [122.116394, 37.509691]],
[[119.461208, 35.428588], [118.326443, 35.065282]],
[[116.307428, 37.453968], [115.469381, 35.246531]],
]
c = (
Map3D(init_opts=opts.InitOpts(width="1400px", height="700px"))
.add_schema(
maptype="重庆",
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=False,
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=False),
)
.add(
series_name="",
data_pair=example_data,
type_=ChartType.LINES3D,
effect=opts.Lines3DEffectOpts(
is_show=True,
period=4,
trail_width=3,
trail_length=0.5,
trail_color="#f00",
trail_opacity=1,
),
linestyle_opts=opts.LineStyleOpts(is_show=False, color="#fff", opacity=0),
)
.set_global_opts(title_opts=opts.TitleOpts(title="Map3D"))
.render("区县3D地图.html")
)
中国3D地图
数组里面分别代表：经纬度，数值
from pyecharts import options as opts
from pyecharts.charts import Map3D
from pyecharts.globals import ChartType
from pyecharts.commons.utils import JsCode
example_data = [
("黑龙江", [127.9688, 45.368, 100]),
("内蒙古", [110.3467, 41.4899, 100]),
("吉林", [125.8154, 44.2584, 100]),
("辽宁", [123.1238, 42.1216, 100]),
("河北", [114.4995, 38.1006, 100]),
("天津", [117.4219, 39.4189, 100]),
("山西", [112.3352, 37.9413, 100]),
("陕西", [109.1162, 34.2004, 100]),
("甘肃", [103.5901, 36.3043, 100]),
("宁夏", [106.3586, 38.1775, 100]),
("青海", [101.4038, 36.8207, 100]),
("新疆", [87.9236, 43.5883, 100]),
("西藏", [91.11, 29.97, 100]),
("四川", [103.9526, 30.7617, 100]),
("重庆", [108.384366, 30.439702, 100]),
("山东", [117.1582, 36.8701, 100]),
("河南", [113.4668, 34.6234, 100]),
("江苏", [118.8062, 31.9208, 100]),
("安徽", [117.29, 32.0581, 100]),
("湖北", [114.3896, 30.6628, 100]),
("浙江", [119.5313, 29.8773, 100]),
("福建", [119.4543, 25.9222, 100]),
("江西", [116.0046, 28.6633, 100]),
("湖南", [113.0823, 28.2568, 100]),
("贵州", [106.6992, 26.7682, 100]),
("广西", [108.479, 23.1152, 100]),
("海南", [110.3893, 19.8516, 100]),
("上海", [121.4648, 31.2891, 100]),
]
c = (
Map3D(init_opts=opts.InitOpts(width="1400px", height="700px"))
.add_schema(
itemstyle_opts=opts.ItemStyleOpts(
color="rgb(5,101,123)",
opacity=1,
border_width=0.8,
border_color="rgb(62,215,213)",
),
map3d_label=opts.Map3DLabelOpts(
is_show=False,
formatter=JsCode("function(data){return data.name + " " + data.value[2];}"),
),
emphasis_label_opts=opts.LabelOpts(
is_show=False,
color="#fff",
font_size=10,
background_color="rgba(0,23,11,0)",
),
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="Scatter3D",
data_pair=example_data,
type_=ChartType.SCATTER3D,
bar_size=1,
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="Map3D"))
.render("中国3D地图.html")
)
中国3D数据地图（适合做数据可视化）
如果说前面的那个你看起来不太舒服，那么这个绝对适合做数据可视化展示哟！
from pyecharts import options as opts
from pyecharts.charts import Map3D
from pyecharts.globals import ChartType
from pyecharts.commons.utils import JsCode
example_data = [
("黑龙江", [127.9688, 45.368, 100]),
("内蒙古", [110.3467, 41.4899, 300]),
("吉林", [125.8154, 44.2584, 300]),
("辽宁", [123.1238, 42.1216, 300]),
("河北", [114.4995, 38.1006, 300]),
("天津", [117.4219, 39.4189, 300]),
("山西", [112.3352, 37.9413, 300]),
