NumPy_04-Mathematical OPS.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "5f49b8ba",
   "metadata": {},
   "source": [
    "# Mathematical Ops"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "70f000ee",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "95da283e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1 2 3]\n",
      " [4 5 6]\n",
      " [7 8 9]]\n",
      "[[1 2 3]\n",
      " [4 5 6]\n",
      " [7 8 9]]\n"
     ]
    }
   ],
   "source": [
    "arr_01 = np.arange(1,10).reshape(3,3)\n",
    "arr_02 = np.arange(1,10).reshape(3,3)\n",
    "print(arr_01)\n",
    "print(arr_02)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a1d29ef9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 2,  4,  6],\n",
       "       [ 8, 10, 12],\n",
       "       [14, 16, 18]])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Addition\n",
    "arr_01+arr_02"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "65f8fd66",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 2  4  6]\n",
      " [ 8 10 12]\n",
      " [14 16 18]]\n"
     ]
    }
   ],
   "source": [
    "arr_add = np.add(arr_01,arr_02)\n",
    "print(arr_add)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "4c5f0d37",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0, 0, 0],\n",
       "       [0, 0, 0],\n",
       "       [0, 0, 0]])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Subtraction\n",
    "arr_01-arr_02"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8ed1ec8f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0 0 0]\n",
      " [0 0 0]\n",
      " [0 0 0]]\n"
     ]
    }
   ],
   "source": [
    "arr_sub = np.subtract(arr_01,arr_02)\n",
    "print(arr_sub)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "3e13634f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 1,  4,  9],\n",
       "       [16, 25, 36],\n",
       "       [49, 64, 81]])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Multiply\n",
    "arr_01*arr_02"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "56e8be7e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 1  4  9]\n",
      " [16 25 36]\n",
      " [49 64 81]]\n"
     ]
    }
   ],
   "source": [
    "arr_mul = np.multiply(arr_01,arr_02)\n",
    "print(arr_mul)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "682253a7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1., 1., 1.],\n",
       "       [1., 1., 1.],\n",
       "       [1., 1., 1.]])"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Division\n",
    "arr_01/arr_02"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "9e3f30f5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1. 1. 1.]\n",
      " [1. 1. 1.]\n",
      " [1. 1. 1.]]\n"
     ]
    }
   ],
   "source": [
    "arr_div = np.divide(arr_01,arr_02)\n",
    "print(arr_div)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4a6e5a88",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 30,  36,  42],\n",
       "       [ 66,  81,  96],\n",
       "       [102, 126, 150]])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Matrix Multiplication\n",
    "arr_01@arr_02"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "e4e8135b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 30  36  42]\n",
      " [ 66  81  96]\n",
      " [102 126 150]]\n"
     ]
    }
   ],
   "source": [
    "arr_mat_mul = arr_01.dot(arr_02)\n",
    "print(arr_mat_mul)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "735c69af",
   "metadata": {},
   "source": [
    "# Max,Min and Numerical OPS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "ad83ae89",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# max element from array\n",
    "arr_test = np.arange(1,10).reshape(3,3)\n",
    "arr_test.max()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "2358ce99",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# max index \n",
    "arr_test.argmax()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "53f284f0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1 2 3]\n",
      " [4 5 6]\n",
      " [7 8 9]]\n",
      "[7 8 9]\n",
      "[3 6 9]\n"
     ]
    }
   ],
   "source": [
    "# max from col or row\n",
    "# axis=0 -> col\n",
    "# axis=1 -> row\n",
    "arr_test = np.arange(1,10).reshape(3,3)\n",
    "arr_test\n",
    "print(arr_test)\n",
    "print(arr_test.max(axis=0))\n",
    "print(arr_test.max(axis=1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "170f7aa3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1 2 3]\n",
      " [4 5 6]\n",
      " [7 8 9]]\n",
      "[1 2 3]\n",
      "[1 4 7]\n"
     ]
    }
   ],
   "source": [
    "# min from col or row\n",
    "# axis=0 -> col\n",
    "# axis=1 -> row\n",
    "arr_test = np.arange(1,10).reshape(3,3)\n",
    "arr_test\n",
    "print(arr_test)\n",
    "print(arr_test.min(axis=0))\n",
    "print(arr_test.min(axis=1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cfaa23d1",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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