pyechart1.6 儀表盤

時間  2021-01-19
標籤 html git github json 微信 網絡 echarts ide spa .net 欄目 HTML 简体版
原文   原文鏈接


代碼上傳

GitHub
https://github.com/deepwindlee/MySQL-with-Python-DATA-MINING/blob/master/pyecharts_study20200102.ipynb


定義好儀表盤中的子圖

柱狀圖 、曲線圖、餅圖、地圖、可切換時間的柱狀圖、可切換時間的餅圖html

from pyecharts.faker import Faker # 僞造的數據
from pyecharts import options as opts
from pyecharts.charts import Bar, Grid, Line, Page, Pie,Map, Timeline
##定義柱狀圖
def bar_datazoom_slider() -> Bar:
    c = (
        Bar()
        .add_xaxis(Faker.days_attrs)
        .add_yaxis("商家A", Faker.days_values)
        .set_global_opts(
            title_opts=opts.TitleOpts(title="Bar-DataZoom（slider-水平）"),
            datazoom_opts=[opts.DataZoomOpts()],
        )
    )
    return c

## 定義曲線圖
def line_markpoint() -> Line:
    c = (
        Line()
        .add_xaxis(Faker.choose())
        .add_yaxis(
            "商家A",
            Faker.values(),
            markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(type_="min")]),
        )
        .add_yaxis(
            "商家B",
            Faker.values(),
            markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(type_="max")]),
        )
        .set_global_opts(title_opts=opts.TitleOpts(title="Line-MarkPoint"))
    )
    return c

## 定義玫瑰餅圖
def pie_rosetype() -> Pie:
    v = Faker.choose()
    c = (
        Pie()
        .add(
            "",
            [list(z) for z in zip(v, Faker.values())],
            radius=["30%", "75%"],
            center=["25%", "50%"],
            rosetype="radius",
            label_opts=opts.LabelOpts(is_show=False),
        )
        .add(
            "",
            [list(z) for z in zip(v, Faker.values())],
            radius=["30%", "75%"],
            center=["75%", "50%"],
            rosetype="area",
        )
        .set_global_opts(title_opts=opts.TitleOpts(title="Pie-玫瑰圖示例"))
    )
    return c

## 定義多y軸圖
def grid_mutil_yaxis() -> Grid:
    x_data = ["{}月".format(i) for i in range(1, 13)]
    bar = (
        Bar()
        .add_xaxis(x_data)
        .add_yaxis(
            "蒸發量",
            [2.0, 4.9, 7.0, 23.2, 25.6, 76.7, 135.6, 162.2, 32.6, 20.0, 6.4, 3.3],
            yaxis_index=0,
            color="#d14a61",
        )
        .add_yaxis(
            "降水量",
            [2.6, 5.9, 9.0, 26.4, 28.7, 70.7, 175.6, 182.2, 48.7, 18.8, 6.0, 2.3],
            yaxis_index=1,
            color="#5793f3",
        )
        .extend_axis(
            yaxis=opts.AxisOpts(
                name="蒸發量",
                type_="value",
                min_=0,
                max_=250,
                position="right",
                axisline_opts=opts.AxisLineOpts(
                    linestyle_opts=opts.LineStyleOpts(color="#d14a61")
                ),
                axislabel_opts=opts.LabelOpts(formatter="{value} ml"),
            )
        )
        .extend_axis(
            yaxis=opts.AxisOpts(
                type_="value",
                name="溫度",
                min_=0,
                max_=25,
                position="left",
                axisline_opts=opts.AxisLineOpts(
                    linestyle_opts=opts.LineStyleOpts(color="#675bba")
                ),
                axislabel_opts=opts.LabelOpts(formatter="{value} °C"),
                splitline_opts=opts.SplitLineOpts(
                    is_show=True, linestyle_opts=opts.LineStyleOpts(opacity=1)
                ),
            )
        )
        .set_global_opts(
            yaxis_opts=opts.AxisOpts(
                name="降水量",
                min_=0,
                max_=250,
                position="right",
                offset=80,
                axisline_opts=opts.AxisLineOpts(
                    linestyle_opts=opts.LineStyleOpts(color="#5793f3")
                ),
                axislabel_opts=opts.LabelOpts(formatter="{value} ml"),
            ),
            title_opts=opts.TitleOpts(title="Grid-多 Y 軸示例"),
            tooltip_opts=opts.TooltipOpts(trigger="axis", axis_pointer_type="cross"),
        )
    )