("陕西", [109.1162, 34.2004, 300]),
("甘肃", [103.5901, 36.3043, 300]),
("宁夏", [106.3586, 38.1775, 300]),
("青海", [101.4038, 36.8207, 300]),
("新疆", [87.9236, 43.5883, 300]),
("西藏", [91.11, 29.97, 300]),
("四川", [103.9526, 30.7617, 300]),
("重庆", [108.384366, 30.439702, 300]),
("山东", [117.1582, 36.8701, 300]),
("河南", [113.4668, 34.6234, 300]),
("江苏", [118.8062, 31.9208, 300]),
("安徽", [117.29, 32.0581, 300]),
("湖北", [114.3896, 30.6628, 300]),
("浙江", [119.5313, 29.8773, 300]),
("福建", [119.4543, 25.9222, 300]),
("江西", [116.0046, 28.6633, 300]),
("湖南", [113.0823, 28.2568, 300]),
("贵州", [106.6992, 26.7682, 300]),
("广西", [108.479, 23.1152, 300]),
("海南", [110.3893, 19.8516, 300]),
("上海", [121.4648, 31.2891, 1300]),
]
c = (
Map3D(init_opts=opts.InitOpts(width="1400px", height="700px"))
.add_schema(
itemstyle_opts=opts.ItemStyleOpts(
color="rgb(5,101,123)",
opacity=1,
border_width=0.8,
border_color="rgb(62,215,213)",
),
map3d_label=opts.Map3DLabelOpts(
is_show=False,
formatter=JsCode("function(data){return data.name + " " + data.value[2];}"),
),
emphasis_label_opts=opts.LabelOpts(
is_show=False,
color="#fff",
font_size=10,
background_color="rgba(0,23,11,0)",
),
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="数据",
data_pair=example_data,
type_=ChartType.BAR3D,
bar_size=1,
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="城市数据"))
.render("带有数据展示地图.html")
)
看完直呼这个模板，适合做城市之间的数据对，同时也展示了经纬度。
全国行政区地图（带城市名字）
from pyecharts import options as opts
from pyecharts.charts import Map3D
from pyecharts.globals import ChartType
c = (
Map3D(init_opts=opts.InitOpts(width="1400px", height="700px"))
.add_schema(
itemstyle_opts=opts.ItemStyleOpts(
color="rgb(5,101,123)",
opacity=1,
border_width=0.8,
border_color="rgb(62,215,213)",
),
map3d_label=opts.Map3DLabelOpts(
is_show=True,
text_style=opts.TextStyleOpts(
color="#fff", font_size=16, background_color="rgba(0,0,0,0)"
),
),
emphasis_label_opts=opts.LabelOpts(is_show=True),
light_opts=opts.Map3DLightOpts(
main_color="#fff",
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="全国行政区划地图-Base"),
visualmap_opts=opts.VisualMapOpts(is_show=False),
tooltip_opts=opts.TooltipOpts(is_show=True),
)
.render("全国标签地图.html")
)
地球展示
import pyecharts.options as opts
from pyecharts.charts import MapGlobe
from pyecharts.faker import POPULATION
data = [x for _, x in POPULATION[1:]]
low, high = min(data), max(data)
c = (
MapGlobe(init_opts=opts.InitOpts(width="1400px", height="700px"))
.add_schema()
.add(
maptype="world",
series_name="World Population",
data_pair=POPULATION[1:],
is_map_symbol_show=False,
label_opts=opts.LabelOpts(is_show=False),
)
.set_global_opts(
visualmap_opts=opts.VisualMapOpts(
min_=low,
max_=high,
range_text=["max", "min"],
is_calculable=True,
range_color=["lightskyblue", "yellow", "orangered"],
)
)
.render("地球.html")
)
其实pyecharts还可以做百度地图，可以缩放定位到每一个区域，但是其实我们在日常生活中可能用不上，如果要用可以去百度地图展示效果或者学习练习也是可的
到此这篇关于Python可视化神器pyecharts之绘制地理图表的文章就介绍到这了,更多相关Python绘制地理图表内容请搜索编程网以前的文章或继续浏览下面的相关文章希望大家以后多多支持编程网！
