可视化实验四:大数据可视化工具—ECharts(二)

实验目的:

  1. 了解ECharts和pyecharts数据可视化的特点
  2. 掌握ECharts和pyecharts的简单操作
  3. 能够使用ECharts和pyecharts实现数据可视化操作

实验内容:

  1. 练习掌握pyecharts的安装和使用方法
  2. 练习使用pyecharts绘制柱状图、仪表盘图、3D图、雷达图、面积图等

实验过程(附结果截图):

1.练习掌握pyecharts的安装和使用方法

(1)打开Windows命令窗口,执行 “pip install pyecharts” 命令安装pyecharts库
可视化实验四:大数据可视化工具—ECharts(二)_第1张图片
(2)执行 “pip list” 命令查看安装结果
在这里插入图片描述
(3)使用pyecharts制作柱状图

from pyecharts.charts import Bar

v1 = [70, 85, 95, 64]
str1 = ['数学', '物理', '化学', '英语']
bar1 = Bar()
bar1.add_xaxis(str1)
bar1.add_yaxis('成绩', v1)
bar1.render()

可视化实验四:大数据可视化工具—ECharts(二)_第2张图片
可视化实验四:大数据可视化工具—ECharts(二)_第3张图片
2.练习使用pyecharts绘制柱状图、仪表盘图、3D图、雷达图、面积图等

(1)绘制柱状图

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

v1 = [70,85,95,64]
v2 = [80,75,85,70]
str1 = ['数学','物理','化学','英语']
bar = Bar()
bar.add_xaxis(str1)
bar.add_yaxis('小明', v1)
bar.add_yaxis('小红', v2)
bar.set_global_opts(title_opts=opts.TitleOpts(title='柱状图', subtitle='分数'))
bar.render()

可视化实验四:大数据可视化工具—ECharts(二)_第4张图片
可视化实验四:大数据可视化工具—ECharts(二)_第5张图片
(2)绘制仪表盘图

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

c = (
    Gauge()
    .add("", [("完成率", 66.6)])
    .set_global_opts(title_opts=opts.TitleOpts(title="Gauge-基本示例"))
    .render("gauge_base.html")
)

可视化实验四:大数据可视化工具—ECharts(二)_第6张图片
可视化实验四:大数据可视化工具—ECharts(二)_第7张图片
(3)绘制3D图

import pyecharts.options as opts
from pyecharts.charts import Bar3D

hours = [
    "12a",
    "1a",
    "2a",
    "3a",
    "4a",
    "5a",
    "6a",
    "7a",
    "8a",
    "9a",
    "10a",
    "11a",
    "12p",
    "1p",
    "2p",
    "3p",
    "4p",
    "5p",
    "6p",
    "7p",
    "8p",
    "9p",
    "10p",
    "11p",
]
days = ["Saturday", "Friday", "Thursday", "Wednesday", "Tuesday", "Monday", "Sunday"]

data = [
    [0, 0, 5],
    [0, 1, 1],
    [0, 2, 0],
    [0, 3, 0],
    [0, 4, 0],
    [0, 5, 0],
    [0, 6, 0],
    [0, 7, 0],
    [0, 8, 0],
    [0, 9, 0],
    [0, 10, 0],
    [0, 11, 2],
    [0, 12, 4],
    [0, 13, 1],
    [0, 14, 1],
    [0, 15, 3],
    [0, 16, 4],
    [0, 17, 6],
    [0, 18, 4],
    [0, 19, 4],
    [0, 20, 3],
    [0, 21, 3],
    [0, 22, 2],
    [0, 23, 5],
    [1, 0, 7],
    [1, 1, 0],
    [1, 2, 0],
    [1, 3, 0],
    [1, 4, 0],
    [1, 5, 0],
    [1, 6, 0],
    [1, 7, 0],
    [1, 8, 0],
    [1, 9, 0],
    [1, 10, 5],
    [1, 11, 2],
    [1, 12, 2],
    [1, 13, 6],
    [1, 14, 9],
    [1, 15, 11],
    [1, 16, 6],
    [1, 17, 7],
    [1, 18, 8],
    [1, 19, 12],
    [1, 20, 5],
    [1, 21, 5],
    [1, 22, 7],
    [1, 23, 2],
    [2, 0, 1],
    [2, 1, 1],
    [2, 2, 0],
    [2, 3, 0],
    [2, 4, 0],
    [2, 5, 0],
    [2, 6, 0],
    [2, 7, 0],
    [2, 8, 0],
    [2, 9, 0],
    [2, 10, 3],
    [2, 11, 2],
    [2, 12, 1],
    [2, 13, 9],
    [2, 14, 8],
    [2, 15, 10],
    [2, 16, 6],
    [2, 17, 5],
    [2, 18, 5],
    [2, 19, 5],
    [2, 20, 7],
    [2, 21, 4],
    [2, 22, 2],
    [2, 23, 4],
    [3, 0, 7],
    [3, 1, 3],
    [3, 2, 0],
    [3, 3, 0],
    [3, 4, 0],
    [3, 5, 0],
    [3, 6, 0],
    [3, 7, 0],
    [3, 8, 1],
    [3, 9, 0],
    [3, 10, 5],
    [3, 11, 4],
    [3, 12, 7],
    [3, 13, 14],
    [3, 14, 13],
    [3, 15, 12],
    [3, 16, 9],
    [3, 17, 5],
    [3, 18, 5],
    [3, 19, 10],
    [3, 20, 6],
    [3, 21, 4],
    [3, 22, 4],
    [3, 23, 1],
    [4, 0, 1],
    [4, 1, 3],
    [4, 2, 0],
    [4, 3, 0],
    [4, 4, 0],
    [4, 5, 1],
    [4, 6, 0],
    [4, 7, 0],
    [4, 8, 0],
    [4, 9, 2],
    [4, 10, 4],
    [4, 11, 4],
    [4, 12, 2],
    [4, 13, 4],
    [4, 14, 4],
    [4, 15, 14],
    [4, 16, 12],
    [4, 17, 1],
    [4, 18, 8],
    [4, 19, 5],
    [4, 20, 3],
    [4, 21, 7],
    [4, 22, 3],
    [4, 23, 0],
    [5, 0, 2],
    [5, 1, 1],
    [5, 2, 0],
    [5, 3, 3],
    [5, 4, 0],
    [5, 5, 0],
    [5, 6, 0],
    [5, 7, 0],
    [5, 8, 2],
    [5, 9, 0],
    [5, 10, 4],
    [5, 11, 1],
    [5, 12, 5],
    [5, 13, 10],
    [5, 14, 5],
    [5, 15, 7],
    [5, 16, 11],
    [5, 17, 6],
    [5, 18, 0],
    [5, 19, 5],
    [5, 20, 3],
    [5, 21, 4],
    [5, 22, 2],
    [5, 23, 0],
    [6, 0, 1],
    [6, 1, 0],
    [6, 2, 0],
    [6, 3, 0],
    [6, 4, 0],
    [6, 5, 0],
    [6, 6, 0],
    [6, 7, 0],
    [6, 8, 0],
    [6, 9, 0],
    [6, 10, 1],
    [6, 11, 0],
    [6, 12, 2],
    [6, 13, 1],
    [6, 14, 3],
    [6, 15, 4],
    [6, 16, 0],
    [6, 17, 0],
    [6, 18, 0],
    [6, 19, 0],
    [6, 20, 1],
    [6, 21, 2],
    [6, 22, 2],
    [6, 23, 6],
]
data = [[d[1], d[0], d[2]] for d in data]


