nov16_2024.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fa5d82bbc50>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow([[1,1],[0, 0]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fa5976ac0b8>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "img = [\n",
    "    [0, 0, 1, 1, 0, 0],\n",
    "    [0, 0, 1, 1, 0, 0],\n",
    "    [1, 1, 1, 1, 1, 1],\n",
    "    [1, 1, 1, 1, 1, 1],\n",
    "    [0, 0, 1, 1, 0, 0],\n",
    "    [0, 0, 1, 1, 0, 0],\n",
    "]\n",
    "plt.imshow(img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 6x6 -> 12, 12"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fa59737f4a8>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow([[1,64],[128, 255]], cmap='gray')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Q1: Zoom an image (2d python list) to double length and double width\n",
    "    - clone one pixel to all four\n",
    "    - LERP - linear interpolation\n",
    "Q2: Zoom an image (2D python list) to half size\n",
    "    - average\n",
    "    - min\n",
    "    - max\n",
    "    - See and compare the output\n",
    "Q3: Come up with your own strategy to make these images look good."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "112.0"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[[1,64],[128, 255]] -> [112.0] --> [[112,112], [112, 112]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fa5972bacc0>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow([[112,112], [112, 112]],cmap='gray')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Course: https://pjreddie.com/courses/computer-vision/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Raster and # Vector Images."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# CIrcle, Line..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "l = [\"Circle\", 12091, False, [2,3], print]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'str'> Circle\n",
      "<class 'int'> 12091\n",
      "<class 'bool'> False\n",
      "<class 'list'> [2, 3]\n",
      "<class 'builtin_function_or_method'> <built-in function print>\n"
     ]
    }
   ],
   "source": [
    "for e in l:\n",
    "    print(type(e), e)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Circle'"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "l[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12091"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "l[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "d = {\n",
    "    \"Name\": \"Sandeep\",\n",
    "    \"age\": 44,\n",
    "    \"City\": \"Torono\",\n",
    "    \"tasks\": [1,2,3,4],\n",
    "    \"works\": {'job': 'CloudxLab', 'Project': 'AI'}\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "txt  = json.dumps(d)\n",
    "with open('txt.json', 'w') as t:\n",
    "    t.write(txt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Distance between 2 points.ipynb\t\t      nov3.ipynb\r\n",
      "img_Distance2points\t\t\t      nov6.ipynb\r\n",
      "mbox-short.txt\t\t\t\t      oct5_2024_classnotes.txt\r\n",
      "mbox.txt\t\t\t\t      oct 6.ipynb\r\n",
      "MultipleVariableEquationsSoln_Explained.xlsx  README.md\r\n",
      "MultipleVariableEquationsSoln.ipynb\t      resources.txt\r\n",
      "nov 10.ipynb\t\t\t\t      test_file.txt\r\n",
      "Nov 16.ipynb\t\t\t\t      txt.json\r\n",
      "Nov2.ipynb\t\t\t\t      Untitled.ipynb\r\n"
     ]
    }
   ],
   "source": [
    "!ls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\"Name\": \"Sandeep\", \"age\": 44, \"City\": \"Torono\", \"tasks\": [1, 2, 3, 4], \"works\": {\"job\": \"CloudxLab\", \"Project\": \"AI\"}}"
     ]
    }
   ],
   "source": [
    "!cat txt.json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\"Name\": \"Sandeep\", \"age\": 44, \"City\": \"Torono\", \"tasks\": [1, 2, 3, 4], \"works\": {\"job\": \"CloudxLab\", \"Project\": \"AI\"}}\n"
     ]
    }
   ],
   "source": [
    "with open('txt.json') as t:\n",
    "    txt1 = t.read()\n",
    "    print(txt1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "d1 = json.loads(txt1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(d1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Name': 'Sandeep',\n",
       " 'age': 44,\n",
       " 'City': 'Torono',\n",
       " 'tasks': [1, 2, 3, 4],\n",
       " 'works': {'job': 'CloudxLab', 'Project': 'AI'}}"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Name': 'Sandeep',\n",
       " 'age': 44,\n",
       " 'City': 'Torono',\n",
       " 'tasks': [1, 2, 3, 4],\n",
