viz_Tool.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "692ab151",
   "metadata": {},
   "source": [
    "# 默认代码"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c8ca3988",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 导入形式（必须是双引号）\n",
    "\n",
    "# %%capture\n",
    "# %run \"viz_Tool.ipynb\"\n",
    "\n",
    "# 最好同时也导入 file_Tool.ipynb 文件，因为下面的绘图方法中会调用到 file_Tool.ipynb 中的数据处理方法"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cfeeb933",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pyecharts.options as opts\n",
    "from pyecharts.charts import Line\n",
    "from pyecharts.charts import Scatter3D\n",
    "from pyecharts.charts import Scatter\n",
    "from pyecharts.charts import Bar3D\n",
    "from pyecharts.faker import Faker"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fbc099a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyecharts.globals import CurrentConfig, NotebookType\n",
    "CurrentConfig.NOTEBOOK_TYPE = NotebookType.JUPYTER_NOTEBOOK"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b86377cf",
   "metadata": {},
   "source": [
    "# 折线图\n",
    ">- 具体语法见 `viz_Use.ipynb` 作图规范"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "50c3df59",
   "metadata": {},
   "outputs": [],
   "source": [
    "# X 、Y 可以是 List 、ndarray 、DataFrame 的一列 Series\n",
    "\n",
    "# ignnore 表示是否将 Y 数据中的 0.0 转化为 None\n",
    "#         以获得更加平滑的折线图，而不是忽上忽下的尖山图\n",
    "#         但是两种方法的均值计算不同，需要注意\n",
    "\n",
    "# Y_name 为 Y 图例名称\n",
    "# Y_unit 为 Y 数据单位\n",
    "\n",
    "\n",
    "def draw_Line(X , Y , ignore = False , Y_name = '' , Y_unit = ''):\n",
    "    \n",
    "    # 预处理\n",
    "    X = list(X)\n",
    "    Y = list(Y)\n",
    "    \n",
    "    # X 最好最好是 List [String , String , ...] 且无重复\n",
    "    X = [str(x) for x in X]\n",
    "    \n",
    "    # 是否将 0 或 0.0 转化为 None\n",
    "    # file_Tool.ipynb 中的数据处理方法\n",
    "    if ignore:\n",
    "        Y = trans_Y_for_Viz(Y)\n",
    "    \n",
    "    # X 与 Y 长度不一致\n",
    "    if len(X) < len(Y):\n",
    "        print('数据 X 有缺失，长度与数据 Y 不一致，可以绘画，但不准确！！！')\n",
    "    elif len(X) > len(Y):\n",
    "        print('数据 Y 有缺失，长度与数据 X 不一致，可以绘画，但不准确！！！')\n",
    "    \n",
    "    line = (\n",
    "        Line(\n",
    "            opts.InitOpts(\n",
    "                bg_color = '#FFFFFF' ,\n",
    "                width = '1333px' ,\n",
    "                height = '600px'\n",
    "            )\n",
    "        )\n",
    "        .add_xaxis(X)\n",
    "        .add_yaxis(\n",
    "            Y_name , \n",
    "            Y , \n",
    "            color = '#FF4500' ,\n",
    "            symbol_size = [7 , 7] ,\n",
    "            is_connect_nones = True ,\n",
    "            markpoint_opts = opts.MarkPointOpts(\n",
    "                data = [\n",
    "                    opts.MarkPointItem(type_ = 'min' , name = 'Min') ,          # 标记 min\n",
    "                    opts.MarkPointItem(type_ = 'max' , name = 'Max')            # 标记 max\n",
    "                ] ,\n",
    "                symbol_size = [45 , 45] , \n",
    "                label_opts = opts.LabelOpts(\n",
    "                    formatter = '{b}' , \n",
    "                    position = 'inside'\n",
    "                )\n",
    "            ) ,\n",
    "            markline_opts = opts.MarkLineOpts(\n",
    "                symbol = ['circle' , 'triangle'] ,\n",
    "                symbol_size = [11 , 11] ,\n",
    "                label_opts = opts.LabelOpts(\n",
    "                    font_weight = 'bold' , \n",
    "                    font_size = 16 , \n",
    "                    color = 'auto' , \n",
    "                    formatter = ' {c} 均值线'\n",
    "                ) ,\n",
    "                linestyle_opts = opts.LineStyleOpts(\n",
