python做可视化数据图表,python绘制可视化图表_python echart

pyecharts可视化

pyecharts是基于Echart图表的一个类库，而Echart是百度开源的一个可视化JavaScript库。

简介：
pyecharts主要基于web浏览器进行显示，绘制的图形比较多，包括折线图、柱状图、饼图、漏斗图、地图、极坐标图等，代码量很少，而且很灵活，绘制出来的图形很美观python用turtle画简单树形图。

使用pyecharts时，需要安装相应的库，安装命令为：
pip install pyecharts

图形绘制过程，基本上所有的图表类型都是这样绘制的：

chart_name = Type()      #初始化具体类型图表
chart_name .add()         #添加数据及配置项
chart_name .render() 
#生成本地文件（html/svg/jpeg/png/pdf/gif）
chart_name .render_notebook  #在jupyter notebook中显示

常用图表绘制

柱状图

利用Bar方法可以绘制柱状图

from pyecharts.charts import Bar
from pyecharts import options as opts
%matplotlib inline
# V1 版本开始支持链式调用
bar = ( Bar()
       .add_xaxis(["衬衫", "毛衣", "领带", "裤子", "风衣", "高跟鞋", "袜子"])
       .add_yaxis("商家A", [114, 55, 27, 101, 125, 27, 105])
       .set_global_opts(title_opts = opts.TitleOpts(title = "某商场销售情况")) )
bar.render_notebook()
#bar.render() 生成html

V1版本开始支持链式调用，如果不习惯链式调用的开发者依旧可以单独调用方法，上面代码为：
使用多个add_yaxis可以绘制并列柱状图。

bar = Bar()
bar.add_xaxis(["衬衫", "毛衣", "领带", "裤子", "风衣", "高跟鞋", "袜子"])
bar.add_yaxis("商家A", [114, 55, 27, 101, 125, 27, 105])
bar.set_global_opts(title_opts = opts.TitleOpts(title = "某商场销售情况"))
bar.render_notebook()

from pyecharts.charts import Bar
from pyecharts import options as opts
%matplotlib inline
bar = Bar()
bar.add_xaxis(["衬衫", "毛衣", "领带", "裤子", "风衣", "高跟鞋", "袜子"])
bar.add_yaxis("商家A", [114, 55, 27, 101, 125, 27, 105])
bar.add_yaxis("商家B", [57, 134, 137, 129, 145, 60, 49])
bar.set_global_opts(title_opts = opts.TitleOpts(title = "货品销售情况",subtitle  =  "A和B公司"))
bar.render_notebook()

饼图

饼图常用于表现不同类别的占比情况。利用Pie方法可以绘制饼图。

from pyecharts import options as opts    
from pyecharts.charts import Page, Pie
L1=['教授','副教授','讲师','助教','其他']
num  = [20,30,10,12,8]
c = Pie()
c.add("", [list(z) for z in zip(L1,num)])
c.set_global_opts(title_opts=opts.TitleOpts(title="Pie-职称类别比例"))
c.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}"))
c.render_notebook()

通过参数圆形饼图radius可以绘制圆形饼图。

from pyecharts import options as opts
from pyecharts.charts import Page, Pie
wd = ['教授','副教授','讲师','助教','其他']
num = [20,30,10,12,8]
c = Pie()
c.add("",[list(z) for z in zip(wd, num)],radius = ["40%", "75%"])   
# 圆环的粗细和大小
c.set_global_opts( title_opts=opts.TitleOpts(title="Pie-Radius"),legend_opts=opts.LegendOpts( orient="vertical", pos_top="5%", pos_left="2%" ))
c .set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}"))
c.render_notebook()

可以通过rich参数设置更多属性

 
c = Pie()
c.add("",[list(z) for z in zip(wd, num)],radius=["40%", "55%"],
       label_opts=opts.LabelOpts(position="outside",
       formatter="{a|{a}}{abg|}\n{hr|}\n{b|{b}:}{c}  {per|{d}%} ",
       background_color="#eee",border_color="#aaa",
       border_width=1,border_radius=4,
       rich={"a": {"color": "#999", "lineHeight": 22, "align": "center"},"abg": {"backgroundColor": "#e3e3e3","width": "100%", "align": "right", "height": 22,"borderRadius": [4, 4, 0, 0],}, "hr": {"borderColor": "#aaa", "width": "100%","borderWidth": 0.5, "height": 0,}, "b": {"fontSize": 16, "lineHeight": 33},"per": {"color": "#eee","backgroundColor": "#334455",                        "padding": [2, 4],"borderRadius": 2,} } ))
c.set_global_opts(title_opts=opts.TitleOpts(title="Pie-富文本示例"))
c.render_notebook()

