2.5 面向对象绘图.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0c62f105",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e0c05cd0",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = np.random.randn(1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "8dd666e0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.hist(data, label='ax')  # 默认分成10份\n",
    "ax.set_title('title is here')\n",
    "ax.set_xlabel('this is x')\n",
    "ax.legend(loc=2)\n",
    "ax.set_xticks([-3,0,3]) # 第二个列表不写，则只显示[-3,0,3]\n",
    "ax.set_xticklabels(['low', 'median', 'high'])\n",
    "# ax.set_xticks([-3,0,3], ['low', 'median', 'high'])\n",
    "ax.grid(True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "6b7426e2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x800 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(2,2,figsize=(10,8))\n",
    "ax[0][0].hist(data)\n",
    "ax[0][1].boxplot(data)\n",
    "plt.tight_layout()  # 让多个图像显示的不那么拥挤"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "9c28f147",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2, 2)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.shape(ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6fd1dca3",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}