       " 'works': {'job': 'CloudxLab', 'Project': 'AI'}}"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Sandeep'"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d['Name']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "44"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d['age']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3, 4]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d['tasks']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'CloudxLab'"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d['works']['job']`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "purse = dict() # {}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "purse['money'] = 12\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'money': 12}"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "purse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "del purse['money']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{}"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "purse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Name': 'Sandeep',\n",
       " 'age': 44,\n",
       " 'City': 'Torono',\n",
       " 'tasks': [1, 2, 3, 4],\n",
       " 'works': {'job': 'CloudxLab', 'Project': 'AI'}}"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "d1['height'] = '5ft 9inch'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'5ft 9inch'"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d1['height'] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['Name', 'age', 'City', 'tasks', 'works', 'height'])"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d1.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "key:  Name\n",
      "value:  Sandeep\n",
      "key:  age\n",
      "value:  44\n",
      "key:  City\n",
      "value:  Torono\n",
      "key:  tasks\n",
      "value:  [1, 2, 3, 4]\n",
      "key:  works\n",
      "value:  {'job': 'CloudxLab', 'Project': 'AI'}\n",
      "key:  height\n",
      "value:  5ft 9inch\n"
     ]
    }
   ],
   "source": [
    "for k, v in d1.items():\n",
    "    print(\"key: \", k)\n",
    "    print(\"value: \", v)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "d1[12] = 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "d1[print] = 18"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Name <class 'str'>\n",
      "age <class 'str'>\n",
      "City <class 'str'>\n",
      "tasks <class 'str'>\n",
      "works <class 'str'>\n",
      "height <class 'str'>\n",
      "12 <class 'int'>\n",
      "<built-in function print> <class 'builtin_function_or_method'>\n"
     ]
    }
   ],
   "source": [
    "for k in d1:\n",
    "    print(k, type(k))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "result = list(d1.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "'<' not supported between instances of 'int' and 'str'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-75-5752bd75923c>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mresult\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msort\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m: '<' not supported between instances of 'int' and 'str'"
     ]
    }
   ],
   "source": [
    "result.sort()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "l = [1, '2']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "'<' not supported between instances of 'int' and 'str'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-77-ee7753be6ea1>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;36m1\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0;34m'2'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m: '<' not supported between instances of 'int' and 'str'"
     ]
    }
   ],
   "source": [
    "1 < '2'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Name': 'Sandeep',\n",
       " 'age': 44,\n",
       " 'City': 'Torono',\n",
       " 'tasks': [1, 2, 3, 4],\n",
       " 'works': {'job': 'CloudxLab', 'Project': 'AI'},\n",
       " 'height': '5ft 9inch',\n",
       " 12: 10,\n",
       " <function print>: 18}"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "del d1[12]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Name': 'Sandeep',\n",
       " 'age': 44,\n",
       " 'City': 'Torono',\n",
       " 'tasks': [1, 2, 3, 4],\n",
       " 'works': {'job': 'CloudxLab', 'Project': 'AI'},\n",
       " 'height': '5ft 9inch',\n",
       " <function print>: 18}"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "del d1[print]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "l = list(d1.keys())\n",
    "l.sort()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['City', 'Name', 'age', 'height', 'tasks', 'works']"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "l"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Name': 'Sandeep',\n",
       " 'age': 44,\n",
       " 'City': 'Torono',\n",
       " 'tasks': [1, 2, 3, 4],\n",
       " 'works': {'job': 'CloudxLab', 'Project': 'AI'},\n",
       " 'height': '5ft 9inch'}"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "d1['tasks'].append(50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Name': 'Sandeep',\n",
       " 'age': 44,\n",
       " 'City': 'Torono',\n",
       " 'tasks': [1, 2, 3, 4, 50],\n",
