1주차_numpy기본.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'numpy' from 'C:\\\\Users\\\\preci\\\\Anaconda3\\\\lib\\\\site-packages\\\\numpy\\\\__init__.py'>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'pandas' from 'C:\\\\Users\\\\preci\\\\Anaconda3\\\\lib\\\\site-packages\\\\pandas\\\\__init__.py'>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'matplotlib.pyplot' from 'C:\\\\Users\\\\preci\\\\Anaconda3\\\\lib\\\\site-packages\\\\matplotlib\\\\pyplot.py'>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'seaborn' from 'C:\\\\Users\\\\preci\\\\Anaconda3\\\\lib\\\\site-packages\\\\seaborn\\\\__init__.py'>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5]\n"
     ]
    }
   ],
   "source": [
    "a = [1,2,3,4,5]\n",
    "print(a*3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 3  6  9 12 15]\n"
     ]
    }
   ],
   "source": [
    "nparr = np.array([1,2,3,4,5])\n",
    "print(nparr*3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1, 2, 3],\n",
       "       [4, 5, 6],\n",
       "       [7, 8, 9]])"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.array([[1,2,3],[4,5,6],[7,8,9]])\n",
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 3 12 27]\n",
      " [12 30 54]\n",
      " [21 48 81]]\n"
     ]
    }
   ],
   "source": [
    "b = np.array([3,6,9])\n",
    "print(a*b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1 2 3]\n",
      "[[1 2 3]\n",
      " [4 5 6]]\n",
      "[list([1, 2]) list([3, 4, 5]) list([6, 7, 8, 9])]\n"
     ]
    }
   ],
   "source": [
    "a = np.array([1,2,3])\n",
    "b = np.array([[1,2,3],[4,5,6]])\n",
    "c = np.array([[1,2],[3,4,5],[6,7,8,9]]) #이런거 안된다는 뜻\n",
    "print(a)\n",
    "print(b)\n",
    "print(c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0. 0. 0.]\n",
      " [0. 0. 0.]\n",
      " [0. 0. 0.]\n",
      " [0. 0. 0.]\n",
      " [0. 0. 0.]\n",
      " [0. 0. 0.]\n",
      " [0. 0. 0.]\n",
      " [0. 0. 0.]\n",
      " [0. 0. 0.]\n",
      " [0. 0. 0.]]\n",
      "--------------------\n",
      "[0. 0. 0.]\n"
     ]
    }
   ],
   "source": [
    "d = np.zeros((10,3))\n",
    "print(d)\n",
    "e = np.zeros(3)\n",
    "print('-'*20)\n",
    "print(e)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'list'>\n",
      "<class 'numpy.ndarray'>\n",
      "[1 2 3]\n"
     ]
    }
   ],
   "source": [
    "orig = [1,2,3]\n",
    "print(type(orig))\n",
    "to_np = np.asarray(orig)\n",
    "print(type(to_np))\n",
    "print(to_np)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1 2 3]\n",
      "[1. 2. 3.]\n"
     ]
    }
   ],
   "source": [
    "a = np.array([1,2,3])\n",
    "b = np.array([1,2,3], dtype=np.float64)\n",
    "print(a)\n",
    "print(b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 3  6  9]\n",
      " [ 6  9 12]]\n",
      "--------------------\n",
      "[[-1 -2 -3]\n",
      " [ 2  1  0]]\n",
      "--------------------\n",
      "[[ 2  8 18]\n",
      " [ 8 20 36]]\n",
      "--------------------\n",
      "[[0.5  0.5  0.5 ]\n",
      " [2.   1.25 1.  ]]\n",
      "--------------------\n",
      "[[    1    16   729]\n",
      " [   16   625 46656]]\n",
      "--------------------\n",
      "[[1 2 3]\n",
      " [0 1 0]]\n",
      "--------------------\n",
      "[[False False False]\n",
      " [ True  True False]]\n",
      "--------------------\n",
      "[[False False False]\n",
      " [False False  True]]\n"
     ]
    }
   ],
   "source": [
    "a = np.array([[1,2,3],[4,5,6]])\n",
    "b = np.array([[2,4,6],[2,4,6]])\n",
    "print(a+b)\n",
    "print('-'*20)\n",
    "print(a-b)\n",
    "print('-'*20)\n",
    "print(a*b)\n",
    "print('-'*20)\n",
    "print(a/b)\n",
    "print('-'*20)\n",
    "print(a**b)\n",
    "print('-'*20)\n",
    "print(a%b)\n",
    "print('-'*20)\n",
    "print(a>b)\n",
    "print('-'*20)\n",
    "print(a==b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1 2 3]\n",
      " [4 5 6]\n",
      " [7 8 9]]\n",
      "--------------------\n",
      "[4 5 6]\n",
      "--------------------\n",
      "[3 6 9]\n",
      "--------------------\n",
      "[[1 2 3]\n",
      " [4 5 3]\n",
      " [7 8 9]]\n"
     ]
    }
   ],
   "source": [
    "a = np.array([[1,2,3],[4,5,6],[7,8,9]])\n",
    "b = a[1]\n",
    "c = a[:,2]\n",
    "print(a)\n",
    "print('-'*20)\n",
    "print(b)\n",
    "print('-'*20)\n",
    "print(c)\n",
    "c[1] = 3 #원본 값이 바뀝니다\n",
    "print('-'*20)\n",
    "print(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0. 0. 0. 0.]\n",
      " [1. 1. 1. 1.]\n",
      " [2. 2. 2. 2.]\n",
      " [3. 3. 3. 3.]\n",
      " [4. 4. 4. 4.]\n",
      " [5. 5. 5. 5.]\n",
      " [6. 6. 6. 6.]\n",
