web实战基础（pycharts篇）：pycharts基础知识科普和案例解析
这是一篇非常非常基础的入门教程，但是也能让你深入了解pycharts的实现机制和带着你深入了解细节的设计，因此非常建议你能看完，相信一定会有所收获！
让我们一起加油，加加油！
文章目录
- 一、pycharts简介
- （一）特性
- （二）安装
- （三）查看版本
- 二、入门案例
- 三、定制主题
- 四、options 配置项
- 五、柱形图Bar
- （一）增加多一个数据列
- （二）实现堆叠效果
- （三）实现堆叠效果（部分）
- （四）回到标题栏
- （五）继续坐标轴
- （六）设置是否显示数值
- （七）区域选择
- （八）区域缩放
- 1、水平选择
- 2、垂直选择
- （九）工具栏设置
- （十）tip侧边条
- （十一）自定义颜色
- （十二）增加背景图
- （十三）设置markpoint
- （十四）设置markline
- （十五）保存成图片
一、pycharts简介
python 擅于数据处理，echarts 是百度开源的数据可视化项目，将二者结合起来，也就诞生了 pyecharts 。
（一）特性
简洁的 API 设计，使用如丝滑般流畅，支持链式调用
囊括了 30+ 种常见图表，应有尽有
支持主流 Notebook环境，Jupyter Notebook 和 JupyterLab
可轻松集成至 Flask，Django 等主流 Web 框架
高度灵活的配置项，可轻松搭配出精美的图表
（二）安装
pip install pyecharts
如果下载较慢，可以换用下面方法：
pip install pyecharts -i https://pypi.tuna.tsinghua.edu.cn/simple
（三）查看版本
import pyecharts
print(pyecharts.__version__)
建议使用pyecharts1.x的版本。
二、入门案例
from pyecharts.charts import Bar
from pyecharts import options as opts
# 内置主题类型可查看 pyecharts.globals.ThemeType
from pyecharts.globals import ThemeType
bar = (
Bar(init_opts=opts.InitOpts(theme=ThemeType.LIGHT))
.add_xaxis(["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"])
.add_yaxis("商家A", [5, 20, 36, 10, 75, 90])
.set_global_opts(title_opts=opts.TitleOpts(title="主标题", subtitle="副标题"))
# 或者直接使用字典参数
# .set_global_opts(title_opts={"text": "主标题", "subtext": "副标题"})
)
bar.render('templates\index.html')
# # 不习惯链式调用的开发者依旧可以单独调用方法
# bar = Bar(init_opts=opts.InitOpts(theme=ThemeType.LIGHT))
# bar.add_xaxis(["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"])
# bar.add_yaxis("商家A", [5, 20, 36, 10, 75, 90])
# bar.set_global_opts(title_opts=opts.TitleOpts(title="主标题", subtitle="副标题"))
# bar.render()
里面有三个点需要关注：
1、初始化图形，可以使用常规的对象赋值的方式，也可以采用链式调用的方式进行设置。
2、如果需要使用内置的主题类型可在初始化时进行设置。内置主题类型可查看 pyecharts.globals.ThemeType。
3、如果需要把生成的图形保存成图片，可以使用函数make_snapshot进行生成。
最终出来的效果如下：
三、定制主题
pyechart给使用用户提供了一套主题样式，使用户对其的使用更加方便。
可以通过如下代码查看：
from pyecharts.globals import ThemeType
help(ThemeType)
如果要使用主题，可以使用如下代码进行设置：
from pyecharts.globals import ThemeType
init_opts=opts.InitOpts(theme=ThemeType.LIGHT)
包括如下10+种的主题样式：
| BUILTIN_THEMES = ['light', 'dark', 'white']
|
| CHALK = 'chalk'
|
| DARK = 'dark'
|
| ESSOS = 'essos'
|
| INFOGRAPHIC = 'infographic'
|
| LIGHT = 'light'
|
| MACARONS = 'macarons'
|
| PURPLE_PASSION = 'purple-passion'
|
| ROMA = 'roma'
|
| ROMANTIC = 'romantic'
|
| SHINE = 'shine'
|
| VINTAGE = 'vintage'
|
| WALDEN = 'walden'
|
| WESTEROS = 'westeros'
|
| WHITE = 'white'
|
| WONDERLAND = 'wonderland'
四、options 配置项
在 pyecharts 中，一切皆 Options。
全局配置项可通过
set_global_options方法设置。
局部配置项可通过set_series_opts方法设置。
五、柱形图Bar
基于上述的配置项，对入门案例进行拓展。
（一）增加多一个数据列
from pyecharts.charts import Bar
from pyecharts import options as opts
from pyecharts.globals import ThemeType
bar = (
Bar(init_opts=opts.InitOpts(theme=ThemeType.LIGHT))
.add_xaxis(["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"])
.add_yaxis("商家A", [5, 20, 36, 10, 75, 90])
.add_yaxis("商家B", [15, 25, 30, 18,65, 70])
