【Python可視化】超詳細Pyecharts 1.x教程，讓你的圖表動起來～-有解無憂

前言

pyecharts 是一個用于生成 Echarts 圖表的Python庫，Echarts是百度開源的一個資料可視化 JS 庫，可以生成一些非常酷炫的圖表，

AQI指數
Pyecharts在1.x版本之后迎來重大更新，與老版本（0.5X）已是兩個完全不同的版本，所以很多小伙伴在使用Pyecharts出現了類似'pyecharts' has no attribute 'xxx'的報錯，那是因為你安裝了1.x的版本卻使用了0.5x的呼叫方法，

當然如果你更習慣使用0.5X版本的可以通過如下陳述句來進行安裝：
pip install pyecharts==0.5.11
安裝1.x版本（僅支持Python 3.6+）：
pip install pyecharts

本文將會介紹Pyecharts1.x版本的使用方法，本文所有陳述句均基于v1.6.2，通過以下陳述句查詢使用pyecharts版本：

import pyecharts

print(pyecharts.__version__)

基本使用

鏈式呼叫

pyecharts在v1.x之后支持鏈式呼叫，具體陳述句如下：

from pyecharts.charts import Bar
from pyecharts import options as opts

# 示例資料
cate = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu']
data1 = [123, 153, 89, 107, 98, 23]
data2 = [56, 77, 93, 68, 45, 67]

# 1.x版本支持鏈式呼叫
bar = (Bar()
       .add_xaxis(cate)
       .add_yaxis('電商渠道', data1)
       .add_yaxis('門店', data2)
       .set_global_opts(title_opts=opts.TitleOpts(title="Bar-基本示例", subtitle="我是副標題"))
      )
# 在jupyter notebook總渲染
bar.render_notebook()

單獨呼叫

不習慣鏈式呼叫的開發者依舊可以單獨呼叫方法，

# 單獨呼叫
bar = Bar()
bar.add_xaxis(cate)
bar.add_yaxis('電商渠道', data1)
bar.add_yaxis('門店', data2)
bar.set_global_opts(title_opts=opts.TitleOpts(title="Bar-基本示例", subtitle="我是副標題"))
bar.render_notebook()

全域配置

可以通過全域配置(.set_global_opts():)控制以下區域

使用示例如下：

"""
全域配置項使用示例：
1. 標題 & 副標題
2. 關閉圖例
3. 顯示工具箱
"""
bar = (Bar()
       .add_xaxis(cate)
       .add_yaxis('電商渠道', data1)
       .add_yaxis('門店', data2)
       .set_global_opts(title_opts=opts.TitleOpts(title="Bar-基本示例", subtitle="我是副標題"),
                        toolbox_opts=opts.ToolboxOpts(),
                        legend_opts=opts.LegendOpts(is_show=False))
      )

bar.render_notebook()

系列配置

可以通過系列配置（.set_series_opts()）控制圖表中的文本，線樣式，標記等，使用示例如下：

"""
系列配置項使用示例：
1. 不顯示數值
2. 標記每個系列的最大值
"""
bar = (Bar()
       .add_xaxis(cate)
       .add_yaxis('電商渠道', data1)
       .add_yaxis('門店', data2)
       .set_series_opts(label_opts=opts.LabelOpts(is_show=False),
                        markpoint_opts=opts.MarkPointOpts(data=https://www.cnblogs.com/awesometang/p/[opts.MarkPointItem(type_="max", name="最大值"),]))
       .set_global_opts(title_opts=opts.TitleOpts(title="Bar-基本示例", subtitle="我是副標題"))
      )

bar.render_notebook()

基本圖表

餅圖

from pyecharts.charts import Pie
from pyecharts import options as opts

# 示例資料
cate = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu']
data = https://www.cnblogs.com/awesometang/p/[153, 124, 107, 99, 89, 46]

pie = (Pie()
       .add('', [list(z) for z in zip(cate, data)],
            radius=["30%", "75%"],
            rosetype="radius")
       .set_global_opts(title_opts=opts.TitleOpts(title="Pie-基本示例", subtitle="我是副標題"))
       .set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {d}%"))
      )

pie.render_notebook()

折線圖

from pyecharts.charts import Line
from pyecharts import options as opts

# 示例資料
cate = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu']
data1 = [123, 153, 89, 107, 98, 23]
data2 = [56, 77, 93, 68, 45, 67]

"""
折線圖示例:
1. is_smooth 折線 OR 平滑
2. markline_opts 標記線 OR 標記點
"""
line = (Line()
       .add_xaxis(cate)
       .add_yaxis('電商渠道', data1, 
                  markline_opts=opts.MarkLineOpts(data=https://www.cnblogs.com/awesometang/p/[opts.MarkLineItem(type_="average")]))
       .add_yaxis('門店', data2, 
                  is_smooth=True, 
                  markpoint_opts=opts.MarkPointOpts(data=https://www.cnblogs.com/awesometang/p/[opts.MarkPointItem(name="自定義標記點", 
                                                                             coord=[cate[2], data2[2]], value=https://www.cnblogs.com/awesometang/p/data2[2])]))
       .set_global_opts(title_opts=opts.TitleOpts(title="Line-基本示例", subtitle="我是副標題"))
      )

line.render_notebook()

