{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 导入工具\n",
    "import numpy as np\n",
    "import random\n",
    "import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "score = np.array([[80, 89, 86, 67, 79],\n",
    "[78, 97, 89, 67, 81],\n",
    "[90, 94, 78, 67, 74],\n",
    "[91, 91, 90, 67, 69],\n",
    "[76, 87, 75, 67, 86],\n",
    "[70, 79, 84, 67, 84],\n",
    "[94, 92, 93, 67, 64],\n",
    "[86, 85, 83, 67, 80]])  # 创建了一个ndarray对象"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[80, 89, 86, 67, 79],\n",
       "       [78, 97, 89, 67, 81],\n",
       "       [90, 94, 78, 67, 74],\n",
       "       [91, 91, 90, 67, 69],\n",
       "       [76, 87, 75, 67, 86],\n",
       "       [70, 79, 84, 67, 84],\n",
       "       [94, 92, 93, 67, 64],\n",
       "       [86, 85, 83, 67, 80]])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "numpy.ndarray"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(score)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## numpy 与Python list的效率对比"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = []\n",
    "for i in range(1000000000):\n",
    "    a.append(random.random())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%time sum(a)  # list求和时间"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "b = np.array(a) # 创建ndarray对象"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# numpy求和时间\n",
    "%time np.sum(b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.3"
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