pyecharts图表库学习:Grid并行显示多张图

自定义图表类

  • Grid 类：并行显示多张图
  • Overlap 类：结合不同类型图表叠加画在同张图上
  • Page 类：同一网页按顺序展示多图
  • Timeline 类：提供时间线轮播多张图

Grid：并行显示多张图

用户可以自定义结合 Line/Bar/Kline/Scatter/EffectScatter/Pie/HeatMap/Boxplot 图表，将不同类型图表画在多张图上。第一个图需为 有 x/y 轴的图，即不能为 Pie，其他位置顺序任意。

Grid 类的使用：

  1. 引入 Grid类，from pyecharts import Grid
  2. 实例化Grid类，grid = Grid()，可指定page_title, width, height, jhost参数。
  3. 使用 add() 向 grid 中添加图，至少需要设置一个grid_top, grid_bottom, grid_left, grid_right 四个参数中的一个。grid_width 和 grid_height 一般不用设置，默认即可。
  4. 使用render() 渲染生成 `.html 文件

Note： Overlap类可放入 Grid类中，不过有个前提，Overlap 不可为多 x 轴或者多 y 轴，否则会出现坐标轴索引混乱问题

Grid 类中其他方法：render_embed()：在 Flask&Django中可以使用该方法渲染 show_config()：打印输出所有配置项chart：chart属性返回图形实例 在 Jupyter-notebook 中直接调用 Grid 实例即可显示图表

