詳解如何基于Pyecharts繪制常見的直角坐標(biāo)系圖表

更新時間：2022年04月27日 16:13:19 作者：小黃同學(xué)AC

pyecharts是基于前端可視化框架echarts的Python可視化庫,下面這篇文章主要給大家介紹了關(guān)于如何基于Pyecharts繪制常見的直角坐標(biāo)系圖表的相關(guān)資料,文中通過實例代碼介紹的非常詳細,需要的朋友可以參考下

1.直方圖

# -*-coding:utf-8 -*-
# @Time :  21:02
# @Author: 黃榮津
# @File : 1.直方圖.py
# @Software: PyCharm
 
from pyecharts.charts import *
from pyecharts.components import Table
from pyecharts import options as opts
from pyecharts.commons.utils import JsCode
import random
import datetime
from pyecharts.globals import CurrentConfig
CurrentConfig.ONLINE_HOST = "https://cdn.kesci.com/lib/pyecharts_assets/"
 
x_data = ['python', 'java', 'c','c++', 'R', 'excel']
y_data = [143, 123, 69, 107, 90, 73]
bar = (Bar()
       .add_xaxis(x_data)
       .add_yaxis('', y_data)
      )
bar.render("1.直方圖.html")

2.折線圖

# -*-coding:utf-8 -*-
# @Time :  21:19
# @Author: 黃榮津
# @File : 2.折線圖.py
# @Software: PyCharm
 
from pyecharts.charts import *
from pyecharts.components import Table
from pyecharts import options as opts
from pyecharts.commons.utils import JsCode
import random
import datetime
from pyecharts.globals import CurrentConfig
CurrentConfig.ONLINE_HOST = "https://cdn.kesci.com/lib/pyecharts_assets/"
 
x_data = ['python', 'java', 'c','c++', 'R', 'excel']
y_data = [143, 123, 69, 107, 90, 73]
line = (Line()
       .add_xaxis(x_data)
       .add_yaxis('', y_data)
      )
line.render("2.折線圖.html")

3.箱形圖

# -*-coding:utf-8 -*-
# @Time :  21:25
# @Author: 黃榮津
# @File : 3.箱型圖.py
# @Software: PyCharm
 
from pyecharts.charts import *
from pyecharts.components import Table
from pyecharts import options as opts
from pyecharts.commons.utils import JsCode
import random
import datetime
from pyecharts.globals import CurrentConfig
CurrentConfig.ONLINE_HOST = "https://cdn.kesci.com/lib/pyecharts_assets/"
 
x_data = ['python', 'java', 'c','c++', 'R', 'excel']
y_data = [[random.randint(100, 150) for i in range(20)] for item in x_data]
 
class Box:
    pass
 
box =( Boxplot()
.add_xaxis(x_data)
.add_yaxis("", (y_data))
)
box.render("3.箱型圖.html")

4.散點圖

# -*-coding:utf-8 -*-
# @Time :  21:58
# @Author: 黃榮津
# @File : 4.散點圖.py
# @Software: PyCharm
 
 
from pyecharts.charts import *
from pyecharts.components import Table
from pyecharts import options as opts
from pyecharts.commons.utils import JsCode
import random
import datetime
from pyecharts.globals import CurrentConfig
CurrentConfig.ONLINE_HOST = "https://cdn.kesci.com/lib/pyecharts_assets/"
x_data = ['python', 'java', 'c','c++', 'R', 'excel']
y_data = [143, 123, 69, 107, 90, 73]
Scatter=(Scatter()
       .add_xaxis(x_data)
       .add_yaxis('', y_data)
      )
Scatter.render("4.散點圖.html")