    "                    width = 1.5 , \n",
    "                    type_ = 'dashed'\n",
    "                ) , \n",
    "                data = [\n",
    "                    opts.MarkLineItem(type_ = 'average' , name = Y_name)       # 标记 mean ，会忽略 None 计算 mean\n",
    "                ]\n",
    "            ) , \n",
    "            label_opts = opts.LabelOpts(is_show = True , font_weight='bold' , color = 'auto') ,\n",
    "            linestyle_opts = opts.LineStyleOpts(width = 2.33)\n",
    "        )\n",
    "        .set_global_opts(\n",
    "            datazoom_opts = opts.DataZoomOpts(           # 区域缩放滚动\n",
    "                range_start = 0 , \n",
    "                range_end = 100\n",
    "            ) ,\n",
    "            yaxis_opts = opts.AxisOpts(\n",
    "                axislabel_opts = opts.LabelOpts(\n",
    "                    formatter = '{value} ' + Y_unit , \n",
    "                    font_weight = 'bold' , \n",
    "                    font_size = 14 , \n",
    "                    color = 'auto')\n",
    "            ) , \n",
    "            xaxis_opts = opts.AxisOpts(\n",
    "                axislabel_opts = opts.LabelOpts(\n",
    "                    is_show = True ,\n",
    "                    formatter = '{value}' , \n",
    "                    font_weight = 'bold' , \n",
    "                    font_size = 14 , \n",
    "                    color = 'auto' , \n",
    "                    rotate = 0)\n",
    "            ) ,\n",
    "            legend_opts = opts.LegendOpts(pos_top = 15) ,\n",
    "            toolbox_opts = opts.ToolboxOpts(pos_top = 10 , pos_left = 950) ,\n",
    "            tooltip_opts=opts.TooltipOpts(\n",
    "                is_show = True , \n",
    "                trigger = 'axis' , \n",
    "                axis_pointer_type = 'cross')\n",
    "        )\n",
    "    )\n",
    "    return line"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fa33dabb",
   "metadata": {},
   "source": [
    "# 散点图\n",
    ">- 一般用于可视化坐标点 `(x , y)` 或 `(x , y , z)` 的分布情况\n",
    ">- 所以传入的 `X 、Y 、Z` 数据都必须为数值型\n",
    ">  - `int` 整数\n",
    ">  - `float` 浮点数"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "636b4ad4",
   "metadata": {},
   "source": [
    "## `3D` 散点图\n",
    ">- [`3D` 文档](https://pyecharts.org/#/zh-cn/3d_charts)\n",
    ">- [视觉映射配置](https://pyecharts.org/#/zh-cn/global_options?id=visualmapopts%ef%bc%9a%e8%a7%86%e8%a7%89%e6%98%a0%e5%b0%84%e9%85%8d%e7%bd%ae%e9%a1%b9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "264fb88e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# X 、Y 、Z \n",
    "#     可以是 List 、ndarray 、DataFrame 的一列 Series\n",
    "#     数据必须是 int 或 float\n",
    "#     长度必须都相同\n",
    "\n",
    "# _name 参数为 X 、Y 、Z 轴的名称\n",
    "# title 是图例名称\n",
    "\n",
    "def draw_Scatter3D(X , Y , Z , X_name = 'X' , Y_name = 'Y' , Z_name = 'Z' , title = '图例名称'):\n",
    "    \n",
    "    # 预处理\n",
    "    X = list(X)\n",
    "    Y = list(Y)\n",
    "    Z = list(Z)\n",
    "    # print(len(X))\n",
    "    # print(len(Y))\n",
    "    # print(len(Z))\n",
    "    \n",
    "    if len(X) != len(Y) or len(X) != len(Z):\n",
    "        print('数据 X 、Y 与 Z 长度不一致，无法绘制 3D 散点图！！！')\n",
    "    else:\n",
    "        \n",
    "        XYZ = [(X[i] , Y[i] , Z[i]) for i in range(len(X))]\n",
    "        \n",
    "        scatter = (\n",
    "            Scatter3D(\n",
    "                opts.InitOpts(\n",
    "                    bg_color = '#FFFFFF' ,\n",
    "                    width = '1333px' ,\n",
    "                    height = '600px'\n",
    "                )\n",
    "            )\n",
    "            .add(\n",
    "                title , \n",
    "                XYZ , \n",
    "                grid3d_opts = opts.Grid3DOpts(           # 笛卡尔坐标系样式\n",