漏斗圖

from pyecharts.charts import Funnel
from pyecharts import options as opts

# 示例資料
cate = ['訪問', '注冊', '加入購物車', '提交訂單', '付款成功']
data = https://www.cnblogs.com/awesometang/p/[30398, 15230, 10045, 8109, 5698]"""
漏斗圖示例：
1. sort_控制排序，默認降序；
2. 標簽顯示位置
"""
funnel = (Funnel()
          .add("用戶數", [list(z) for z in zip(cate, data)], 
               sort_='ascending',
               label_opts=opts.LabelOpts(position="inside"))
          .set_global_opts(title_opts=opts.TitleOpts(title="Funnel-基本示例", subtitle="我是副標題"))
         )

funnel.render_notebook()

熱力圖

from pyecharts.charts import HeatMap
from pyecharts import options as opts
from pyecharts.faker import Faker
import random

# 示例資料
data = https://www.cnblogs.com/awesometang/p/[[i, j, random.randint(0, 50)] for i in range(24) for j in range(7)]

heat = (HeatMap()
        .add_xaxis(Faker.clock)
        .add_yaxis("訪客數", 
                   Faker.week, 
                   data,
                   label_opts=opts.LabelOpts(is_show=True, position="inside"))
        .set_global_opts(
            title_opts=opts.TitleOpts(title="HeatMap-基本示例", subtitle="我是副標題"),
            visualmap_opts=opts.VisualMapOpts(),
            legend_opts=opts.LegendOpts(is_show=False))
       )

heat.render_notebook()

日歷圖

from pyecharts.charts import Calendar
from pyecharts import options as opts
import random
import datetime

# 示例資料
begin = datetime.date(2019, 1, 1)
end = datetime.date(2019, 12, 31)
data = https://www.cnblogs.com/awesometang/p/[[str(begin + datetime.timedelta(days=i)), random.randint(1000, 25000)]
        for i in range((end - begin).days + 1)]"""
日歷圖示例：
"""
calendar = (
        Calendar()
        .add("微信步數", data, calendar_opts=opts.CalendarOpts(range_="2019"))
        .set_global_opts(
            title_opts=opts.TitleOpts(title="Calendar-基本示例", subtitle="我是副標題"),
            legend_opts=opts.LegendOpts(is_show=False),
            visualmap_opts=opts.VisualMapOpts(
                max_=25000,
                min_=1000,
                orient="horizontal",
                is_piecewise=True,
                pos_top="230px",
                pos_left="100px",
            )
        )
    )

calendar.render_notebook()

地理系圖表

from pyecharts import options as opts
from pyecharts.charts import Map
import random

province = ['廣東', '湖北', '湖南', '四川', '重慶', '黑龍江', '浙江', '山西', '河北', '安徽', '河南', '山東', '西藏']
data = https://www.cnblogs.com/awesometang/p/[(i, random.randint(50, 150)) for i in province]

_map = (
        Map()
        .add("銷售額", data, "china")
        .set_global_opts(
            title_opts=opts.TitleOpts(title="Map-基本示例"),
            legend_opts=opts.LegendOpts(is_show=False),
            visualmap_opts=opts.VisualMapOpts(max_=200, is_piecewise=True),
        )
    )

_map.render_notebook()

地理熱點圖

from pyecharts import options as opts
from pyecharts.charts import Geo
from pyecharts.globals import ChartType
import random

province = ['武漢', '十堰', '鄂州', '宜昌', '荊州', '孝感', '黃石', '咸寧', '仙桃']
data = https://www.cnblogs.com/awesometang/p/[(i, random.randint(50, 150)) for i in province]

geo = (Geo()
        .add_schema(maptype="湖北")
        .add("門店數", data,
            type_=ChartType.HEATMAP)
        .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
        .set_global_opts(
            visualmap_opts=opts.VisualMapOpts(),
            legend_opts=opts.LegendOpts(is_show=False),
            title_opts=opts.TitleOpts(title="Geo-湖北熱力地圖"))
      )

geo.render_notebook()

3D散點圖

from pyecharts import options as opts
from pyecharts.charts import Scatter3D
from pyecharts.faker import Faker
import random


data = https://www.cnblogs.com/awesometang/p/[[random.randint(0, 100), random.randint(0, 100), random.randint(0, 100)]
        for _ in range(1000)]

scatter3D = (Scatter3D()
             .add("", data)
             .set_global_opts(
                 title_opts=opts.TitleOpts("Scatter3D-基本示例"),
                 visualmap_opts=opts.VisualMapOpts(range_color=Faker.visual_color))
            )

scatter3D.render_notebook()

