快捷導(dǎo)航

基于Python pyecharts實(shí)現(xiàn)多種圖例代碼解析

更新時(shí)間：2020年08月10日 09:51:08 作者：Yi_warmth

這篇文章主要介紹了基于Python pyecharts實(shí)現(xiàn)多種圖例代碼解析,文中通過示例代碼介紹的非常詳細(xì)，對(duì)大家的學(xué)習(xí)或者工作具有一定的參考學(xué)習(xí)價(jià)值,需要的朋友可以參考下

詞云圖

from pyecharts.charts import WordCloud
def word1():
  words= [
    ("Sam S Club", 10000),
    ("Macys", 6181),
    ("Amy Schumer", 4386),
    ("Jurassic World", 4055),
    ("Charter Communications", 2467),
    ("Chick Fil A", 2244),
    ("Planet Fitness", 1868),
    ("Pitch Perfect", 1484),
    ("Express", 1112),
    ("Home", 865),
    ("Johnny Depp", 847),
    ("Lena Dunham", 582),
    ("Lewis Hamilton", 555),
    ("KXAN", 550),
    ("Mary Ellen Mark", 462),
    ("Farrah Abraham", 366),
    ("Rita Ora", 360),
    ("Serena Williams", 282),
    ("NCAA baseball tournament", 273),
    ("Point Break", 265),
  ]
  worldcloud = (
    WordCloud()
    .add("", words, word_size_range=[20, 100])
    .set_global_opts(title_opts=opt.TitleOpts(title="WorldCloud-shape-diamond"))
  )
  # worldcloud = (
  #   WordCloud()
  #   .add("", words, word_size_range=[20, 100], shape=SymbolType.DIAMOND)
  #   .set_global_opts(title_opts=opt.TitleOpts(title="WorldCloud-shape-diamond"))
  # )
  worldcloud.render("wordl.html")
  os.system("wordl.html")

效果如下:

散點(diǎn)圖

from pyecharts.charts import Scatter
import numpy as np

def sca():
  x_data = np.linspace(0, 10, 30)
  y1_data = np.sin(x_data)
  y2_data = np.cos(x_data)
  # 繪制散點(diǎn)圖
  # 設(shè)置圖表大小
  figsise = opt.InitOpts(width="800px", height="600px")
  scatter = Scatter(init_opts=figsise)
  # 添加數(shù)據(jù)
  scatter.add_xaxis(xaxis_data=x_data)
  scatter.add_yaxis(series_name="sin(x)散點(diǎn)圖", #名稱
           y_axis=y1_data, # 數(shù)據(jù)
           label_opts=opt.LabelOpts(is_show=False), # 數(shù)據(jù)不顯示
           symbol_size=15, # 設(shè)置散點(diǎn)的大小
           symbol="triangle" # 設(shè)置散點(diǎn)的形狀
           )
  scatter.add_yaxis(series_name="cos(x)散點(diǎn)圖", y_axis=y2_data, label_opts=opt.LabelOpts(is_show=False))
  scatter.render()
  os.system("render.html")

效果如下:

餅狀圖

from pyecharts.charts import Pie
from pyecharts import options as optfrom pyecharts.faker import Faker as fa

def pie1():
  pie = (
    Pie()
    .add("", [list(z) for z in zip(fa.choose(), fa.values())])
    .set_global_opts(title_opts=opt.TitleOpts(title="pie-基本示例"))
    .set_series_opts(label_opts=opt.LabelOpts(formatter=":{c}"))
  )
  pie.render()
  os.system("render.html")

def pie2():
  pie = (
    Pie()
      .add("", [list(z) for z in zip(fa.choose(), fa.values())], radius=["40%", "75%"])
      .set_global_opts(title_opts=opt.TitleOpts(title="pie-示例"),
               legend_opts=opt.LegendOpts(
                 orient="vertical", pos_top="15%", pos_left="2%"
               ))
      .set_series_opts(label_opts=opt.LabelOpts(formatter=":{c}"))
  )
  pie.render()
  os.system("render.html")


def pie3():
  pie = (
    Pie()
      .add("", [list(z) for z in zip(fa.choose(), fa.values())],
         radius=["40%", "75%"],
         center=["25%", "50%"],
         rosetype="radius",
         label_opts=opt.LabelOpts(is_show=False))

      .add("", [list(z) for z in zip(fa.choose(), fa.values())],
         radius=["30%", "75%"],
         center=["75%", "50%"],
         rosetype="area")