玫瑰图绘制

from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Page, Pie
data = [45,86,39,52,68]
labels = ['电脑','手机','彩电','冰箱','洗衣机']
c = Pie()
c.add("",[list(z) for z in zip(wd, num)],radius=["40%", "55%"],center=[240,220],rosetype='radius')
c.add("",[list(z) for z in zip(wd, num)],radius=["40%", "55%"],center=[620,220],rosetype='area')
c.set_global_opts(title_opts=opts.TitleOpts(title="玫瑰图"))
c.render_notebook()

漏斗图

pyecharts中通过Funnel绘制漏斗图。

from pyecharts.charts import Funnel
from pyecharts import options as opts
%matplotlib inline
data = [45,86,39,52,68]
labels = ['电脑','手机','彩电','冰箱','洗衣机']
wf = Funnel()
wf.add('电器销量图',[list(z) for z in zip(labels, data)], is_selected= True)
wf.render_notebook()

散点图

pyecharts利用Scatter绘制散点图。

from pyecharts import options as opts
from pyecharts.charts import Scatter
week = ["周一", "周二", "周三", "周四", "周五", "周六", "周日"]
c = Scatter()
c.add_xaxis(week)
c.add_yaxis("商家A", [81,65,48,32,68,92,87])
c.set_global_opts(title_opts=opts.TitleOpts(title="Scatter-一周的销售额（万元）"))
c.render_notebook()

K线图

pyecharts利用Kline绘制K线图。

from pyecharts import options as opts
from pyecharts.charts import Kline
data = [[2320.26, 2320.26, 2287.3, 2362.94],[2300, 2291.3, 2288.26, 2308.38],[2295.35, 2346.5, 2295.35, 2345.92]]
c = Kline()
c.add_xaxis(["2019/7/{}".format(i + 1) for i in range(31)])
c.add_yaxis("2019年7月份K线图", data)
c.set_global_opts(yaxis_opts=opts.AxisOpts(is_scale=True),
            xaxis_opts=opts.AxisOpts(is_scale=True),
            title_opts=opts.TitleOpts(title="Kline-基本示例"),)
c.render_notebook()

仪表盘

pyecharts利用Gauge绘制仪表盘。

from pyecharts import options as opts
from pyecharts.charts import Gauge, Page
c = Gauge()
c.add("业务指标",[("完成率", 55.5)],axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts(color=[(0.3, "#67e0e3"),
 (0.7, "#37a2da"), (1, "#fd666d")], width=30)))
c.set_global_opts(title_opts=opts.TitleOpts(title="Gauge-不同颜色"),
 legend_opts=opts.LegendOpts(is_show=False)) 
c.render_notebook()

词云

Pyecharts利用WordCloud绘制词云。

from pyecharts import options as opts
from pyecharts.charts import Page, WordCloud
from pyecharts.globals import SymbolType
words = [
    ("牛肉面", 7800),("黄河", 6181),
    ("《读者》杂志", 4386), ("甜胚子", 3055),
      ("五泉山", 2550)]
c = WordCloud()
c.add("", words, word_size_range=[20, 80])
c.set_global_opts(title_opts=opts.TitleOpts(title="WordCloud-基本示例"))
c.render_notebook()

地图

自从 0.3.2 开始，为了缩减项目本身的体积以及维持 pyecharts 项目的轻量化运行，pyecharts 将不再自带地图 js 文件。如用户需要用到地图图表（Geo、Map），可自行安装对应的地图文件包。

Windows下通过以下的pip命令进行安装：

#安装全球国家地图，包括世界地图和 213 个国家
pip install echarts-countries-pypkg 
#安装中国省级地图，包括23 个省，5 个自治区
pip install echarts-china-provinces-pypkg 
 #中国市级地图，包括370 个中国城市
pip install echarts-china-cities-pypkg 

在指定地图上的城市标示某天最高温度

from pyecharts import options as opts
from pyecharts.charts import Map
temperature=[30,31,27,29,18]
loc = ['兰州市','天水市','白银市','武威市','甘南藏族自治州']
c =  Map()
c.add("甘肃省", [list(z) for z in zip(loc, temperature)], "甘肃",is_roam=True) 
# is_roam是否开启鼠标缩放和平移漫游
c .set_global_opts(title_opts=opts.TitleOpts(title="甘肃省部分城市最高气温"))
c.render_notebook()

组合图表