其他特性

xy軸翻轉

from pyecharts.charts import Bar
from pyecharts import options as opts

# 示例資料
cate = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu']
data1 = [123, 153, 89, 107, 98, 23]
data2 = [56, 77, 93, 68, 45, 67]

bar = (Bar()
       .add_xaxis(cate)
       .add_yaxis('電商渠道', data1)
       .add_yaxis('門店', data2)
       .set_global_opts(title_opts=opts.TitleOpts(title="XY軸翻轉-基本示例", subtitle="我是副標題"))
       .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
       .reversal_axis()
      )

bar.render_notebook()

組合圖表

from pyecharts import options as opts
from pyecharts.charts import Map, Bar, Grid
from pyecharts.globals import ChartType, ThemeType
import random

province = ['武漢', '十堰', '鄂州', '宜昌', '荊州', '孝感', '黃石', '咸寧', '仙桃']
data = https://www.cnblogs.com/awesometang/p/[324, 125, 145, 216, 241, 244, 156, 278, 169]

bar = (Bar()
       .add_xaxis(province)
       .add_yaxis('營業額', data)
       .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
       .set_global_opts(
            title_opts=opts.TitleOpts(title="Grid-Bar")
        )
      )

line = (Line()
       .add_xaxis(province)
       .add_yaxis('營業額', data, 
                  markline_opts=opts.MarkLineOpts(data=https://www.cnblogs.com/awesometang/p/[opts.MarkLineItem(type_="average")]))
       .set_global_opts(title_opts=opts.TitleOpts(title="Grid-Line", pos_top="48%"))
      )

grid = (
        Grid()
        .add(bar, grid_opts=opts.GridOpts(pos_bottom="60%"))
        .add(line, grid_opts=opts.GridOpts(pos_top="60%"))
    )

grid.render_notebook()

主題設定

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.globals import ThemeType

# 示例資料
cate = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu']
data1 = [123, 153, 89, 107, 98, 23]
data2 = [56, 77, 93, 68, 45, 67]

"""
主題設定：
默認white
"""
bar = (Bar(init_opts=opts.InitOpts(theme=ThemeType.ROMANTIC))
       .add_xaxis(cate)
       .add_yaxis('電商渠道', data1)
       .add_yaxis('門店', data2)
       .set_series_opts(label_opts=opts.LabelOpts(is_show=False),
                        markpoint_opts=opts.MarkPointOpts(data=https://www.cnblogs.com/awesometang/p/[opts.MarkPointItem(type_="max", name="最大值"),]))
       .set_global_opts(title_opts=opts.TitleOpts(title="Theme-ROMANTIC"))
      )

bar.render_notebook()

時間軸

from pyecharts import options as opts
from pyecharts.charts import Bar, Timeline
from pyecharts.globals import ThemeType
import random

# 示例資料
cate = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu']

tl = Timeline()
for i in range(2015, 2020):
    bar = (
        Bar()
        .add_xaxis(cate)
        .add_yaxis("線上", [random.randint(50, 150) for _ in cate])
        .add_yaxis("門店", [random.randint(100, 200) for _ in cate])
        .set_global_opts(title_opts=opts.TitleOpts("手機品牌{}年營業額".format(i)))
    )
    tl.add(bar, "{}年".format(i))
    
tl.render_notebook()

航線圖

from pyecharts import options as opts
from pyecharts.charts import Geo
from pyecharts.globals import ChartType, SymbolType, ThemeType
import requests

r = requests.get('https://echarts.baidu.com/examples/data-gl/asset/data/flights.json')
data = https://www.cnblogs.com/awesometang/p/r.json()

city = ['Beijing']
airports_code = []

geo = Geo(init_opts=opts.InitOpts(theme=ThemeType.DARK))
for i, airport in enumerate(data['airports']):
    if airport[1] in city:
        geo.add_coordinate(i, airport[3], airport[4])
        airports_code.append(i)

route = [(x, y) for _, x, y in data['routes'] if x in airports_code]


geo.add_schema(maptype="world",
                itemstyle_opts=opts.ItemStyleOpts())
geo.add("geo", route, 
        is_large = True,
        symbol_size=0,
        type_='lines',
        is_polyline=True,
        effect_opts=opts.EffectOpts(symbol='pin', symbol_size=1, trail_length=1, color="rgba(255,69,0,0.9)"),
        linestyle_opts=opts.LineStyleOpts(curve=0.2, width=0.2, color='rgb(245,245,245)',opacity=0.05)
       )
geo.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
geo.set_global_opts(title_opts=opts.TitleOpts(title="北京發出所有航線"),
                   legend_opts=opts.LegendOpts(is_show=False))


geo.render_notebook()

整理不易，歡迎點贊收藏???

轉載請註明出處，本文鏈接：https://www.uj5u.com/houduan/192490.html

標籤：Python

上一篇：PHP冒泡排序

下一篇：Python入門常識【入門必學】