numpy_2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import numpy as np\n",
    "# x = np.array([[2,5,8,9], [8,9,6,5]])\n",
    "# x.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# y = np.array(['a' , 'v' , 'x'])\n",
    "# y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5\n",
      "()\n",
      "0\n",
      "int64\n",
      "<class 'numpy.ndarray'>\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "x = np.array(5)\n",
    "print(x)\n",
    "print(x.shape)\n",
    "print(x.ndim)\n",
    "print(x.dtype)\n",
    "print(type(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# type(x)\n",
    "print(x.shape)\n",
    "print(x.ndim)\n",
    "x.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 0.  1.  2.  3.  4.]\n",
      " [ 5.  6.  7.  8.  9.]\n",
      " [10. 11. 12. 13. 14.]\n",
      " [15. 16. 17. 18. 19.]\n",
      " [20. 21. 22. 23. 24.]\n",
      " [25. 26. 27. 28. 29.]\n",
      " [30. 31. 32. 33. 34.]\n",
      " [35. 36. 37. 38. 39.]\n",
      " [40. 41. 42. 43. 44.]]\n",
      "2\n"
     ]
    }
   ],
   "source": [
    "my_arr = np.arange(45).reshape(9,5).astype('float')\n",
    "print(my_arr)\n",
    "print(my_arr.ndim)\n",
    "# my_arr.astype('float')\n",
    "# x = np.array([1,2,3] , dtype = 'float')\n",
    "# x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[[ 0  1  2]\n",
      "  [ 3  4  5]\n",
      "  [ 6  7  8]]\n",
      "\n",
      " [[ 9 10 11]\n",
      "  [12 13 14]\n",
      "  [15 16 17]]\n",
      "\n",
      " [[18 19 20]\n",
      "  [21 22 23]\n",
      "  [24 25 26]]\n",
      "\n",
      " [[27 28 29]\n",
      "  [30 31 32]\n",
      "  [33 34 35]]\n",
      "\n",
      " [[36 37 38]\n",
      "  [39 40 41]\n",
      "  [42 43 44]]]\n"
     ]
    }
   ],
   "source": [
    "arr_3d = np.arange(45).reshape(5,3,3)\n",
    "\n",
    "print(arr_3d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11])"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.arange(12)\n",
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 2, 4, 6])"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[0:7:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0,  1,  2,  3,  4],\n",
       "       [ 5,  6,  7,  8,  9],\n",
       "       [10, 11, 12, 13, 14],\n",
       "       [15, 16, 17, 18, 19],\n",
       "       [20, 21, 22, 23, 24],\n",
       "       [25, 26, 27, 28, 29],\n",
       "       [30, 31, 32, 33, 34],\n",
       "       [35, 36, 37, 38, 39],\n",
       "       [40, 41, 42, 43, 44],\n",
       "       [45, 46, 47, 48, 49],\n",
       "       [50, 51, 52, 53, 54],\n",
       "       [55, 56, 57, 58, 59],\n",
       "       [60, 61, 62, 63, 64],\n",
       "       [65, 66, 67, 68, 69],\n",
       "       [70, 71, 72, 73, 74]])"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bg_array = np.arange(75).reshape(15 , 5)\n",
    "bg_array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "a[:7:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 0  1  2  3]\n",
      " [ 4  5  6  7]\n",
      " [ 8  9 10 11]\n",
      " [12 13 14 15]\n",
      " [16 17 18 19]\n",
      " [20 21 22 23]]\n"
     ]
    }
   ],
   "source": [
    "b = np.arange(24).reshape(6,4)\n",
    "print(b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "bg_array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[18]]\n",
      "(1, 1)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# b[start:end,start:end]\n",
    "new_b = b[4:5,2:3]\n",
    "print(new_b)\n",
    "print(new_b.shape)\n",
    "new_b.ndim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "assignment = np.arange(54).reshape(6,9)\n",
    "assignment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "assignment[3:,5: ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "array_3d = np.arange(36).reshape(6,6)\n",