.set_global_opts(title_opts=opts.TitleOpts(title="主标题", subtitle="副标题"))
)
bar.render('templates\index.html')
（二）实现堆叠效果
from pyecharts.charts import Bar
from pyecharts import options as opts
from pyecharts.globals import ThemeType
bar = (
Bar(init_opts=opts.InitOpts(theme=ThemeType.LIGHT))
.add_xaxis(["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"])
.add_yaxis("商家A", [5, 20, 36, 10, 75, 90], stack="stack1")
.add_yaxis("商家B", [15, 25, 30, 18,65, 70], stack="stack1")
.set_global_opts(title_opts=opts.TitleOpts(title="主标题", subtitle="副标题"))
)
bar.render('templates\index.html')
（三）实现堆叠效果（部分）
from pyecharts.charts import Bar
from pyecharts import options as opts
from pyecharts.globals import ThemeType
bar = (
Bar(init_opts=opts.InitOpts(theme=ThemeType.LIGHT))
.add_xaxis(["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"])
.add_yaxis("商家A", [5, 20, 36, 10, 75, 90], stack="stack1")
.add_yaxis("商家B", [15, 25, 30, 18,65, 70], stack="stack1")
.add_yaxis("商家C", [25, 15, 50, 38,25, 20])
.set_global_opts(title_opts=opts.TitleOpts(title="主标题", subtitle="副标题"))
)
bar.render('templates\index.html')
（四）回到标题栏
通过修改TitleOpts：标题配置项进行设置。
from pyecharts.charts import Bar
from pyecharts import options as opts
from pyecharts.globals import ThemeType
bar = (
Bar(init_opts=opts.InitOpts(theme=ThemeType.LIGHT))
.add_xaxis(["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"])
.add_yaxis("商家A", [5, 20, 36, 10, 75, 90], stack="stack1")
.add_yaxis("商家B", [15, 25, 30, 18,65, 70], stack="stack1")
.add_yaxis("商家C", [25, 15, 50, 38,25, 20])
.set_global_opts(title_opts=opts.TitleOpts(title="我的柱状图", subtitle="hello bar",pos_left=100))
)
bar.render('templates\index.html')
（五）继续坐标轴
通过修改AxisOpts：坐标轴配置项进行设置。
from pyecharts.charts import Bar
from pyecharts import options as opts
from pyecharts.globals import ThemeType
bar = (
Bar(init_opts=opts.InitOpts(theme=ThemeType.LIGHT))
.add_xaxis(["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"])
.add_yaxis("商家A", [5, 20, 36, 10, 75, 90], stack="stack1")
.add_yaxis("商家B", [15, 25, 30, 18,65, 70], stack="stack1")
.add_yaxis("商家C", [25, 15, 50, 38,25, 20])
.set_global_opts(
xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=-15)),
title_opts=opts.TitleOpts(title="我的柱状图", subtitle="hello bar",pos_left=100)
)
)
bar.render('templates\index.html')
（六）设置是否显示数值
换一个主题风格theme=ThemeType.DARK，好看些！
from pyecharts.charts import Bar
from pyecharts import options as opts
from pyecharts.globals import ThemeType
bar = (
Bar(init_opts=opts.InitOpts(theme=ThemeType.DARK))
.add_xaxis(["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"])
.add_yaxis("商家A", [5, 20, 36, 10, 75, 90], stack="stack1")
.add_yaxis("商家B", [15, 25, 30, 18,65, 70], stack="stack1")
.add_yaxis("商家C", [25, 15, 50, 38,25, 20])
.set_series_opts(label_opts=opts.LabelOpts(is_show=True,position="inside"))
.set_global_opts(
# xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=-15)),
title_opts=opts.TitleOpts(title="我的柱状图", subtitle="hello bar",pos_left=100)
)
)
bar.render('templates\index.html')
（七）区域选择
通过设置BrushOpts：区域选择组件配置项进行设置
from pyecharts.charts import Bar
from pyecharts import options as opts
from pyecharts.globals import ThemeType
bar = (
Bar(init_opts=opts.InitOpts(theme=ThemeType.DARK))
.add_xaxis(["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"])
.add_yaxis("商家A", [5, 20, 36, 10, 75, 90], stack="stack1")
.add_yaxis("商家B", [15, 25, 30, 18,65, 70], stack="stack1")
.add_yaxis("商家C", [25, 15, 50, 38,25, 20])
.set_series_opts(label_opts=opts.LabelOpts(is_show=True,position="inside"))
.set_global_opts(
brush_opts=opts.BrushOpts(),
title_opts=opts.TitleOpts(title="我的柱状图", subtitle="hello bar",pos_left=100)
)
)
bar.render('templates\index.html')
（八）区域缩放
1、水平选择
通过DataZoomOpts：区域缩放配置项设置，可以直接在鼠标进行图形缩放。
from pyecharts.charts import Bar
from pyecharts import options as opts
from pyecharts.globals import ThemeType
bar = (
Bar(init_opts=opts.InitOpts(theme=ThemeType.DARK))
.add_xaxis(["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"])
.add_yaxis("商家A", [5, 20, 36, 10, 75, 90], stack="stack1")
.add_yaxis("商家B", [15, 25, 30, 18,65, 70], stack="stack1")
.add_yaxis("商家C", [25, 15, 50, 38,25, 20])
.set_series_opts(label_opts=opts.LabelOpts(is_show=True,position="inside"))
.set_global_opts(
brush_opts=opts.BrushOpts(),
datazoom_opts=opts.DataZoomOpts(),
title_opts=opts.TitleOpts(title="我的柱状图", subtitle="hello bar",pos_left=100)
)
)
bar.render('templates\index.html')
2、垂直选择
from pyecharts.charts import Bar
from pyecharts import options as opts
from pyecharts.globals import ThemeType
bar = (
Bar(init_opts=opts.InitOpts(theme=ThemeType.DARK))
.add_xaxis(["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"])
.add_yaxis("商家A", [5, 20, 36, 10, 75, 90], stack="stack1")
.add_yaxis("商家B", [15, 25, 30, 18,65, 70], stack="stack1")
.add_yaxis("商家C", [25, 15, 50, 38,25, 20])
.set_series_opts(label_opts=opts.LabelOpts(is_show=True,position="inside"))
.set_global_opts(
brush_opts=opts.BrushOpts(),
# datazoom_opts=opts.DataZoomOpts(),
datazoom_opts=opts.DataZoomOpts(orient="vertical"),
title_opts=opts.TitleOpts(title="我的柱状图", subtitle="hello bar",pos_left=100),
yaxis_opts=opts.AxisOpts(name="我是 Y 轴"),
xaxis_opts = opts.AxisOpts(name="我是 X 轴"),
)
)
bar.render('templates\index.html')
（九）工具栏设置
from pyecharts.charts import Bar
from pyecharts import options as opts
from pyecharts.globals import ThemeType
bar = (
Bar(init_opts=opts.InitOpts(theme=ThemeType.DARK))
.add_xaxis(["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"])
.add_yaxis("商家A", [5, 20, 36, 10, 75, 90], stack="stack1")
.add_yaxis("商家B", [15, 25, 30, 18,65, 70], stack="stack1")
.add_yaxis("商家C", [25, 15, 50, 38,25, 20])
.set_series_opts(label_opts=opts.LabelOpts(is_show=True,position="inside"))
.set_global_opts(
brush_opts=opts.BrushOpts(),
datazoom_opts=opts.DataZoomOpts(),
toolbox_opts=opts.ToolboxOpts(),