    "                    height = 90 ,                        # Z 轴长度\n",
    "                    width =  175 ,                       # X 轴长度\n",
    "                    depth = 90 ,                         # Y 轴长度\n",
    "                    rotate_speed = 10 , \n",
    "                    rotate_sensitivity = 3               # 鼠标转动的灵敏度\n",
    "                ) , \n",
    "                xaxis3d_opts = opts.Axis3DOpts(          # X_name 为 X 轴名称\n",
    "                    type_ = 'value' , \n",
    "                    name = X_name , \n",
    "                    # min_ = 'dataMin' , \n",
    "                    # max_ = 'dataMax' , \n",
    "                ) , \n",
    "                yaxis3d_opts = opts.Axis3DOpts(          # Y_name 为 Y 轴名称\n",
    "                    type_ = 'value' , \n",
    "                    name = Y_name , \n",
    "                    # min_ = 'dataMin' , \n",
    "                    # max_ = 'dataMax' , \n",
    "                ) , \n",
    "                zaxis3d_opts = opts.Axis3DOpts(          # Z_name 为 Z 轴名称\n",
    "                    type_ = 'value' , \n",
    "                    name = Z_name , \n",
    "                    # min_ = 'dataMin' , \n",
    "                    # max_ = 'dataMax' , \n",
    "                ) , \n",
    "            )\n",
    "            .set_global_opts(\n",
    "                visualmap_opts = opts.VisualMapOpts(     # 按 Z 轴高低区分色彩\n",
    "                    min_ = min(Z) ,\n",
    "                    max_ = max(Z) , \n",
    "                    range_text = [f'High' , f'Low'] , \n",
    "                    range_color = Faker.visual_color ,   # 配色\n",
    "                    pos_top = 188 , \n",
    "                    pos_left = 80 , \n",
    "                ) , \n",
    "                toolbox_opts = opts.ToolboxOpts(pos_top = 10 , pos_left = 950) ,       # 便捷工具栏\n",
    "            )\n",
    "        )\n",
    "        return scatter"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d89e3c9a",
   "metadata": {},
   "source": [
    "## `3D` 散点图标签\n",
    ">- 根据每个三维坐标点 `(x , y , z)` 的类别或标签 `lable` 不同，显式不同的颜色"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7c9da9f4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# X_Y_Z 数据为如下两种结构\n",
    "# [\n",
    "#     [x , y , z] , \n",
    "#     [x , y , z] , \n",
    "#     [x , y , z] , \n",
    "#     ... ,\n",
    "# ]\n",
    "# [\n",
    "#     (x , y , z) , \n",
    "#     (x , y , z) , \n",
    "#     (x , y , z) , \n",
    "#     ... ,\n",
    "# ]\n",
    "\n",
    "# labels = [int , int , ...] 或 [String , String , ...]\n",
    "# labelsDict = {\n",
    "#     标签 : '颜色' , \n",
    "#     标签 : '颜色' , \n",
    "#     ...\n",
    "# }\n",
    "\n",
    "# 常用的一些标签颜色字典，即 Faker.visual_color 配色\n",
    "LABELS_DICT_Int = {\n",
    "    0 : '#abd9e9' , \n",
    "    1 : '#fee090' , \n",
    "    2 : '#fdae61' ,\n",
    "    3 : '#f46d43' , \n",
    "    4 : '#4575b4' , \n",
    "}\n",
    "LABELS_DICT_Str = {\n",
    "    'A' : '#abd9e9' , \n",
    "    'B' : '#fee090' , \n",
    "    'C' : '#fdae61' ,\n",
    "    'D' : '#f46d43' , \n",
    "    'E' : '#4575b4' , \n",
    "}\n",
    "\n",
    "\n",
    "def draw_Scatter3D_clf(X_Y_Z , \n",
    "                       labels , labelsDict , \n",
    "                       X_name = 'X' , Y_name = 'Y' , Z_name = 'Z' , \n",
    "                       title = '图例名称'):\n",
    "    \n",
    "    # 下面要用到 Z 确定 VisualMapOpts 的范围\n",
    "    Z = [ xyz[2] for xyz in X_Y_Z ]\n",
    "    \n",
    "    scatter3d = (\n",
    "        Scatter3D(\n",
    "            opts.InitOpts(\n",
    "                bg_color = '#FFFFFF' ,\n",
    "                width = '1333px' ,\n",
    "                height = '600px'\n",
    "            )\n",
    "        )\n",
