时间:2023-02-14 10:22:47 | 栏目:Python代码 | 点击:次
之前我们介绍了很多Python地图可视化的内容,本次主要介绍如何Python绘制3D地图,还是比较神奇的,下面让我们一起一饱眼福吧!
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") )
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") )
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。
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") )
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!