(
    Bar3D(init_opts=opts.InitOpts(width="1600px", height="800px"))
    .add(
        series_name="",
        data=data,
        xaxis3d_opts=opts.Axis3DOpts(type_="category", data=hours),
        yaxis3d_opts=opts.Axis3DOpts(type_="category", data=days),
        zaxis3d_opts=opts.Axis3DOpts(type_="value"),
    )
    .set_global_opts(
        visualmap_opts=opts.VisualMapOpts(
            max_=20,
            range_color=[
                "#313695",
                "#4575b4",
                "#74add1",
                "#abd9e9",
                "#e0f3f8",
                "#ffffbf",
                "#fee090",
                "#fdae61",
                "#f46d43",
                "#d73027",
                "#a50026",
            ],
        )
    )
    .render("bar3d_punch_card.html")
)

可视化实验四:大数据可视化工具—ECharts(二)_第8张图片
可视化实验四:大数据可视化工具—ECharts(二)_第9张图片
(4)绘制雷达图

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

v1 = [[4300, 10000, 28000, 35000, 50000, 19000]]
v2 = [[5000, 14000, 28000, 31000, 42000, 21000]]

(
    Radar(init_opts=opts.InitOpts(width="1280px", height="720px", bg_color="#CCCCCC"))
    .add_schema(
        schema=[
            opts.RadarIndicatorItem(name="销售(sales)", max_=6500),
            opts.RadarIndicatorItem(name="管理(Administration)", max_=16000),
            opts.RadarIndicatorItem(name="信息技术(Information Technology)", max_=30000),
            opts.RadarIndicatorItem(name="客服(Customer Support)", max_=38000),
            opts.RadarIndicatorItem(name="研发(Development)", max_=52000),
            opts.RadarIndicatorItem(name="市场(Marketing)", max_=25000),
        ],
        splitarea_opt=opts.SplitAreaOpts(
            is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1)
        ),
        textstyle_opts=opts.TextStyleOpts(color="#fff"),
    )
    .add(
        series_name="预算分配(Allocated Budget)",
        data=v1,
        linestyle_opts=opts.LineStyleOpts(color="#CD0000"),
    )
    .add(
        series_name="实际开销(Actual Spending)",
        data=v2,
        linestyle_opts=opts.LineStyleOpts(color="#5CACEE"),
    )
    .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
    .set_global_opts(
        title_opts=opts.TitleOpts(title="基础雷达图"), legend_opts=opts.LegendOpts()
    )
    .render("basic_radar_chart.html")
)

可视化实验四:大数据可视化工具—ECharts(二)_第10张图片
可视化实验四:大数据可视化工具—ECharts(二)_第11张图片
(5)绘制面积图

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


c = (
    Line()
    .add_xaxis(Faker.choose())
    .add_yaxis("商家A", Faker.values(), is_smooth=True)
    .add_yaxis("商家B", Faker.values(), is_smooth=True)
    .set_series_opts(
        areastyle_opts=opts.AreaStyleOpts(opacity=0.5),
        label_opts=opts.LabelOpts(is_show=False),
    )
    .set_global_opts(
        title_opts=opts.TitleOpts(title="Line-面积图(紧贴 Y 轴)"),
        xaxis_opts=opts.AxisOpts(
            axistick_opts=opts.AxisTickOpts(is_align_with_label=True),
            is_scale=False,
            boundary_gap=False,
        ),
    )
    .render("line_areastyle_boundary_gap.html")
)

可视化实验四:大数据可视化工具—ECharts(二)_第12张图片
可视化实验四:大数据可视化工具—ECharts(二)_第13张图片

实验总结自己写写就行了,本实验仅供参考。

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