    "        .add(\n",
    "            title , \n",
    "            [ {'value':xyz} for xyz in X_Y_Z ] ,     # 将 X_Y_Z 转化为字典\n",
    "            grid3d_opts = opts.Grid3DOpts(           # 笛卡尔坐标系样式\n",
    "                height = 90 ,                        # Z 轴长度\n",
    "                width =  175 ,                       # X 轴长度\n",
    "                depth = 90 ,                         # Y 轴长度\n",
    "                rotate_speed = 10 , \n",
    "                rotate_sensitivity = 3               # 鼠标转动的灵敏度\n",
    "            ) , \n",
    "            xaxis3d_opts = opts.Axis3DOpts(          # X_name 为 X 轴名称\n",
    "                type_ = 'value' , \n",
    "                name = X_name , \n",
    "                # min_ = 'dataMin' , \n",
    "                # max_ = 'dataMax'\n",
    "            ) , \n",
    "            yaxis3d_opts = opts.Axis3DOpts(          # Y_name 为 Y 轴名称\n",
    "                type_ = 'value' , \n",
    "                name = Y_name , \n",
    "                # min_ = 'dataMin' , \n",
    "                # max_ = 'dataMax'\n",
    "            ) , \n",
    "            zaxis3d_opts = opts.Axis3DOpts(          # Z_name 为 Z 轴名称\n",
    "                type_ = 'value' , \n",
    "                name = Z_name , \n",
    "                # min_ = 'dataMin' , \n",
    "                # max_ = 'dataMax'\n",
    "            ) , \n",
    "        )\n",
    "        .set_global_opts(\n",
    "            visualmap_opts = opts.VisualMapOpts(     # 按 Z 轴高低区分色彩\n",
    "                min_ = min(Z) ,\n",
    "                max_ = max(Z) , \n",
    "                range_text = [f'High' , f'Low'] , \n",
    "                range_color = Faker.visual_color ,   # 配色\n",
    "                pos_top = 188 , \n",
    "                pos_left = 80 , \n",
    "            ) , \n",
    "            toolbox_opts = opts.ToolboxOpts(pos_top = 10 , pos_left = 950) ,       # 便捷工具栏\n",
    "        )\n",
    "    )\n",
    "    \n",
    "    # 根据 labels 和 labelsDict 设置每个点的颜色\n",
    "    for i, la in enumerate(labels):\n",
    "        scatter3d.options['series'][0]['data'][i].update(\n",
    "            itemStyle = { \n",
    "                'color' : labelsDict[la] \n",
    "            }\n",
    "        )\n",
    "    \n",
    "    return scatter3d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d0d01f7e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7cdc6360",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "08e1b1a2",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "0946922d",
   "metadata": {},
   "source": [
    "## `2D` 散点图\n",
    ">- [文档](https://pyecharts.org/#/zh-cn/rectangular_charts?id=scatter%ef%bc%9a%e6%95%a3%e7%82%b9%e5%9b%be)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3ac021b3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# X 、Y\n",
    "#      可以是 List 、ndarray 、DataFrame 的一列 Series\n",
    "#      数据必须是 int 或 float\n",
    "#      长度必须都相同\n",
    "\n",
    "# 控制参数：\n",
    "#     scale 参数在 X 、Y 数据的最大值和最小值基础上，用于微微调节 X 、Y 轴的刻度范围\n",
    "#     c     是否使用 VisualMapOpts ，默认为 True ，将覆盖 cc 的统一颜色\n",
    "#           且不知道为啥，使用 VisualMapOpts 后无鼠标移动提示框，即 TooltipOpts 也会失效\n",
    "#           使用统一颜色 cc 就有鼠标移动提示框\n",
    "#           但 3d 图即使使用 VisualMapOpts 也会有鼠标移动提示框\n",
    "#     cc    统一的散点颜色，只有在 c = False 的情况下才有效\n",
    "\n",
    "def draw_Scatter2D(X , Y , Xscale = 0 , Yscale = 0 , c = True , cc = '#00BFFF' , title = '图例名称'):\n",
    "    \n",
    "    # 预处理\n",
    "    X = list(X)\n",
    "    Y = list(Y)\n",
    "    \n",
    "    if len(X) != len(Y):\n",
    "        print('数据 X 与 Y 长度不一致，无法绘制 2D 散点图！！！')\n",
    "    else:\n",
    "        scatter = (\n",
    "            Scatter(\n",
    "                opts.InitOpts(\n",
    "                    bg_color = '#FFFFFF' ,\n",