      " [7. 7. 7. 7.]]\n"
     ]
    }
   ],
   "source": [
    "a = np.empty((8,4))\n",
    "for i in range(8):\n",
    "    a[i] = i\n",
    "    \n",
    "print(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3. 3. 3. 3.]\n",
      "--------------------\n",
      "[[4. 4. 4. 4.]\n",
      " [7. 7. 7. 7.]\n",
      " [0. 0. 0. 0.]\n",
      " [3. 3. 3. 3.]]\n"
     ]
    }
   ],
   "source": [
    "print(a[3])\n",
    "print('-'*20)\n",
    "print(a[[4,7,0,3]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.arange(15)\n",
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0,  1,  2],\n",
       "       [ 3,  4,  5],\n",
       "       [ 6,  7,  8],\n",
       "       [ 9, 10, 11],\n",
       "       [12, 13, 14]])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b = a.reshape((5,3))\n",
    "b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0,  3,  6,  9, 12],\n",
       "       [ 1,  4,  7, 10, 13],\n",
       "       [ 2,  5,  8, 11, 14]])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c = b.T\n",
    "c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2. 2. 6.]\n",
      "[1. 1. 5.]\n",
      "[0.5        2.         0.83333333]\n"
     ]
    }
   ],
   "source": [
    "a = np.array([1,2,5])\n",
    "b = np.array([2,1,6])\n",
    "c = np.array([3.3,1.7,2.7])\n",
    "\n",
    "print(np.maximum(a,b,c))\n",
    "print(np.minimum(a,b,c))\n",
    "print(np.divide(a,b,c))\n",
    "#np.substract: 빼기\n",
    "#np.multiply: 곱하기\n",
    "#np.power : 제곱"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0 1 2 3 4 5 6 7 8 9]\n"
     ]
    }
   ],
   "source": [
    "d = np.arange(10)\n",
    "print(d)\n",
    "np.save('test',d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0 1 2 3 4 5 6 7 8 9]\n"
     ]
    }
   ],
   "source": [
    "e = np.load('test.npy')\n",
    "print(e)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1 2 3]\n",
      " [4 5 6]\n",
      " [7 8 9]]\n",
      "--------------------\n",
      "[3 2 1]\n",
      "--------------------\n",
      "[10 28 46]\n",
      "--------------------\n",
      "[18 24 30]\n"
     ]
    }
   ],
   "source": [
    "a = np.array([[1,2,3],[4,5,6],[7,8,9]])\n",
    "b = np.array([3,2,1])\n",
    "c = a.dot(b)\n",
    "\n",
    "print(a)\n",
    "print('-'*20)\n",
    "print(b)\n",
    "print('-'*20)\n",
    "print(c)\n",
    "print('-'*20)\n",
    "print(b.T.dot(a))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "from numpy.linalg import inv, qr, eig, det,svd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 1.61168440e+01, -1.11684397e+00, -9.75918483e-16]),\n",
       " array([[-0.23197069, -0.78583024,  0.40824829],\n",
       "        [-0.52532209, -0.08675134, -0.81649658],\n",
       "        [-0.8186735 ,  0.61232756,  0.40824829]]))"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eig(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-9.51619735392994e-16"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "det(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1 2 3]\n",
      " [4 5 6]\n",
      " [7 8 9]]\n",
      "--------------------\n",
      "[[ 3.15251974e+15 -6.30503948e+15  3.15251974e+15]\n",
      " [-6.30503948e+15  1.26100790e+16 -6.30503948e+15]\n",
      " [ 3.15251974e+15 -6.30503948e+15  3.15251974e+15]]\n",
      "--------------------\n",
      "[[ 0.   1.  -0.5]\n",
      " [ 0.   2.  -1. ]\n",
      " [ 0.   3.   2.5]]\n"
     ]
    }
   ],
   "source": [
    "b = inv(a)\n",
    "print(a)\n",
    "print('-'*20)\n",
    "print(b)\n",
    "print('-'*20)\n",
    "print(a.dot(b))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(array([[-0.21483724,  0.88723069,  0.40824829],\n",
      "       [-0.52058739,  0.24964395, -0.81649658],\n",
      "       [-0.82633754, -0.38794278,  0.40824829]]), array([1.68481034e+01, 1.06836951e+00, 3.33475287e-16]), array([[-0.47967118, -0.57236779, -0.66506441],\n",
      "       [-0.77669099, -0.07568647,  0.62531805],\n",
      "       [-0.40824829,  0.81649658, -0.40824829]]))\n"
     ]
    }
   ],
   "source": [
    "print(svd(a))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(array([[-0.12309149,  0.90453403,  0.40824829],\n",
      "       [-0.49236596,  0.30151134, -0.81649658],\n",
      "       [-0.86164044, -0.30151134,  0.40824829]]), array([[-8.12403840e+00, -9.60113630e+00, -1.10782342e+01],\n",
      "       [ 0.00000000e+00,  9.04534034e-01,  1.80906807e+00],\n",
      "       [ 0.00000000e+00,  0.00000000e+00, -1.11164740e-15]]))\n"
     ]
    }
   ],
   "source": [
    "print(qr(a))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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