Grid.add()方法签名

add(chart,    grid_width=None,    grid_height=None,    grid_top=None,    grid_bottom=None,    grid_left=None,    grid_right=None)chart -> chart instance图表实例grid_width -> str/intgrid 组件的宽度。默认自适应。grid_height -> str/intgrid 组件的高度。默认自适应。grid_top -> str/intgrid 组件离容器顶部的距离。默认为 None, 有'top', 'center', 'middle'可选，也可以为百分数或者整数grid_bottom -> str/intgrid 组件离容器底部的距离。默认为 None, 有'top', 'center', 'middle'可选，也可以为百分数或者整数grid_left -> str/intgrid 组件离容器左侧的距离。默认为 None, 有'left', 'center', 'right'可选，也可以为百分数或者整数grid_right -> str/intgrid 组件离容器右侧的距离。默认为 None, 有'left', 'center', 'right'可选，也可以为百分数或者整数
上下类型，Bar + Line
from pyecharts import Bar, Line, Gridattr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]v1 = [5, 20, 36, 10, 75, 90]v2 = [10, 25, 8, 60, 20, 80]bar = Bar("柱状图示例", height=720)bar.add("商家A", attr, v1, is_stack=True)bar.add("商家B", attr, v2, is_stack=True)line = Line("折线图示例", title_top="50%")attr = ["周一", "周二", "周三", "周四", "周五", "周六", "周日"]line.add(    "最高气温",    attr,    [11, 11, 15, 13, 12, 13, 10],    mark_point=["max", "min"],    mark_line=["average"],)line.add(    "最低气温",    attr,    [1, -2, 2, 5, 3, 2, 0],    mark_point=["max", "min"],    mark_line=["average"],    legend_top="50%",)grid = Grid()grid.add(bar, grid_bottom="60%")grid.add(line, grid_top="60%")grid.render()
左右类型，Scatter + EffectScatter
from pyecharts import Scatter, EffectScatter, Gridv1 = [5, 20, 36, 10, 75, 90]v2 = [10, 25, 8, 60, 20, 80]scatter = Scatter(width=1200)scatter.add("散点图示例", v1, v2, legend_pos="70%")es = EffectScatter()es.add(    "动态散点图示例",    [11, 11, 15, 13, 12, 13, 10],    [1, -2, 2, 5, 3, 2, 0],    effect_scale=6,    legend_pos="20%",)grid = Grid()grid.add(scatter, grid_left="60%")grid.add(es, grid_right="60%")grid.render()
上下左右类型，Bar + Line + Scatter + EffectScatter
from pyecharts import Bar, Line, Scatter, EffectScatter, Gridattr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]v1 = [5, 20, 36, 10, 75, 90]v2 = [10, 25, 8, 60, 20, 80]bar = Bar("柱状图示例", title_pos="65%")bar.add("商家A", attr, v1, is_stack=True)bar.add("商家B", attr, v2, is_stack=True, legend_pos="80%")line = Line("折线图示例")attr = ["周一", "周二", "周三", "周四", "周五", "周六", "周日"]line.add(    "最高气温",    attr,    [11, 11, 15, 13, 12, 13, 10],    mark_point=["max", "min"],    mark_line=["average"],)line.add(    "最低气温",    attr,    [1, -2, 2, 5, 3, 2, 0],    mark_point=["max", "min"],    mark_line=["average"],    legend_pos="20%",)v1 = [5, 20, 36, 10, 75, 90]v2 = [10, 25, 8, 60, 20, 80]scatter = Scatter("散点图示例", title_top="50%", title_pos="65%")scatter.add("scatter", v1, v2, legend_top="50%", legend_pos="80%")es = EffectScatter("动态散点图示例", title_top="50%")es.add(    "es",    [11, 11, 15, 13, 12, 13, 10],    [1, -2, 2, 5, 3, 2, 0],    effect_scale=6,    legend_top="50%",    legend_pos="20%",)grid = Grid(height=720, width=1200)grid.add(bar, grid_bottom="60%", grid_left="60%")grid.add(line, grid_bottom="60%", grid_right="60%")grid.add(scatter, grid_top="60%", grid_left="60%")grid.add(es, grid_top="60%", grid_right="60%")grid.render()
Line + Pie
from pyecharts import Line, Pie, Gridline = Line("折线图示例")attr = ["周一", "周二", "周三", "周四", "周五", "周六", "周日"]line.add(    "最高气温",    attr,    [11, 11, 15, 13, 12, 13, 10],    mark_point=["max", "min"],    mark_line=["average"],)line.add(    "最低气温",    attr,    [1, -2, 2, 5, 3, 2, 0],    mark_point=["max", "min"],    mark_line=["average"],    legend_pos="20%",)attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]v1 = [11, 12, 13, 10, 10, 10]pie = Pie("饼图示例", title_pos="55%")pie.add(    "",    attr,    v1,    radius=[45, 65],    center=[65, 50],    legend_pos="80%",    legend_orient="vertical",)grid = Grid(width=1200)grid.add(line, grid_right="55%")grid.add(pie, grid_left="60%")grid.render()
HeatMap + Bar
import randomfrom pyecharts import HeatMap, Bar, Gridx_axis = [    "12a", "1a", "2a", "3a", "4a", "5a", "6a",    "7a", "8a", "9a", "10a", "11a", "12p", "1p",    "2p", "3p", "4p", "5p", "6p", "7p", "8p", "9p",    "10p", "11p",]y_axis = [    "Saturday",    "Friday",    "Thursday",    "Wednesday",    "Tuesday",    "Monday",    "Sunday",]data = [[i, j, random.randint(0, 50)] for i in range(24) for j in range(7)]heatmap = HeatMap("热力图示例")heatmap.add(    "热力图直角坐标系",    x_axis,    y_axis,    data,    is_visualmap=True,    visual_top="45%",    visual_text_color="#000",    visual_orient="horizontal",)attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]v1 = [5, 20, 36, 10, 75, 90]v2 = [10, 25, 8, 60, 20, 80]bar = Bar("柱状图示例", title_top="52%")bar.add("商家A", attr, v1, is_stack=True)bar.add("商家B", attr, v2, is_stack=True, legend_top="50%")grid = Grid(height=700)grid.add(heatmap, grid_bottom="60%")grid.add(bar, grid_top="60%")grid.render()