       " 'works': {'job': 'CloudxLab', 'Project': 'AI'},\n",
       " 'height': '5ft 9inch'}"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'Name' in d1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'Name1' in d1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "def check_an_update_tally(d, name):\n",
    "    if name in d:\n",
    "        d[name] += 1\n",
    "    else:\n",
    "        d[name] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'cwen': 1}"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tally = {}\n",
    "check_an_update_tally(tally, \"cwen\")\n",
    "tally"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'cwen': 2}"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "check_an_update_tally(tally, \"cwen\")\n",
    "tally"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'cwen': 2, 'marquard': 1}"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "check_an_update_tally(tally, \"marquard\")\n",
    "tally"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "names = [\"cwen\",\"cwen\",\"marquard\",\"zhen\",\"marquard\",\"zhen\",\"csev\",\"zhen\",\"csev\",\"marquard\",\"csev\",\"zhen\",\"zhen\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [],
   "source": [
    "tally = {}\n",
    "for name in names:\n",
    "    check_an_update_tally(tally, name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'cwen': 2, 'marquard': 3, 'zhen': 5, 'csev': 3}"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tally"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [],
   "source": [
    "most_popular_name = None\n",
    "best_counts = -1\n",
    "for item in tally.items():\n",
    "    name, counts = item\n",
    "    if counts > best_counts:\n",
    "        most_popular_name = name\n",
    "        best_counts = counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'zhen'"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "most_popular_name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "best_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [],
   "source": [
    "tup = (\"sandeep\", 10)\n",
    "name, value = tup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'sandeep'"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Name': 'Sandeep',\n",
       " 'age': 44,\n",
       " 'City': 'Torono',\n",
       " 'tasks': [1, 2, 3, 4, 50],\n",
       " 'works': {'job': 'CloudxLab', 'Project': 'AI'},\n",
       " 'height': '5ft 9inch'}"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "d1['Name'] = 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Name': 10,\n",
       " 'age': 44,\n",
       " 'City': 'Torono',\n",
       " 'tasks': [1, 2, 3, 4, 50],\n",
       " 'works': {'job': 'CloudxLab', 'Project': 'AI'},\n",
       " 'height': '5ft 9inch'}"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'age' in d1 # Constant time operation, O(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "44"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d1['age'] # Constant time operation, O(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'age'"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "l[2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['City', 'Name', 'age', 'height', 'tasks', 'works']"
      ]
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "l"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 129,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'age' in l # Order of n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'height'"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "l[3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "188"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hash('sandeep') % 1234"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Name': 10,\n",
       " 'age': 44,\n",
       " 'City': 'Torono',\n",
       " 'tasks': [1, 2, 3, 4, 50],\n",
       " 'works': {'job': 'CloudxLab', 'Project': 'AI'},\n",
       " 'height': '5ft 9inch'}"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'cwen': 2, 'marquard': 3, 'zhen': 5, 'csev': 3}"
      ]
     },
     "execution_count": 134,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tally"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tally.get('cwen1', 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Distance between 2 points.ipynb\t\t      nov3.ipynb\r\n",
      "img_Distance2points\t\t\t      nov6.ipynb\r\n",
      "mbox-short.txt\t\t\t\t      oct5_2024_classnotes.txt\r\n",
      "mbox.txt\t\t\t\t      oct 6.ipynb\r\n",
      "MultipleVariableEquationsSoln_Explained.xlsx  README.md\r\n",
      "MultipleVariableEquationsSoln.ipynb\t      resources.txt\r\n",
      "nov 10.ipynb\t\t\t\t      test_file.txt\r\n",
      "Nov 16.ipynb\t\t\t\t      txt.json\r\n",
      "Nov2.ipynb\t\t\t\t      Untitled.ipynb\r\n"
     ]
    }
   ],
   "source": [
    "!ls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [],
