主要是以下几点:
(一)、 pyecharts绘制树图;
(二)、 散点图矩阵绘制;
(三)、 词云图、主题河流图、文本关系图的绘制;
(四)、 地理热力图、地图上标注点的绘制
1、使用以下JSON数据绘制树图、矩形树图。
树图:
from pyecharts import options as opts
from pyecharts.charts import Tree
data = [{
"name": "flare",
"children": [
{
"name": "flex",
"children": [
{
"name": "FlareVis", "value": 4116}
]
},
{
"name": "scale",
"children": [
{
"name": "IScaleMap", "value": 2105},
{
"name": "LinearScale", "value": 1316},
{
"name": "LogScale", "value": 3151},
{
"name": "OrdinalScale", "value": 3770},
{
"name": "QuantileScale", "value": 2435},
{
"name": "QuantitativeScale", "value": 4839},
{
"name": "RootScale", "value": 1756},
{
"name": "Scale", "value": 4268},
{
"name": "ScaleType", "value": 1821},
{
"name": "TimeScale", "value": 5833}
]
},
{
"name": "display",
"children": [
{
"name": "DirtySprite", "value": 8833}
]
}
]
}]
c = (
Tree()
.add("", data)
.set_global_opts(title_opts=opts.TitleOpts(title="Tree"))
.render("tree_base.html")
)
结果如下图:
矩形树图:
from pyecharts import options as opts
from pyecharts.charts import TreeMap
data = [{
"name": "flare",
"children": [
{
"name": "flex",
"children": [
{
"name": "FlareVis", "value": 4116}
]
},
{
"name": "scale",
"children": [
{
"name": "IScaleMap", "value": 2105},
{
"name": "LinearScale", "value": 1316},
{
"name": "LogScale", "value": 3151},
{
"name": "OrdinalScale", "value": 3770},
{
"name": "QuantileScale", "value": 2435},
{
"name": "QuantitativeScale", "value": 4839},
{
"name": "RootScale", "value": 1756},
{
"name": "Scale", "value": 4268},

本文介绍了使用pyecharts进行数据可视化的多个示例,包括树图、散点图矩阵、词云图、主题河流图、地理热力图以及地图标注,通过具体案例展示了pyecharts在数据展现上的应用。
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