numpy_array_slice.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NumPy version = 1.14.5\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "print(f'NumPy version = {np.__version__}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([174, 194, 198, 159, 142, 190, 178, 162, 152, 168])"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.random.randint(140, 200, 10)\n",
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(10,)\n",
      "10\n",
      "1\n"
     ]
    }
   ],
   "source": [
    "print(a.shape)\n",
    "print(a.size)\n",
    "print(a.ndim)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.arange(10)\n",
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 1, 2])"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([4, 5, 6, 7, 8, 9])"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[4:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2, 3, 4])"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[2:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 2, 4, 6, 8])"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[::2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 3, 6, 9])"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[::3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([9, 8, 7, 6, 5, 4, 3, 2, 1, 0])"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[::-1] # reverse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([7, 8, 9])"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[-3:] # last 3 elements"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([6, 7, 8])"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[-4:-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Mercury', 'Venus', 'Earth', 'Mars', 'Jupiter', 'Saturn', 'Uranus',\n",
       "       'Neptune', 'Pluto'], dtype='<U7')"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b = np.array(['Mercury', 'Venus', 'Earth', 'Mars', 'Jupiter', 'Saturn', 'Uranus', 'Neptune', 'Pluto'])\n",
    "b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Earth'"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b[2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## shoe size\n",
    "https://en.wikipedia.org/wiki/Shoe_size#Size_conversion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['EUR', 'Mondo', 'UK', 'US men', 'US women'], dtype='<U8')"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.array(['EUR','Mondo','UK','US men','US women'])\n",
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[2]])"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.argwhere(a == 'UK')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([2]),)"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.where(a == 'UK')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "shoe_size = np.array([[34,215,2,3,4],[34.5,215,2.5,3.5,4.5],[35,220,3,4,5],[35.5,225,3.5,4.5,5.5],[36,225,4,5,6],[36.5,230,4,5,6],[37,235,4.5,5.5,6.5],[37.5,235,5,6,7],[38,240,5.5,6.5,7.5],[38.5,245,5.5,6.5,7.5],[39,245,6,7,8],[39.5,250,6.5,7.5,8.5],[40,255,7,8,9],[40.5,255,7.5,8.5,9.5],[41,260,7.5,8.5,9.5],[41.5,265,8,9,10],[42,265,8.5,9.5,10.5],[42.5,270,9,10,11],[43,275,9.5,10.5,11.5],[43.5,275,9.5,10.5,11.5],[44,280,10,11,12],[44.5,285,10.5,11.5,12.5],[45,285,11,12,13],[45.5,290,11.5,12.5,13.5],[46,295,11.5,12.5,13.5],[46.5,295,12,13,14],[47,300,12.5,13.5,14.5],[47.5,305,13,14,15],[48,305,13,14,15],[48.5,310,13.5,14.5,15.5],[49,315,14,15,16],[49.5,315,14.5,15.5,16.5],[50,320,15,16,17]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 34. , 215. ,   2. ,   3. ,   4. ],\n",
       "       [ 34.5, 215. ,   2.5,   3.5,   4.5],\n",
       "       [ 35. , 220. ,   3. ,   4. ,   5. ],\n",
       "       [ 35.5, 225. ,   3.5,   4.5,   5.5],\n",
       "       [ 36. , 225. ,   4. ,   5. ,   6. ],\n",
       "       [ 36.5, 230. ,   4. ,   5. ,   6. ],\n",
       "       [ 37. , 235. ,   4.5,   5.5,   6.5],\n",
       "       [ 37.5, 235. ,   5. ,   6. ,   7. ],\n",
       "       [ 38. , 240. ,   5.5,   6.5,   7.5],\n",
       "       [ 38.5, 245. ,   5.5,   6.5,   7.5],\n",
       "       [ 39. , 245. ,   6. ,   7. ,   8. ],\n",
       "       [ 39.5, 250. ,   6.5,   7.5,   8.5],\n",
       "       [ 40. , 255. ,   7. ,   8. ,   9. ],\n",
       "       [ 40.5, 255. ,   7.5,   8.5,   9.5],\n",
       "       [ 41. , 260. ,   7.5,   8.5,   9.5],\n",
       "       [ 41.5, 265. ,   8. ,   9. ,  10. ],\n",
       "       [ 42. , 265. ,   8.5,   9.5,  10.5],\n",
       "       [ 42.5, 270. ,   9. ,  10. ,  11. ],\n",
       "       [ 43. , 275. ,   9.5,  10.5,  11.5],\n",
       "       [ 43.5, 275. ,   9.5,  10.5,  11.5],\n",
       "       [ 44. , 280. ,  10. ,  11. ,  12. ],\n",
       "       [ 44.5, 285. ,  10.5,  11.5,  12.5],\n",
       "       [ 45. , 285. ,  11. ,  12. ,  13. ],\n",
       "       [ 45.5, 290. ,  11.5,  12.5,  13.5],\n",
       "       [ 46. , 295. ,  11.5,  12.5,  13.5],\n",
       "       [ 46.5, 295. ,  12. ,  13. ,  14. ],\n",
       "       [ 47. , 300. ,  12.5,  13.5,  14.5],\n",
       "       [ 47.5, 305. ,  13. ,  14. ,  15. ],\n",
       "       [ 48. , 305. ,  13. ,  14. ,  15. ],\n",
       "       [ 48.5, 310. ,  13.5,  14.5,  15.5],\n",
       "       [ 49. , 315. ,  14. ,  15. ,  16. ],\n",
       "       [ 49.5, 315. ,  14.5,  15.5,  16.5],\n",
       "       [ 50. , 320. ,  15. ,  16. ,  17. ]])"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shoe_size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 35., 220.,   3.,   4.,   5.])"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shoe_size[2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 2. ,  2.5,  3. ,  3.5,  4. ,  4. ,  4.5,  5. ,  5.5,  5.5,  6. ,\n",
       "        6.5,  7. ,  7.5,  7.5,  8. ,  8.5,  9. ,  9.5,  9.5, 10. , 10.5,\n",
       "       11. , 11.5, 11.5, 12. , 12.5, 13. , 13. , 13.5, 14. , 14.5, 15. ])"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shoe_size[:, 2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([False, False, False, False, False, False, False, False, False,\n",
       "       False, False, False, False, False,  True, False, False, False,\n",
       "       False, False, False, False, False, False, False, False, False,\n",
       "       False, False, False, False, False, False])"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shoe_size[:, 0] == 41"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 41. , 260. ,   7.5,   8.5,   9.5]])"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shoe_size[shoe_size[:, 0] == 41]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[260. ,   7.5,   8.5,   9.5]])"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shoe_size[:, 1:][shoe_size[:, 0] == 41]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([8.5])"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shoe_size[:, 3][shoe_size[:, 0] == 41]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([8.5])"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shoe_size[:, 3][shoe_size[:, 0] == 41]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['EUR', 'Mondo', 'UK', 'US men', 'US women'], dtype='<U8')"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2])"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "i, = np.where(a == 'UK')\n",
    "i"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[[8.5]]])"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shoe_size[:, np.where(a == 'US men')][shoe_size[:, 0] == 41]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'UK'"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['UK'], dtype='<U8')"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[i]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2, 3])"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "i, = np.where((a == 'UK') | (a == 'US men'))\n",
    "i"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[[7.5, 8.5]]])"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shoe_size[:, np.where((a == 'UK') | (a == 'US men'))][shoe_size[:, 0] == 41]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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