   "source": [
    "chars = {}\n",
    "with open('mbox.txt') as hdl:\n",
    "    for c in hdl.read():\n",
    "        chars[c] = chars.get(c, 0 ) + 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'F': 20557,\n",
       " 'r': 256629,\n",
       " 'o': 300187,\n",
       " 'm': 130937,\n",
       " ' ': 498382,\n",
       " 's': 229067,\n",
       " 't': 254609,\n",
       " 'e': 385082,\n",
       " 'p': 133993,\n",
       " 'h': 102009,\n",
       " 'n': 178127,\n",
       " '.': 261041,\n",
       " 'a': 319823,\n",
       " 'q': 3097,\n",
       " 'u': 203488,\n",
       " 'd': 115263,\n",
       " '@': 22019,\n",
       " 'c': 215369,\n",
       " 'z': 3305,\n",
       " 'S': 47180,\n",
       " 'J': 4856,\n",
       " '5': 48203,\n",
       " '0': 214249,\n",
       " '9': 40158,\n",
       " ':': 115389,\n",
       " '1': 147110,\n",
       " '4': 58134,\n",
       " '6': 29577,\n",
       " '2': 129239,\n",
       " '8': 48581,\n",
       " '\\n': 132045,\n",
       " 'R': 25230,\n",
       " '-': 199054,\n",
       " 'P': 34454,\n",
       " '<': 8994,\n",
       " 'l': 137484,\n",
       " 'b': 72772,\n",
       " 'k': 76287,\n",
       " 'i': 306085,\n",
       " 'j': 46299,\n",
       " 'g': 61818,\n",
       " '>': 10904,\n",
       " 'v': 72146,\n",
       " 'f': 53695,\n",
       " '(': 40160,\n",
       " '[': 16177,\n",
       " ']': 16177,\n",
       " ')': 40168,\n",
       " '\\t': 28874,\n",
       " 'y': 43993,\n",
       " 'C': 22746,\n",
       " '3': 67724,\n",
       " 'w': 38553,\n",
       " 'L': 7405,\n",
       " 'M': 47178,\n",
       " 'T': 48007,\n",
       " 'A': 35514,\n",
       " ';': 21582,\n",
       " ',': 18674,\n",
       " 'X': 14938,\n",
       " 'U': 9049,\n",
       " 'x': 19073,\n",
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     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "chars"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [],
   "source": [
    "wordcount = {}\n",
    "with open('mbox.txt') as hdl:\n",
    "    for word in hdl.read().split():\n",
    "        wordcount[word] =wordcount.get(word, 0 ) + 1"
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  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [
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       " '611': 5,\n",
       " '12:01:53': 2,\n",
       " '5296342D3C': 1,\n",
       " 'm04C0gnm006795': 1,\n",
       " '07:00:42': 3,\n",
       " 'm04C0gfK006793': 1,\n",
       " 'r39754': 1,\n",
       " 'polls/branches/sakai_2-5-x:': 1,\n",
       " 'tool/src/java/org/sakaiproject/poll/tool': 2,\n",
       " 'tool/src/java/org/sakaiproject/poll/tool/evolvers': 2,\n",
       " 'tool/src/webapp/WEB-INF': 7,\n",
       " '0.6526': 2,\n",
       " 'http://source.sakaiproject.org/viewsvn/?view=rev&rev=39754': 1,\n",
       " '07:00:10': 1,\n",
       " '39754': 1,\n",
       " 'polls/branches/sakai_2-5-x/tool/src/java/org/sakaiproject/poll/tool/evolvers/': 1,\n",
       " 'polls/branches/sakai_2-5-x/tool/src/java/org/sakaiproject/poll/tool/evolvers/SakaiFCKTextEvolver.java': 2,\n",
       " 'Removed:': 132,\n",
       " 'polls/branches/sakai_2-5-x/.classpath': 1,\n",
       " 'polls/branches/sakai_2-5-x/tool/pom.xml': 1,\n",
       " 'polls/branches/sakai_2-5-x/tool/src/webapp/WEB-INF/requestContext.xml': 1,\n",
       " '-r39753': 1,\n",
       " 'https://source.sakaiproject.org/svn/polls/trunk': 23,\n",
       " 'r39753': 2,\n",
       " '13:05:51': 1,\n",
       " '+0200': 18,\n",
       " '1': 492,\n",
       " 'line': 202,\n",
       " 'SAK-12228': 2,\n",
       " 'implmented': 2,\n",
       " 'workaround': 2,\n",
       " 'sugested': 2,\n",
       " 'AB': 2,\n",
       " 'needs': 21,\n",
       " 'tested': 6,\n",
       " 'against': 7,\n",
       " 'trunk': 35,\n",
       " 'build': 34,\n",
       " 'dhorwitz@david-horwitz-6:~/branchManagemnt/sakai_2-5-x>': 34,\n",
       " '-c39753': 1,\n",
       " 'polls/': 1,\n",
       " 'polls/.classpath': 1,\n",
       " 'A': 134,\n",
       " 'polls/tool/src/java/org/sakaiproject/poll/tool/evolvers': 1,\n",
       " 'polls/tool/src/java/org/sakaiproject/poll/tool/evolvers/SakaiFCKTextEvolver.java': 1,\n",
       " 'C': 44,\n",
       " 'polls/tool/src/webapp/WEB-INF/requestContext.xml': 2,\n",
       " 'polls/tool/pom.xml': 1,\n",
       " 'resolved': 13,\n",
       " 'Resolved': 11,\n",
       " 'conflicted': 10,\n",
       " 'state': 12,\n",
       " \"'polls/tool/src/webapp/WEB-INF/requestContext.xml\": 1,\n",
       " '06:08:27': 4,\n",
       " '[141.211.14.98])': 141,\n",
       " 'casino.mail.umich.edu': 141,\n",
       " 'm04B8Qw9001368;': 1,\n",
       " '06:08:26': 1,\n",
       " '477E13A5.30FC0.24054': 1,\n",
       " '06:08:23': 1,\n",
       " '784A476D7B;': 1,\n",
       " '11:08:12': 1,\n",
       " '<200801041106.m04B6lK3006677@nakamura.uits.iupui.edu>': 1,\n",