    "                    width = '1333px' ,\n",
    "                    height = '600px'\n",
    "                )\n",
    "            )\n",
    "            .add_xaxis(X)\n",
    "            .add_yaxis(\n",
    "                title ,\n",
    "                Y , \n",
    "                color = cc , \n",
    "                symbol_size = 15 ,\n",
    "                label_opts = opts.LabelOpts(is_show = False) ,     # 不显示每个散点的数据\n",
    "            )\n",
    "            .set_global_opts(\n",
    "                datazoom_opts = opts.DataZoomOpts(                 # 区域缩放滚动\n",
    "                    range_start = 0 , \n",
    "                    range_end = 100\n",
    "                ) ,\n",
    "                tooltip_opts = opts.TooltipOpts(          # 鼠标移动提示框\n",
    "                    is_show = True , \n",
    "                    trigger = 'axis' , \n",
    "                    axis_pointer_type = 'cross') , \n",
    "                xaxis_opts = opts.AxisOpts(               # X 轴刻度样式\n",
    "                    type_ = 'value' ,                     # 说明 X 轴是数值轴，适用于连续数据\n",
    "                    min_ = min(X) - Xscale ,              # 刻度范围\n",
    "                    max_ = max(X) + Xscale ,\n",
    "                ),\n",
    "                yaxis_opts = opts.AxisOpts(               # Y 轴刻度样式\n",
    "                    type_ = 'value' ,                     # 说明 Y 轴是数值轴，适用于连续数据\n",
    "                    min_ = min(Y) - Yscale ,              # 刻度范围\n",
    "                    max_ = max(Y) + Yscale , \n",
    "                ) , \n",
    "                toolbox_opts = opts.ToolboxOpts(pos_top = 10 , pos_left = 950) ,       # 便捷工具栏\n",
    "            )\n",
    "        )\n",
    "        if c:\n",
    "            scatter.set_global_opts(\n",
    "                visualmap_opts = opts.VisualMapOpts(      # Y 轴高低区分色彩\n",
    "                    min_ = min(Y) ,\n",
    "                    max_ = max(Y) , \n",
    "                    range_text = [f'High' , f'Low'] , \n",
    "                    range_color = Faker.visual_color ,    # 配色\n",
    "                    pos_top = 188 , \n",
    "                    pos_left = 0 , \n",
    "                ) , \n",
    "                toolbox_opts = opts.ToolboxOpts(pos_top = 10 , pos_left = 950) ,       # 便捷工具栏\n",
    "            )\n",
    "        \n",
    "        return scatter"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "06541f19",
   "metadata": {},
   "source": [
    "## `2D` 散点图叠加\n",
    ">- 数据聚类分析，详见 `viz_Use.ipynb` 中的测试"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "450efd29",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 上述 draw_Scatter2D() 的精简版本，或者说是适配版，专用于数据聚类分析的绘制\n",
    "#     仅在下面的 draw_Scatter2D_clf 方法中调用\n",
    "#     平常绘制散点图，使用上面的 、更加通用的 draw_Scatter2D()\n",
    "\n",
    "# 与上述 draw_Scatter2D() 的区别：\n",
    "#     无 c\n",
    "#     scales 用于直接指定 X 、Y 轴的刻度范围，而不是调节，方便多个类别的散点图 overlap 叠加时统一指定 X 、Y 轴刻度范围\n",
    "#     scale  同上，用于微微调节\n",
    "\n",
    "# 注意，每个叠加的散点图的图例 Y_title 必须不同，不然颜色会覆盖\n",
    "\n",
    "\n",
    "def draw_Scatter2D_special(X , Y , \n",
    "                           Xscales = [0 , 0] , Yscales = [0 , 0] , \n",
    "                           Xscale = 0 , Yscale = 0 , \n",
    "                           cc = '#00BFFF' , \n",
    "                           title = '图例名称'):\n",
    "    \n",
    "    # 预处理\n",
    "    X = list(X)\n",
    "    Y = list(Y)\n",
    "    \n",
    "    # X 、Y 轴刻度范围\n",
    "    if Xscales == [0 , 0]:\n",
    "        Xscales = [min(X) , max(X)]\n",
    "    if Yscales == [0 , 0]:\n",
    "        Yscales = [min(Y) , max(Y)]\n",
    "    \n",
    "    if len(X) != len(Y):\n",
    "        print('数据 X 与 Y 长度不一致，无法绘制 2D 散点图！！！')\n",