Bar 会受 HeatMap 影响，很有趣。

利用 Grid 解决 dataZoom 与 X 轴标签重叠问题

from pyecharts imoprt Bar, Gridx = [    "名字很长的x轴1",    "名字很长的x轴2",    "名字很长的x轴3",    "名字很长的x轴4",    "名字很长的x轴5",    "名字很长的x轴6",    "名字很长的x轴7",    "名字很长的x轴8",    "名字很长的x轴9",]y = [10, 20, 30, 40, 50, 60, 70, 80, 90]grid = Grid()bar = Bar("利用 Grid 解决 dataZoom 与 X 轴标签重叠问题")bar.add("", x, y, is_datazoom_show=True, xaxis_interval=0, xaxis_rotate=30)# 把 bar 加入到 grid 中，并适当调整 grid_bottom 参数，使 bar 图整体上移grid.add(bar, grid_bottom="25%")grid.render()
datazoom 组件同时控制多个图
from pyecharts import Line, Kline, Gridline = Line("折线图示例")attr = ["周一", "周二", "周三", "周四", "周五", "周六", "周日"]line.add(    "最高气温",    attr,    [11, 11, 15, 13, 12, 13, 10],    mark_point=["max", "min"],    mark_line=["average"],)line.add(    "最低气温",    attr,    [1, -2, 2, 5, 3, 2, 0],    mark_point=["max", "min"],    legend_top="50%",    mark_line=["average"],    # 设置 dataZoom 控制索引为 0,1 的 x 轴，即第一个和第二个    is_datazoom_show=True,    datazoom_xaxis_index=[0, 1],)v1 = [    [2320.26, 2320.26, 2287.3, 2362.94],    [2300, 2291.3, 2288.26, 2308.38],    [2295.35, 2346.5, 2295.35, 2345.92],    [2347.22, 2358.98, 2337.35, 2363.8],    [2360.75, 2382.48, 2347.89, 2383.76],    [2383.43, 2385.42, 2371.23, 2391.82],    [2377.41, 2419.02, 2369.57, 2421.15],    [2425.92, 2428.15, 2417.58, 2440.38],    [2411, 2433.13, 2403.3, 2437.42],    [2432.68, 2334.48, 2427.7, 2441.73],    [2430.69, 2418.53, 2394.22, 2433.89],    [2416.62, 2432.4, 2414.4, 2443.03],    [2441.91, 2421.56, 2418.43, 2444.8],    [2420.26, 2382.91, 2373.53, 2427.07],    [2383.49, 2397.18, 2370.61, 2397.94],    [2378.82, 2325.95, 2309.17, 2378.82],    [2322.94, 2314.16, 2308.76, 2330.88],    [2320.62, 2325.82, 2315.01, 2338.78],    [2313.74, 2293.34, 2289.89, 2340.71],    [2297.77, 2313.22, 2292.03, 2324.63],    [2322.32, 2365.59, 2308.92, 2366.16],    [2364.54, 2359.51, 2330.86, 2369.65],    [2332.08, 2273.4, 2259.25, 2333.54],    [2274.81, 2326.31, 2270.1, 2328.14],    [2333.61, 2347.18, 2321.6, 2351.44],    [2340.44, 2324.29, 2304.27, 2352.02],    [2326.42, 2318.61, 2314.59, 2333.67],    [2314.68, 2310.59, 2296.58, 2320.96],    [2309.16, 2286.6, 2264.83, 2333.29],    [2282.17, 2263.97, 2253.25, 2286.33],    [2255.77, 2270.28, 2253.31, 2276.22],]kline = Kline("K 线图示例", title_top="50%")kline.add(    "日K",    ["2017/7/{}".format(i + 1) for i in range(31)],    v1,    is_datazoom_show=True,)grid = Grid(width=1200, height=700)grid.add(line, grid_top="60%")grid.add(kline, grid_bottom="60%")grid.render()

Overlap：结合不同类型图表叠加画在同张图上

用户可以自定义结合 Line/Bar/Kline, Scatter/EffectScatter 图表，将不同类型图表画在一张图上。利用第一个图表为基础，往后的数据都将会画在第一个图表上。

Overlap 类的使用：

  1. 引入 Overlap 类，from pyecharts import Overlap
  2. 实例化 Overlap 类，overlap = Overlap()，可指定 page_title, width, height, jhost 参数。
  3. 使用 add() 向 overlap 中添加图
  4. 使用 render() 渲染生成 .html 文件

Overlap.add() 方法签名

add(chart,    xaxis_index=0,    yaxis_index=0,    is_add_xaxis=False,    is_add_yaxis=False)chart -> chart instance图表示例xaxis_index -> intx 坐标轴索引，默认为 0yaxis_index -> inty 坐标轴索引，默认为 0is_add_xaxis -> bool是否新增一个 x 坐标轴，默认为 Falseis_add_yaxis -> bool是否新增一个 y 坐标轴，默认为 False
Line + Bar
from pyecharts import Bar, Line, Overlapattr = ['A', 'B', 'C', 'D', 'E', 'F']v1 = [10, 20, 30, 40, 50, 60]v2 = [38, 28, 58, 48, 78, 68]bar = Bar("Line - Bar 示例")bar.add("bar", attr, v1)line = Line()line.add("line", attr, v2)overlap = Overlap()overlap.add(bar)overlap.add(line)overlap.render()
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