title_opts=opts.TitleOpts(title="我的柱状图", subtitle="hello bar",pos_left=100)
)
)
bar.render('templates\index.html')
（十）tip侧边条
from pyecharts.charts import Bar
from pyecharts import options as opts
from pyecharts.globals import ThemeType
from pyecharts.commons.utils import JsCode
bar = (
Bar(init_opts=opts.InitOpts(theme=ThemeType.DARK))
.add_xaxis(["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"])
.add_yaxis("商家A", [5, 20, 36, 10, 75, 60], stack="stack1")
.add_yaxis("商家B", [15, 25, 30, 18,65, 70], stack="stack1")
.add_yaxis("商家C", [25, 15, 50, 38,25, 20])
.set_series_opts(label_opts=opts.LabelOpts(is_show=True,position="inside"))
.set_global_opts(
brush_opts=opts.BrushOpts(),
datazoom_opts=opts.DataZoomOpts(),
toolbox_opts=opts.ToolboxOpts(),
title_opts=opts.TitleOpts(title="我的柱状图", subtitle="hello bar",pos_left=100),
graphic_opts=[
opts.GraphicGroup(
graphic_item=opts.GraphicItem(
rotation=JsCode("Math.PI / 4"),
bounding = "raw",
right = 110,
bottom = 110,
z = 100,
),
children = [
opts.GraphicRect(
graphic_item=opts.GraphicItem(
left="center", top="center", z=100
),
graphic_shape_opts=opts.GraphicShapeOpts(width=400, height=50),
graphic_basicstyle_opts=opts.GraphicBasicStyleOpts(
fill="rgba(0,0,0,0.3)"
),
),
opts.GraphicText(
graphic_item=opts.GraphicItem(
left="center", top="center", z=100
),
graphic_textstyle_opts=opts.GraphicTextStyleOpts(
text="pyecharts bar chart",
font="bold 26px Microsoft YaHei",
graphic_basicstyle_opts=opts.GraphicBasicStyleOpts(
fill="#fff"
),
),
),
],
)
]
)
)
bar.render('templates\index.html')
（十一）自定义颜色
from pyecharts.charts import Bar
from pyecharts import options as opts
from pyecharts.globals import ThemeType
from pyecharts.commons.utils import JsCode
color_function = """
function (params) {
if (params.value > 0 && params.value < 50) {
return 'red';
} else if (params.value > 50 && params.value < 100) {
return 'blue';
}
return 'green';
}
"""
bar = (
Bar(init_opts=opts.InitOpts(theme=ThemeType.LIGHT))
.add_xaxis(["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"])
.add_yaxis("商家A", [5, 20, 36, 10, 75, 90],
itemstyle_opts=opts.ItemStyleOpts(color=JsCode(color_function)))
.add_yaxis("商家C", [25, 15, 50, 38,25, 20],
itemstyle_opts=opts.ItemStyleOpts(color=JsCode(color_function)))
.set_series_opts(label_opts=opts.LabelOpts(is_show=True,position="inside"))
.set_global_opts(
title_opts=opts.TitleOpts(title="我的柱状图", subtitle="hello bar",pos_left=100),
)
)
bar.render('templates\index.html')
（十二）增加背景图
from pyecharts.charts import Bar
from pyecharts import options as opts
from pyecharts.globals import ThemeType
from pyecharts.commons.utils import JsCode
bar = (
Bar(init_opts=opts.InitOpts(
bg_color={"type": "pattern", "image": JsCode("img"), "repeat": "no-repeat"}
))
.add_xaxis(["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"])
.add_yaxis("商家A", [5, 20, 36, 10, 75, 90], stack="stack1")
.add_yaxis("商家B", [15, 25, 30, 18,65, 70], stack="stack1")