    "    else:\n",
    "        scatter = (\n",
    "            Scatter(\n",
    "                opts.InitOpts(\n",
    "                    bg_color = '#FFFFFF' ,\n",
    "                    width = '1333px' ,\n",
    "                    height = '600px'\n",
    "                )\n",
    "            )\n",
    "            .add_xaxis(X)\n",
    "            .add_yaxis(\n",
    "                title ,\n",
    "                Y , \n",
    "                color = cc , \n",
    "                symbol_size = 15 ,\n",
    "                label_opts = opts.LabelOpts(is_show = False) ,\n",
    "            )\n",
    "            .set_global_opts(\n",
    "                datazoom_opts = opts.DataZoomOpts(\n",
    "                    range_start = 0 , \n",
    "                    range_end = 100\n",
    "                ) ,\n",
    "                tooltip_opts = opts.TooltipOpts(\n",
    "                    is_show = True , \n",
    "                    trigger = 'axis' , \n",
    "                    axis_pointer_type = 'cross') , \n",
    "                xaxis_opts = opts.AxisOpts(               # X 轴刻度样式\n",
    "                    type_ = 'value' ,\n",
    "                    min_ = Xscales[0] - Xscale ,\n",
    "                    max_ = Xscales[1] + Xscale ,\n",
    "                ),\n",
    "                yaxis_opts = opts.AxisOpts(               # Y 轴刻度样式\n",
    "                    type_ = 'value' ,\n",
    "                    min_ = Yscales[0] - Yscale ,\n",
    "                    max_ = Yscales[1] + Yscale , \n",
    "                ) , \n",
    "                toolbox_opts = opts.ToolboxOpts(pos_top = 10 , pos_left = 950) ,       # 便捷工具栏\n",
    "            )\n",
    "        )\n",
    "        \n",
    "        return scatter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1187f24a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# clf == classfier == 分类绘制\n",
    "\n",
    "# data 为 DataFrame\n",
    "#      col1    要作为 X 数据的列名\n",
    "#      col2    要作为 Y 数据的列名\n",
    "#      colLab  用于分类的标签列的列名\n",
    "\n",
    "# colors 为每个类别的颜色列表 List ，需要与标签类别个数相同\n",
    "# scale 同上，为微微调整\n",
    "\n",
    "# 常用颜色\n",
    "COLORS = [\n",
    "    '#FF0000' , '#1E90FF' , '#54FF9F' ,    # 红 蓝 绿\n",
    "    '#FFDAB9' , '#ffff00' , '#313695' ,    # 乳 黄 深蓝\n",
    "    '#FF00FF' , '#FF7F24' , '#8B0000' ,    # 橘 紫 酒红 \n",
    "    '#abd9e9' ,    # 浅蓝\n",
    "]\n",
    "\n",
    "\n",
    "def draw_Scatter2D_clf(data , col1 , col2 , colLab , colors = COLORS , Xscale = 0 , Yscale = 0):\n",
    "    \n",
    "    \n",
    "    # 统计所有的类别标签\n",
    "    # file_Tool.ipynb 中的数据处理方法\n",
    "    cnts = val_cnt(data , colLab)\n",
    "    labels = list(cnts[colLab].values)\n",
    "    labels.sort()\n",
    "    \n",
    "    if len(labels) > len(colors):\n",
    "        print('提供的颜色列表 colors 的长度 < 标签类别个数，无法绘制！！！')\n",
    "    else:\n",
    "        \n",
    "        # 统一多个散点图叠加时的 X 、Y 轴刻度范围\n",
    "        minX = min(data[col1])\n",
    "        maxX = max(data[col1])\n",
    "        minY = min(data[col2])\n",
    "        maxY = max(data[col2])\n",
    "        \n",
    "        # 每个类别的散点图\n",
    "        scatters = []\n",
    "        \n",
    "        # 遍历颜色\n",
    "        idx = 0\n",
    "        \n",
    "        for la in labels:\n",
    "            scatters += [\n",
    "                draw_Scatter2D_special(\n",
    "                    X = data[data[colLab] == la][col1] , \n",
    "                    Y = data[data[colLab] == la][col2] , \n",
    "                    Xscales = [minX , maxX] , \n",
    "                    Yscales = [minY , maxY] , \n",
    "                    Xscale = Xscale , \n",
    "                    Yscale = Yscale , \n",
    "                    cc = colors[idx] , \n",