       " '585': 3,\n",
       " '11:07:56': 1,\n",
       " '1CACC42D0C': 1,\n",
       " '11:07:58': 1,\n",
       " 'm04B6lWM006679': 1,\n",
       " '06:06:47': 3,\n",
       " 'm04B6lK3006677': 1,\n",
       " 'polls/trunk:': 3,\n",
       " '0.6948': 3,\n",
       " 'http://source.sakaiproject.org/viewsvn/?view=rev&rev=39753': 1,\n",
       " '06:05:51': 1,\n",
       " '39753': 1,\n",
       " 'polls/trunk/tool/src/java/org/sakaiproject/poll/tool/evolvers/': 1,\n",
       " 'polls/trunk/tool/src/java/org/sakaiproject/poll/tool/evolvers/SakaiFCKTextEvolver.java': 1,\n",
       " 'polls/trunk/.classpath': 1,\n",
       " 'polls/trunk/tool/pom.xml': 2,\n",
       " 'polls/trunk/tool/src/webapp/WEB-INF/requestContext.xml': 2,\n",
       " '04:49:08': 4,\n",
       " '[141.211.14.92])': 132,\n",
       " 'galaxyquest.mr.itd.umich.edu': 180,\n",
       " '(galaxyquest.mr.itd.umich.edu': 90,\n",
       " '[141.211.93.145])': 90,\n",
       " 'score.mail.umich.edu': 132,\n",
       " 'm049n60G017588;': 1,\n",
       " '04:49:06': 1,\n",
       " '477E010C.48C2.10259': 1,\n",
       " '04:49:03': 1,\n",
       " '254CC8CDEE;': 1,\n",
       " '09:48:55': 1,\n",
       " '<200801040947.m049lUxo006517@nakamura.uits.iupui.edu>': 1,\n",
       " '246': 2,\n",
       " '09:48:36': 1,\n",
       " '8C13342C92': 1,\n",
       " '09:48:40': 1,\n",
       " 'm049lU3P006519': 1,\n",
       " '04:47:30': 3,\n",
       " 'm049lUxo006517': 1,\n",
       " 'r39752': 1,\n",
       " 'podcasts/branches/sakai_2-5-x/podcasts-app/src/webapp:': 2,\n",
       " 'css': 7,\n",
       " 'podcasts': 5,\n",
       " '0.6528': 2,\n",
       " 'http://source.sakaiproject.org/viewsvn/?view=rev&rev=39752': 1,\n",
       " '04:47:16': 1,\n",
       " '39752': 1,\n",
       " 'podcasts/branches/sakai_2-5-x/podcasts-app/src/webapp/css/podcaster.css': 2,\n",
       " 'podcasts/branches/sakai_2-5-x/podcasts-app/src/webapp/podcasts/podMain.jsp': 2,\n",
       " '-r39641': 1,\n",
       " 'https://source.sakaiproject.org/svn/podcasts/trunk': 6,\n",
       " 'r39641': 2,\n",
       " 'josrodri@iupui.edu': 131,\n",
       " '2007-12-28': 8,\n",
       " '23:44:24': 1,\n",
       " '28': 561,\n",
       " 'SAK-9882:': 4,\n",
       " 'refactored': 7,\n",
       " 'podMain.jsp': 2,\n",
       " 'right': 6,\n",
       " 'way': 7,\n",
       " '(at': 2,\n",
       " 'least': 2,\n",
       " 'much': 4,\n",
       " 'closer': 4,\n",
       " 'to)': 2,\n",
       " '-c39641': 1,\n",
       " 'podcasts/': 2,\n",
       " 'podcasts/podcasts-app/src/webapp/podcasts/podMain.jsp': 2,\n",
       " 'podcasts/podcasts-app/src/webapp/css/podcaster.css': 2,\n",
       " 'merged': 21,\n",
       " 'manualy': 2,\n",
       " '04:33:44': 4,\n",
       " 'workinggirl.mr.itd.umich.edu': 174,\n",
       " '(workinggirl.mr.itd.umich.edu': 87,\n",
       " '[141.211.93.143])': 87,\n",
       " 'm049Xge3031803;': 1,\n",
       " '04:33:42': 1,\n",
       " '477DFD6C.75DBE.26054': 1,\n",
       " '04:33:35': 1,\n",
       " '6C929BA656;': 1,\n",
       " '09:33:27': 1,\n",
       " '<200801040932.m049W2i5006493@nakamura.uits.iupui.edu>': 1,\n",
       " '153': 2,\n",
       " '09:33:10': 1,\n",
       " '6C69423767': 1,\n",
       " '09:33:13': 1,\n",
       " 'm049W3fl006495': 1,\n",
       " '04:32:03': 1,\n",
       " 'm049W2i5006493': 1,\n",
       " '04:32:02': 2,\n",
       " 'r39751': 1,\n",
       " 'images': 4,\n",
       " 'http://source.sakaiproject.org/viewsvn/?view=rev&rev=39751': 1,\n",
       " '04:31:35': 1,\n",
       " '39751': 1,\n",
       " 'podcasts/branches/sakai_2-5-x/podcasts-app/src/webapp/images/rss-feed-icon.png': 1,\n",
       " 'podcasts/branches/sakai_2-5-x/podcasts-app/src/webapp/podcasts/podPermissions.jsp': 1,\n",
       " 'podcasts/branches/sakai_2-5-x/podcasts-app/src/webapp/podcasts/podDelete.jsp': 1,\n",
       " 'podcasts/branches/sakai_2-5-x/podcasts-app/src/webapp/podcasts/podNoResource.jsp': 1,\n",
       " 'podcasts/branches/sakai_2-5-x/podcasts-app/src/webapp/podcasts/podOptions.jsp': 1,\n",
       " '-r39146': 1,\n",
       " 'r39146': 2,\n",
       " '2007-12-12': 59,\n",
       " '21:40:33': 1,\n",
       " '(Wed,': 347,\n",
       " '12': 737,\n",
       " 'other': 20,\n",
       " 'pages': 4,\n",
       " 'as': 99,\n",
       " 'well': 9,\n",
       " 'take': 8,\n",
       " 'advantage': 4,\n",
       " 'proper': 7,\n",
       " 'jsp': 4,\n",
       " 'components': 7,\n",
       " 'validation': 6,\n",
       " 'cleanup.': 2,\n",
       " '-c39146': 1,\n",
       " 'D': 16,\n",
       " 'podcasts/podcasts-app/src/webapp/podcasts/podPermissions.jsp': 1,\n",
       " 'podcasts/podcasts-app/src/webapp/podcasts/podDelete.jsp': 1,\n",
       " 'podcasts/podcasts-app/src/webapp/podcasts/podNoResource.jsp': 1,\n",
       " ...}"
