6.4 Arithmetic With NumPy Arrays.ipynb

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   "source": [
    "<center><em>Copyright! This material is protected, please do not copy or distribute.    by:Taher Assaf</em></center>"
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   "cell_type": "markdown",
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   "source": [
    "***\n",
    "<h1 align=\"center\">Udemy course : Python Bootcamp for Data Science 2021 Numpy Pandas & Seaborn</h1> \n",
    "\n",
    "***"
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   "source": [
    "## 6.4 Arithmetic With NumPy Arrays "
   ]
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   "source": [
    "First we import Numpy library:"
   ]
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   "source": [
    "import numpy as np"
   ]
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   "source": [
    "We can create two dimensional numpy array like this:"
   ]
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1, 2, 3],\n",
       "       [4, 5, 6]])"
      ]
     },
     "execution_count": 2,
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   "source": [
    "array = np.array([[1,2,3], [4,5,6]])\n",
    "array"
   ]
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   "source": [
    "We can do element-wise multiplication of this array by itself, like this:"
   ]
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   "execution_count": 3,
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 1,  4,  9],\n",
       "       [16, 25, 36]])"
      ]
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     "execution_count": 3,
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   "source": [
    "array * array"
   ]
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   "source": [
    "We can do element-wise subtraction of this array from itself, like this:"
   ]
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   "execution_count": 4,
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    {
     "data": {
      "text/plain": [
       "array([[0, 0, 0],\n",
       "       [0, 0, 0]])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "array - array"
   ]
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   "cell_type": "markdown",
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   "source": [
    "We can do element-wise multiplication of this array by number 4, like this:"
   ]
  },
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   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "hide_input": false
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 4,  8, 12],\n",
       "       [16, 20, 24]])"
      ]
     },
     "execution_count": 5,
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   "source": [
    "array * 4"
   ]
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   "source": [
    "We can do element-wise division of this array by number 2, like this:"
   ]
  },
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   "cell_type": "code",
   "execution_count": 6,
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    "hide_input": false
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.5, 1. , 1.5],\n",
       "       [2. , 2.5, 3. ]])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "array /2"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "We can raise each element to the power of two, like this:"
   ]
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   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "hide_input": false
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1.        , 1.41421356, 1.73205081],\n",
       "       [2.        , 2.23606798, 2.44948974]])"
      ]
     },
     "execution_count": 7,
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   "source": [
    "array ** 0.5"
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   "cell_type": "markdown",
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   "source": [
    "We can do boolean operation like this:"
   ]
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   "execution_count": 8,
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    "hide_input": false
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      "text/plain": [
       "array([[False, False, False],\n",
       "       [False,  True,  True]])"
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     "execution_count": 8,
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   "source": [
    "array > 4"
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   "source": [
    "***\n",
    "\n",
    "<h1 align=\"center\">Thank You</h1> \n",
    "\n",
    "***"
   ]
  }
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