5.帶漣漪效果散點圖

# -*-coding:utf-8 -*-
# @Time :  22:23
# @Author: 黃榮津
# @File : 5.帶漣漪效果散點圖.py
# @Software: PyCharm
 
 
from pyecharts.charts import *
from pyecharts.components import Table
from pyecharts import options as opts
from pyecharts.commons.utils import JsCode
import random
import datetime
from pyecharts.globals import CurrentConfig
CurrentConfig.ONLINE_HOST = "https://cdn.kesci.com/lib/pyecharts_assets/"
x_data = ['python', 'java', 'c','c++', 'R', 'excel']
y_data = [143, 123, 69, 107, 90, 73]
 
effectScatter = (EffectScatter()
           .add_xaxis(x_data)
           .add_yaxis('', y_data)
           )
 
effectScatter.render("5.帶漣漪效果散點圖.html")

6.k線圖

# -*-coding:utf-8 -*-
# @Time :  22:27
# @Author: 黃榮津
# @File : 6.k線圖.py
# @Software: PyCharm
 
from pyecharts.charts import *
from pyecharts.components import Table
from pyecharts import options as opts
from pyecharts.commons.utils import JsCode
import random
import datetime
from pyecharts.globals import CurrentConfig
CurrentConfig.ONLINE_HOST = "https://cdn.kesci.com/lib/pyecharts_assets/"
 
date_list = ["2022/4/{}".format(i + 1) for i in range(30)]
y_data = [[random.randint(200, 350) for i in range(20)] for item in date_list]
 
kline = (Kline()
         .add_xaxis(date_list)
         .add_yaxis('', y_data)
         )
 
kline.render("6.k線圖.html")

7.熱力圖

# -*-coding:utf-8 -*-
# @Time :  22:36
# @Author: 黃榮津
# @File : 7.熱力圖.py
# @Software: PyCharm
 
from pyecharts.charts import *
from pyecharts.components import Table
from pyecharts import options as opts
from pyecharts.commons.utils import JsCode
import random
import datetime
from pyecharts.globals import CurrentConfig
CurrentConfig.ONLINE_HOST = "https://cdn.kesci.com/lib/pyecharts_assets/"
 
data = [[i, j, random.randint(0, 100)] for i in range(24) for j in range(7)]
hour_list = [str(i) for i in range(24)]
week_list = ['周日', '周一', '周二', '周三', '周四', '周五', '周六']
 
heat = (HeatMap()
        .add_xaxis(hour_list)
        .add_yaxis("", week_list, data)
        )
 
heat.render("7.熱力圖.html")

8.象型圖

# -*-coding:utf-8 -*-
# @Time :  22:46
# @Author: 黃榮津
# @File : 8.象型圖.py
# @Software: PyCharm
 
from pyecharts.charts import *
from pyecharts.components import Table
from pyecharts import options as opts
from pyecharts.commons.utils import JsCode
import random
import datetime
from pyecharts.globals import CurrentConfig
CurrentConfig.ONLINE_HOST = "https://cdn.kesci.com/lib/pyecharts_assets/"
 
x_data = ['python', 'java', 'c','c++', 'R', 'excel']
y_data = [143, 123, 69, 107, 90, 33]
pictorialBar = (PictorialBar()
                .add_xaxis(x_data)
                .add_yaxis('', y_data)
                )
 
pictorialBar.render("8.象型圖.html")

9.層疊圖

# -*-coding:utf-8 -*-
# @Time :  23:02
# @Author: 黃榮津
# @File : 9.層疊圖.py
# @Software: PyCharm
 
from pyecharts.charts import *
from pyecharts.components import Table
from pyecharts import options as opts
from pyecharts.commons.utils import JsCode
import random
import datetime
from pyecharts.globals import CurrentConfig
CurrentConfig.ONLINE_HOST = "https://cdn.kesci.com/lib/pyecharts_assets/"
 
x_data = ['python', 'java', 'c','c++', 'R', 'excel']
y_data = [143, 123, 69, 107, 90, 73]
bar = (Bar()
       .add_xaxis(x_data)
       .add_yaxis('', y_data)
       )
 
line = (Line()
        .add_xaxis(x_data)
        .add_yaxis('', y_data)
        )
 
overlap = bar.overlap(line) #利用第一個圖表為基礎(chǔ)，往后的數(shù)據(jù)都將會畫在第一個圖表上
overlap.render("9.層疊圖.html")