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wordcount"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Q: Do the word count after cleaning the data. remove non-alphabatic characters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.image as image\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "myimg = image.imread('istockphoto-2155904673-1024x1024.jpg')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Q4: Write code to convert colored image into grayscale as show below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f7b51c996a0>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(myimg, cmap='gray')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f7b4261b668>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(new_image, cmap='gray')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Tuples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = ('Glenn', 'Sally', 'Joseph')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Glenn'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "'tuple' object does not support item assignment",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-17-5c386b4a5088>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mx\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m10\u001b[0m \u001b[0;31m# ReadOnly\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m: 'tuple' object does not support item assignment"
     ]
    }
   ],
   "source": [
    "x[0] = 10 # ReadOnly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "import math"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "def distance(point1, point2):\n",
    "    x1, y1 = point1\n",
    "    x2, y2 = point2\n",
    "    \n",
    "    dx, dy = x1 - x2, y1 - y2\n",
    "    \n",
    "    return math.sqrt(dx*dx + dy*dy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10.770329614269007"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "point1 = (0, 1)\n",
    "point2 = (10, 5)\n",
    "distance(point1, point2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10.770329614269007"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "point1 = [0, 1]\n",
    "point2 = [10, 5]\n",
    "distance(point1, point2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Tuples:\n",
    "    - Safer (read-only)\n",
    "    - Faster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = (1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "int"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x + 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tuple"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = (1,)\n",
    "type(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "can only concatenate tuple (not \"int\") to tuple",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-37-eaf7b6991020>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mx\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m: can only concatenate tuple (not \"int\") to tuple"
     ]
    }
   ],
   "source": [
    "x + 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "table = [(\"Name\",\"Gender\",\"Age\"), (\"Sandeep\", 'M', 44)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "def add_complex_num(complex1, complex2):\n",
    "    r1, i1 = complex1\n",
    "    r2, i2 = complex2\n",
    "    return (r1+r2, i1+i2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3, 4)"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "add_complex_num((1,1), (2, 3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "'int' object is not iterable",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-64-91cc07da9275>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0madd_complex_num\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m<ipython-input-62-98f6cc062d79>\u001b[0m in \u001b[0;36madd_complex_num\u001b[0;34m(complex1, complex2)\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0madd_complex_num\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcomplex1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcomplex2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m     \u001b[0mr1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mi1\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcomplex1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m     \u001b[0mr2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mi2\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcomplex2\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mr1\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0mr2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mi1\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0mi2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mTypeError\u001b[0m: 'int' object is not iterable"
     ]
    }
   ],
   "source": [