      .set_global_opts(title_opts=opt.TitleOpts(title="pie-玫瑰圖示例"))

  )
  pie.render()
  os.system("render.html")

def pie4():
  # 多餅圖顯示
  pie = (
    Pie()
    .add(
      "",
      [list(z) for z in zip(["劇情", "其他"], [25, 75])],
      center=["20%", "30%"],
      radius=[40, 60]
    )
    .add(
      "",
      [list(z) for z in zip(["奇幻", "其他"], [24, 76])],
      center=["55%", '30%'],
      radius=[40, 60]
    )
    .add(
      "",
      [list(z) for z in zip(["愛情", "其他"], [14, 86])],
      center=["20%", "70%"],
      radius=[40, 60]
    )
    .add(
      "",
      [list(z) for z in zip(["驚駭", "其他"], [1, 89])],
      center=["55%", "70%"],
      radius=[40, 60]
    )
    .set_global_opts(
      title_opts=opt.TitleOpts(title="pie-多餅圖基本示例"),
      legend_opts=opt.LegendOpts(
        type_="scroll", pos_top="20%", pos_left="80%", orient="vertical"
      )
    )
    .set_series_opts(label_opts=opt.LabelOpts(formatter=":{c}"))
  )
  pie.render()
  os.system("render.html")

直方圖

from pyecharts.charts import Bar
from pyecharts import options as opt
from pyecharts.globals import ThemeType
from pyecharts.faker import Faker as fa
import random


def pye1():
  # 生成隨機(jī)數(shù)據(jù)
  attr = fa.days_attrs
  v1 = [random.randrange(10, 150) for _ in range(31)]
  v2 = [random.randrange(10, 150) for _ in range(31)]

  # 初始化一個(gè)Bar對(duì)象，并設(shè)定一寫初始化設(shè)置
  bar = Bar(init_opts=opt.InitOpts(theme=ThemeType.WHITE))
  # 添加數(shù)據(jù)
  bar.add_xaxis(attr)
  # is_selected: 打開圖表時(shí)是否默認(rèn)加載  grap:不同系列的柱間距離，百分比； color:指定柱狀圖Label的顏色
  bar.add_yaxis("test1", v1, gap="0", category_gap="20%", color=fa.rand_color())
  bar.add_yaxis("test2", v2, is_selected=False, gap="0%", category_gap="20%", color=fa.rand_color())
  # 全局配置
  # title_opts:圖標(biāo)標(biāo)題相關(guān)設(shè)置
  # toolbox_opts: 工具欄相關(guān)設(shè)置
  # yaxis_opts/xaxis_opts: 坐標(biāo)軸相關(guān)設(shè)置
  # axislabel_opts: 坐標(biāo)軸簽字相關(guān)設(shè)置
  # axisline_opts: 坐標(biāo)軸軸線相關(guān)設(shè)置
  # datazoom_opts: 坐標(biāo)軸軸線相關(guān)設(shè)置
  # markpoint_opts: 標(biāo)記點(diǎn)相關(guān)設(shè)置
  # markpoint_opts:label_opts=opts.LabelOpts(is_show=False) 標(biāo)簽值是否疊加
  # markline_opts：標(biāo)記線相關(guān)設(shè)置
  bar.set_global_opts(title_opts=opt.TitleOpts(title="主標(biāo)題", subtitle="副標(biāo)題"),
            toolbox_opts=opt.ToolboxOpts(),
            yaxis_opts=opt.AxisOpts(axislabel_opts=opt.LabelOpts(formatter="{value}/月"), name="這是y軸"),
            xaxis_opts=opt.AxisOpts(
            axisline_opts=opt.AxisLineOpts(linestyle_opts=opt.LineStyleOpts(color='blue')), name="這是x軸"),
            datazoom_opts=opt.DataZoomOpts()
            )
  bar.set_series_opts(markpoint_opts=opt.MarkPointOpts(data=[opt.MarkPointItem(type_="max", name="最大值"),
                                opt.MarkPointItem(type_="min", name="最小值"),
                                opt.MarkPointItem(type_="average", name="平均值")]),
            markline_opts=opt.MarkLineOpts(data=[opt.MarkLineItem(type_="min", name="最小值"),
                               opt.MarkLineItem(type_="max", name="最大值"),
                               opt.MarkLineItem(type_="average", name="平均值")]))
  # 指定生成html文件路徑
  bar.render('test.html')
  os.system("test.html")

效果如下