    "array_3d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# array_3d[0:2,0:4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "b = np.arange(27).reshape(3,3,3)\n",
    "bb[1:2,0:1,0:1]\n",
    "b.ndim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "index = np.arange(36).reshape(6,6)\n",
    "index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "index[3,3] = 8\n",
    "index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "rep_3d = np.arange(27).reshape(3,3,3)\n",
    "rep_3d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "rep_3d[1, 0:2, 2:] = 5\n",
    "rep_3d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[[ 0,  1,  2],\n",
       "        [ 3,  4,  5],\n",
       "        [ 6,  7,  8]],\n",
       "\n",
       "       [[ 9, 10, 11],\n",
       "        [12, 13, 14],\n",
       "        [15, 16, 17]],\n",
       "\n",
       "       [[18, 19, 20],\n",
       "        [21, 22, 23],\n",
       "        [24, 25, 26]]])"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arr_3d = np.arange(27).reshape(3,3,3)\n",
    "arr_3d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[[13],\n",
       "        [16]]])"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arr_3d[1:2,1:3,1:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[[ 0,  1,  2,  3,  4],\n",
       "        [ 5,  6,  7,  8,  9],\n",
       "        [10, 11, 12, 13, 14]],\n",
       "\n",
       "       [[15, 16, 17, 18, 19],\n",
       "        [20, 21, 22, 23, 24],\n",
       "        [25, 26, 27, 28, 29]],\n",
       "\n",
       "       [[30, 31, 32, 33, 34],\n",
       "        [35, 36, 37, 38, 39],\n",
       "        [40, 41, 42, 43, 44]],\n",
       "\n",
       "       [[45, 46, 47, 48, 49],\n",
       "        [50, 51, 52, 53, 54],\n",
       "        [55, 56, 57, 58, 59]],\n",
       "\n",
       "       [[60, 61, 62, 63, 64],\n",
       "        [65, 66, 67, 68, 69],\n",
       "        [70, 71, 72, 73, 74]]])"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "assignment = np.arange(75).reshape(5,3,5)\n",
    "assignment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[[  0,   1,   2,   3,   4],\n",
       "        [  5,   6,   7,   8,   9],\n",
       "        [ 10,  11,  12,  13,  14]],\n",
       "\n",
       "       [[ 15,  16,  17,  18,  19],\n",
       "        [ 20,  21,  22,  23,  24],\n",
       "        [ 25,  26,  27,  28,  29]],\n",
       "\n",
       "       [[ 30,  31,  32,  33,  34],\n",
       "        [ 35,  36,  37,  38,  39],\n",
       "        [ 40,  41,  42,  43,  44]],\n",
       "\n",
       "       [[ 45,  46,  47,  48,  49],\n",
       "        [ 50,  51,  52,  53,  54],\n",
       "        [ 55,  56, 100,  58,  59]],\n",
       "\n",
       "       [[ 60,  61,  62,  63,  64],\n",
       "        [ 65,  66,  67,  68,  69],\n",
       "        [ 70,  71,  72,  73,  74]]])"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "assignment[3,2,2] = 100\n",
    "assignment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1., 1., 1., 1., 1., 1., 1., 1., 1., 1.],\n",
       "       [1., 0., 0., 0., 0., 0., 0., 0., 0., 1.],\n",
       "       [1., 0., 0., 0., 0., 0., 0., 0., 0., 1.],\n",
       "       [1., 0., 0., 0., 0., 0., 0., 0., 0., 1.],\n",
       "       [1., 0., 0., 0., 0., 0., 0., 0., 0., 1.],\n",
       "       [1., 0., 0., 0., 0., 0., 0., 0., 0., 1.],\n",
       "       [1., 0., 0., 0., 0., 0., 0., 0., 0., 1.],\n",
       "       [1., 0., 0., 0., 0., 0., 0., 0., 0., 1.],\n",
       "       [1., 0., 0., 0., 0., 0., 0., 0., 0., 1.],\n",
       "       [1., 1., 1., 1., 1., 1., 1., 1., 1., 1.]])"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = np.ones((10,10))\n",
    "x[1:9 , 1:9]= 0\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "file_extension": ".py",
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   "nbconvert_exporter": "python",
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