    "add_complex_num(1,2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "(x,y,z) = (10, 10, 20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "z"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "(x,y,z) = [10, 10, 20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "z"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = (3,4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "'tuple' object does not support item assignment",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-58-d8268ef9d1f3>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mx\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m10\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m: 'tuple' object does not support item assignment"
     ]
    }
   ],
   "source": [
    "x[0] = 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3, 4)"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = (9, 3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(9, 3)"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "rectangle1 = ((1,2), (5, 6))\n",
    "rectangle2 = ((10,20), (2, 6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Q5: Find the \n",
    "def find_intersection(rect1, rect2):\n",
    "    "
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Lexical Comparision"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1 < 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(1, 1) < (1, 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(1, 2, 3) < (3, 2, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(1, 1, 1) < (1, 1, 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "# sort the data base on first_name, lastname"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "names = [\"Sandeep\", \"Akash\", \"Rohan\", \"Amit\", \"Toshi\", \"Ashok\", \"Sachin\", \"Sarika\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "names.sort()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Akash', 'Amit', 'Ashok', 'Rohan', 'Sachin', 'Sandeep', 'Sarika', 'Toshi']"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Sort list first letter and then last letter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "def mykey(name):\n",
    "    return (name[0], name[-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "names.sort(key=mykey)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Akash', 'Ashok', 'Amit', 'Rohan', 'Sarika', 'Sachin', 'Sandeep', 'Toshi']"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Sort the list by first letter and length"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "def mykey1(name):\n",
    "    return (name[0], len(name))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "names.sort(key=mykey1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Amit', 'Akash', 'Ashok', 'Rohan', 'Sarika', 'Sachin', 'Sandeep', 'Toshi']"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Problem Statment:\n",
    "# We have words from a dictionary. We want to bring the analgrams together\n",
    "# An anagram is basicallt rearrangement of letter or you can it contains same set of letter but in different order.\n",
    "cat <> act, tac, ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [],
   "source": [
    "words = [\"car\", \"art\", \"cat\", \"rat\", \"arc\", \"tar\", \"act\"]\n",
    "def mykey3(name):\n",
    "    return (''.join(sorted(name)), name)\n",
    "words.sort(key=mykey3)\n",
    "# [art, tar, rat, car, arc, cat, act]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['arc', 'car', 'act', 'cat', 'art', 'rat', 'tar']"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'act'"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "''.join(sorted(\"act\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('acr',)"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mykey3(\"car\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('acr',)"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mykey3(\"arc\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('acr', 'arc'),\n",
       " ('acr', 'car'),\n",
       " ('act', 'act'),\n",
       " ('act', 'cat'),\n",
       " ('art', 'art'),\n",
       " ('art', 'rat'),\n",
       " ('art', 'tar')]"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "words = [\"car\", \"art\", \"cat\", \"rat\", \"arc\", \"tar\", \"act\"]\n",
    "new_list = []\n",
    "for word in words:\n",
    "    new_word = (''.join(sorted(word)), word)\n",
    "    new_list.append(new_word)\n",
    "new_list.sort()\n",
    "new_list"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Q6: \n",
    "\n",
    "You have millions of strings in an list, you have to group the anagrams together.\n",
    "\n",
    "Input: [\"car\", \"art\", \"cat\", \"rat\", \"arc\", \"tar\", \"act\"]\n",
    "\n",
    "Expected Output:\n",
    "arc, car\n",
    "act, cat\n",
    "art, rat, tar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Try the other approach"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# We will discuss the complexity the two methods."
   ]
  }
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