.add_yaxis("商家C", [25, 15, 50, 38,25, 20])
.set_series_opts(label_opts=opts.LabelOpts(is_show=True,position="inside"))
.set_global_opts(
title_opts=opts.TitleOpts(title="我的柱状图", subtitle="hello bar",pos_left=100,title_textstyle_opts=opts.TextStyleOpts(color="white"),),
)
)
bar.add_js_funcs(
"""
var img = new Image(); img.src = 'static/1.jpg';
"""
)
bar.render('templates\index.html')
（十三）设置markpoint
通过修改MarkPointItem：标记点数据项进行设置。
from pyecharts.charts import Bar
from pyecharts import options as opts
from pyecharts.globals import ThemeType
from pyecharts.commons.utils import JsCode
bar = (
Bar(init_opts=opts.InitOpts(theme=ThemeType.LIGHT))
.add_xaxis(["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"])
.add_yaxis("商家A", [5, 20, 36, 10, 75, 90])
.add_yaxis("商家B", [15, 25, 30, 18,65, 70])
.set_series_opts(
label_opts=opts.LabelOpts(is_show=False),
markpoint_opts = opts.MarkPointOpts(
data=[
opts.MarkPointItem(type_="max", name="最大值"),
opts.MarkPointItem(type_="min", name="最小值"),
opts.MarkPointItem(type_="average", name="平均值"),
]
),
)
.set_global_opts(
title_opts=opts.TitleOpts(title="我的柱状图", subtitle="hello bar",pos_left=100),
)
)
bar.render('templates\index.html')
（十四）设置markline
通过修改MarkLineItem：标记线数据项进行设置
from pyecharts.charts import Bar
from pyecharts import options as opts
from pyecharts.globals import ThemeType
from pyecharts.commons.utils import JsCode
bar = (
Bar(init_opts=opts.InitOpts(theme=ThemeType.LIGHT))
.add_xaxis(["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"])
.add_yaxis("商家A", [5, 20, 36, 10, 75, 90])
.add_yaxis("商家B", [15, 25, 30, 18,65, 70])
.set_series_opts(
label_opts=opts.LabelOpts(is_show=True),
markline_opts=opts.MarkLineOpts(
data=[opts.MarkLineItem(y=30, name="yAxis=30")],
symbol_size=[20,10],
linestyle_opts=opts.LineStyleOpts(color='red',width=2)
),
)
.set_global_opts(
title_opts=opts.TitleOpts(title="我的柱状图", subtitle="hello bar",pos_left=100),
)
)
bar.render('templates\index.html')
（十五）保存成图片
from pyecharts.charts import Bar
from pyecharts import options as opts
# 渲染图片
from pyecharts.render import make_snapshot
# 使用 snapshot-selenium 渲染图片
from snapshot_selenium import snapshot
# 内置主题类型可查看 pyecharts.globals.ThemeType
from pyecharts.globals import ThemeType
bar = (
Bar(init_opts=opts.InitOpts(theme=ThemeType.LIGHT))
.add_xaxis(["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"])
.add_yaxis("商家A", [5, 20, 36, 10, 75, 90])
.set_global_opts(title_opts=opts.TitleOpts(title="主标题", subtitle="副标题"))
# 或者直接使用字典参数
# .set_global_opts(title_opts={"text": "主标题", "subtext": "副标题"})
)
make_snapshot(snapshot, bar.render(), "bar.png")
核心的代码如下：
#渲染图片
from pyecharts.render import make_snapshot
#使用 snapshot-selenium 渲染图片
from snapshot_selenium import snapshot
make_snapshot(snapshot, bar.render(), "bar.png")
OK，写了这么多，本来打算一篇写完的，但是发现里面的知识点太多，只写完了关于柱状图（Bar）的部分，后续我将会继续介绍常见的其他图形（如饼图、仪表盘等）的实现方式，敬请期待。
感谢你的关注！
参考：https://pyecharts.org/#/zh-cn/intro