    line = (
        Line()
        .add_xaxis(x_data)
        .add_yaxis(
            "平均溫度",
            [2.0, 2.2, 3.3, 4.5, 6.3, 10.2, 20.3, 23.4, 23.0, 16.5, 12.0, 6.2],
            yaxis_index=2,
            color="#675bba",
            label_opts=opts.LabelOpts(is_show=False),
        )
    )

    bar.overlap(line)
    return Grid().add(
        bar, opts.GridOpts(pos_left="5%", pos_right="20%"), is_control_axis_index=True
    )
def timeline_bar() -> Timeline:
    x = Faker.choose()
    tl = Timeline()
    for i in range(2015, 2020):
        bar = (
            Bar()
            .add_xaxis(x)
            .add_yaxis("商家A", Faker.values())
            .add_yaxis("商家B", Faker.values())
            .set_global_opts(title_opts=opts.TitleOpts("某商店{}年營業額".format(i)))
        )
        tl.add(bar, "{}年".format(i))
    return tl

#timeline_bar().render_notebook()
from pyecharts.charts import Bar, Page, Pie, Timeline,Map
def timeline_map() -> Timeline:
    tl = Timeline()
    for i in range(2015, 2020):
        map0 = (
            Map()
            .add(
                "商家A", [list(z) for z in zip(Faker.provinces, Faker.values())], "china"
            )
            .set_global_opts(
                title_opts=opts.TitleOpts(title="Map-{}年某些數據".format(i)),
                visualmap_opts=opts.VisualMapOpts(max_=200),
            )
        )
        tl.add(map0, "{}年".format(i))
    return tl
#timeline_map().render_notebook()
def timeline_pie() -> Timeline:
    attr = Faker.choose()
    tl = Timeline()
    for i in range(2015, 2020):
        pie = (
            Pie()
            .add(
                "商家A",
                [list(z) for z in zip(attr, Faker.values())],
                rosetype="radius",
                radius=["30%", "55%"],
            )
            .set_global_opts(title_opts=opts.TitleOpts("某商店{}年營業額".format(i)))
        )
        tl.add(pie, "{}年".format(i))
    return tl

def table_base() -> Table:
#文本表格圖
    table = Table()

    headers = ["City name", "Area", "Population", "Annual Rainfall"]
    rows = [
        ["Brisbane", 5905, 1857594, 1146.4],
        ["Adelaide", 1295, 1158259, 600.5],
        ["Darwin", 112, 120900, 1714.7],
        ["Hobart", 1357, 205556, 619.5],
        ["Sydney", 2058, 4336374, 1214.8],
        ["Melbourne", 1566, 3806092, 646.9],
        ["Perth", 5386, 1554769, 869.4],
    ]
    table.add(headers, rows).set_global_opts(
        title_opts=opts.ComponentTitleOpts(title="Table")
    )
    return table

下面把子圖都放到一個頁面上

page = Page()
page.add(bar_datazoom_slider(),
         line_markpoint(),
         pie_rosetype(),
         grid_mutil_yaxis(),
         timeline_bar(),
         timeline_map(),
         timeline_pie())
page.render('2020102順序多圖.html')
page.render_notebook()

打開保存的html文件，這種順序圖顯然是不適合業務的



給Page內加參數，進行簡單的排版

收縮放大後會從新自動排版，可是仍是不夠靈活

page = Page(layout=Page.SimplePageLayout)
# 須要自行調整每一個 chart 的 height/width，顯示效果在不一樣的顯示器上可能不一樣
page.add(bar_datazoom_slider(),
         line_markpoint(),
         pie_rosetype(),
         grid_mutil_yaxis(),
         timeline_bar(),
         timeline_map(),
         timeline_pie()
        )

page.render_notebook()
page.render('20200102簡單排版,收縮放大後會從新自動排版.html')



