Numpy_05-Slicing.ipynb

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   "cell_type": "code",
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   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3752391d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[  1   2   3   4   5   6   7   8   9  10]\n",
      " [ 11  12  13  14  15  16  17  18  19  20]\n",
      " [ 21  22  23  24  25  26  27  28  29  30]\n",
      " [ 31  32  33  34  35  36  37  38  39  40]\n",
      " [ 41  42  43  44  45  46  47  48  49  50]\n",
      " [ 51  52  53  54  55  56  57  58  59  60]\n",
      " [ 61  62  63  64  65  66  67  68  69  70]\n",
      " [ 71  72  73  74  75  76  77  78  79  80]\n",
      " [ 81  82  83  84  85  86  87  88  89  90]\n",
      " [ 91  92  93  94  95  96  97  98  99 100]]\n"
     ]
    }
   ],
   "source": [
    "arr_01 = np.arange(1,101).reshape(10,10)\n",
    "print(arr_01)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b2d0e389",
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   "outputs": [],
   "source": [
    "# Get Element = [row,column]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "78969c46",
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   "outputs": [
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       "4"
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     "execution_count": 4,
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     "output_type": "execute_result"
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   ],
   "source": [
    "arr_01[0,3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f715970f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1, 11])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "arr_01[0:2 , 0]    # arr[row , column]\n",
    "                   # [: , :] -> denotes entire row and col"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "f4d3a36c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 1,  2,  3,  4],\n",
       "       [11, 12, 13, 14],\n",
       "       [21, 22, 23, 24],\n",
       "       [31, 32, 33, 34],\n",
       "       [41, 42, 43, 44],\n",
       "       [51, 52, 53, 54],\n",
       "       [61, 62, 63, 64],\n",
       "       [71, 72, 73, 74],\n",
       "       [81, 82, 83, 84],\n",
       "       [91, 92, 93, 94]])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arr_01[: , 0:4]"
   ]
  },
  {
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   "execution_count": 8,
   "id": "44c0adba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6"
      ]
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     "execution_count": 8,
     "metadata": {},
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   ],
   "source": [
    "arr_01[0,5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ce8b0ce9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arr_01[0,5].ndim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "927af99b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arr_01[: , 0:4].ndim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f21fc3dd",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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