    "                    title = f'Class-{la}'\n",
    "                )\n",
    "            ]\n",
    "            idx += 1\n",
    "        \n",
    "        # 叠加多个散点图\n",
    "        for i in range(1 , len(scatters)):\n",
    "            scatters[0].overlap(scatters[i])\n",
    "            \n",
    "        return scatters[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "40c9fb78",
   "metadata": {},
   "source": [
    "# `3D` 柱状图\n",
    ">- 同散点图， `X 、Y 、Z` 数据都必须为数值型（`int` 或 `float`）\n",
    ">- 但可以传入 `Xticks` 和 `Yticks` ，表示 `X 、Y` 轴的刻度标签"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "eb97d810",
   "metadata": {},
   "outputs": [],
   "source": [
    "# X_Y_Z 数据为如下两种结构\n",
    "# [\n",
    "#     [x , y , z] , \n",
    "#     [x , y , z] , \n",
    "#     [x , y , z] , \n",
    "#     ... ,\n",
    "# ]\n",
    "# [\n",
    "#     (x , y , z) , \n",
    "#     (x , y , z) , \n",
    "#     (x , y , z) , \n",
    "#     ... ,\n",
    "# ]\n",
    "\n",
    "\n",
    "def draw_Bar3D(X_Y_Z , \n",
    "               Xticks , Yticks , \n",
    "               X_name = 'X' , Y_name = 'Y' , Z_name = 'Z' , title = '图例名称'\n",
    "              ):\n",
    "    \n",
    "    bar3d = (\n",
    "        Bar3D(\n",
    "            opts.InitOpts(\n",
    "                bg_color = '#FFFFFF' ,\n",
    "                width = '1333px' ,\n",
    "                height = '600px'\n",
    "            )\n",
    "        )\n",
    "        .add(\n",
    "            title ,\n",
    "            X_Y_Z ,\n",
    "            grid3d_opts = opts.Grid3DOpts(     # 笛卡尔坐标系样式\n",
    "                height = 90 ,\n",
    "                width =  175 ,\n",
    "                depth = 90 ,\n",
    "                rotate_speed = 10 , \n",
    "                rotate_sensitivity = 3\n",
    "            ) , \n",
    "            xaxis3d_opts = opts.Axis3DOpts(    # X 轴刻度，大概因为 type_ = 'category' 所以可以自定义 ticks\n",
    "                type_ = 'category' ,           # 上述的 3D 散点图也可以\n",
    "                data = Xticks , \n",
    "                name = X_name , \n",
    "                min_ = 'dataMin' , \n",
    "                max_ = 'dataMax' , \n",
    "            ) ,\n",
    "            yaxis3d_opts = opts.Axis3DOpts(    # Y 轴刻度\n",
    "                type_ = 'category' , \n",
    "                data = Yticks , \n",
    "                name = Y_name , \n",
    "                min_ = 'dataMin' , \n",
    "                max_ = 'dataMax' , \n",
    "            ) ,\n",
    "            zaxis3d_opts = opts.Axis3DOpts(\n",
    "                type_ = 'value' , \n",
    "                name = Z_name , \n",
    "                min_ = 'dataMin' , \n",
    "                max_ = 'dataMax' , \n",
    "            ) , \n",
    "        )\n",
    "        .set_global_opts(\n",
    "            visualmap_opts = opts.VisualMapOpts(     # 按 Z 轴高低区分色彩\n",
    "                min_ = min(Z) ,\n",
    "                max_ = max(Z) , \n",
    "                range_text = [f'High' , f'Low'] , \n",
    "                range_color = Faker.visual_color ,   # 配色\n",
    "                pos_top = 188 , \n",
    "                pos_left = 80 , \n",
    "            ) , \n",
    "            toolbox_opts = opts.ToolboxOpts(pos_top = 10 , pos_left = 950) ,       # 便捷工具栏\n",
    "        )\n",
    "    )\n",
    "    return bar3d"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "MathBert",
   "language": "python",
   "name": "mathbert"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": false,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {
    "height": "calc(100% - 180px)",
    "left": "10px",
    "top": "150px",
    "width": "165px"
   },
   "toc_section_display": true,
   "toc_window_display": true
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}