改變Page（）內參數，能夠對html 內的子圖進行拖拽放大縮小排版

page = Page(layout=Page.DraggablePageLayout)
page.add(bar_datazoom_slider(),
         line_markpoint(),
         pie_rosetype(),
         grid_mutil_yaxis(),
         timeline_bar(),
         timeline_map(),
         timeline_pie()
        )
page.render('20200112drag可拖拽縮小隨意組合.html')

排版好後點擊右上角的 SAVE_FIg 按鈕，保存參數，再讀取參數，新的html內的子圖也固定了



使用生成好的參數(從生成的文件中複製json數據)

cfg_dict = [{"cid":"0ffb8c5376e44e4e8163249945fb8a62",
             "width":"662px",
             "height":"247px",
             "top":"31px",
             "left":"8px"},
            {"cid":"989078509b19408f981e1ed0ce16e13b",
             "width":"692px",
             "height":"253px",
             "top":"32px",
             "left":"701px"},
            {"cid":"8f6d92a2b3874c9284c2f80fa1671cdb",
             "width":"1383px",
             "height":"422px",
             "top":"341px",
             "left":"18px"},
            {"cid":"15b9d663bb5b411d9da720ca8d657399",
             "width":"694px","height":"500px",
             "top":"783px","left":"22px"},
            {"cid":"c910f679ee574fd5920c1de206225f07",
             "width":"900px","height":"500px",
             "top":"784px","left":"737px"},
            {"cid":"61f7328625c6409aab3b93f6f489cd1f",
             "width":"763px","height":"500px","top":"1311px","left":"5px"},
            {"cid":"7603986f38ad445caec386225a1dfd3e","width":"900px","height":"500px","top":"1300px","left":"790px"}]

讀取這個參數，就能夠固定好html內的子表，生成新的html文件

##dest 爲新文件名, cfg_dict 爲從json數據中複製到的參數
Page.save_resize_html("20200112drag可拖拽縮小隨意組合.html", cfg_dict=cfg_dict, dest="my_new_charts2.html")

打開新文件後發現子圖固定了



、git


還能夠添加 文本表格圖 和 網絡圖片

from pyecharts.components import Image
from pyecharts.options import ComponentTitleOpts
def table_base() -> Table:
    table = Table()

    headers = ["City name", "Area", "Population", "Annual Rainfall"]
    rows = [
        ["Brisbane", 5905, 1857594, 1146.4],
        ["Adelaide", 1295, 1158259, 600.5],
        ["Darwin", 112, 120900, 1714.7],
        ["Hobart", 1357, 205556, 619.5],
        ["Sydney", 2058, 4336374, 1214.8],
        ["Melbourne", 1566, 3806092, 646.9],
        ["Perth", 5386, 1554769, 869.4],
    ]
    table.add(headers, rows).set_global_opts(
        title_opts=opts.ComponentTitleOpts(title="Table")
    )
    return table

def image_base() -> Image:
    image = Image()

    img_src = (
        " https://upload-images.jianshu.io/upload_images/9024458-44671873bd6b5397.jpg?imageMogr2/auto-orient/strip|imageView2/2"
    )
    image.add(
        src=img_src,
        style_opts={"width": "800px", "height": "1000px", "style": "margin-top: 20px"},
    ).set_global_opts(
        title_opts=ComponentTitleOpts(title="Image-基本示例", subtitle="從網絡載入圖片")
    )
    return image
page = Page(layout=Page.DraggablePageLayout)
# 須要自行調整每一個 chart 的 height/width，顯示效果在不一樣的顯示器上可能不一樣
page.add(bar_datazoom_slider(),
         line_markpoint(),
         pie_rosetype(),
         grid_mutil_yaxis(),
         timeline_bar(),
         timeline_map(),
         timeline_pie(),
         table_base(),image_base()
         
        )

page.render_notebook()
page.render('秦妃.html')

排版後可得


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