Python Set.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "________________________________________________________________________________________________________________________\n",
    "\n",
    "\n",
    "* Yuvraj Sutar \n",
    "* yuvrajsutar009@gmail.com\n",
    "_ _________________________________________________________________________________________________________________________\n",
    "_  _________________________________________________________________________________________________________________________"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Python Sets"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Unordered-indexes does not start with 0\n",
    "- sets are written with curly {} brackets\n",
    "- used to perform mathematical set operations like union, intersection, symmetric difference etc.\n",
    "- Unhashable- can't access values from their indices e.g. numbers and sets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1, 2, 3, 4}"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Set creation\n",
    "# set of integers\n",
    "my_set = {1, 2, 3,3,3,4,3}\n",
    "my_set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "set"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(my_set)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# set of mixed datatypes\n",
    "my_set = {1.0, \"Hello\", (1, 2, 3)}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{(1, 2, 3), 1.0, 'Hello'}"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1, 2, 3, 4, 6, 52, 100}"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# set do not have duplicates\n",
    "my_set = {1,100,52,6,3,100,2,2,2,2,2,2,4,4,4}\n",
    "my_set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3, 500]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_set.add(500)\n",
    "list(my_set)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# we can make set from a list\n",
    "my_set = [1,2,3,2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1, 2, 3}"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Creating empty set-Little but tricky\n",
    "#Empty curly braces {} will make an empty dictionary in Python.\n",
    "#Use set()function\n",
    "# initialize a with {}\n",
    "a = {}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{}"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# initialize a with set()\n",
    "a = set()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "set()"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "set"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Add item into set\n",
    "#add()-To add one item to a set use the \n",
    "#update()-To add more than one item to a set\n",
    "#The update() method can take tuples, lists, strings or other sets as its argument. \n",
    "#In all cases, duplicates are avoided.\n",
    "# initialize my_set\n",
    "my_set = {1,100,3,2,5,4}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1, 2, 3, 4, 5, 100}"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{4}"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_set.pop()\n",
    "my_set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_set.remove(100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1, 2, 3, 4, 5}"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# add an element\n",
    "my_set.add(6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1, 2, 3, 4, 5}"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "# add multiple elements\n",
    "my_set.update([3,30,4,60])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1, 2, 3, 4, 5, 30, 60}"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# add list and set\n",
    "my_set.update([4,5], {1,6,8})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1, 2, 3, 4, 5, 6, 8}"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_set"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Python Set Operation\n",
    "# 1-Union\n",
    "# 2-Intersection\n",
    "# 3-Difference\n",
    "# 4-Symmetric Difference\n"
   ]
  },
  {
   "attachments": {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![Union-in-python.jpg](attachment:Union-in-python.jpg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Union-Union is performed using | operator.\n",
    "# initialize A and B\n",
    "A = {1, 2, 3}\n",
    "B = {3,4, 5}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1, 2, 3, 4, 5, 6}"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A.union(B)"
   ]
  },
  {
   "attachments": {
    "intersection-in-python.jpg": {
     "image/jpeg": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![intersection-in-python.jpg](attachment:intersection-in-python.jpg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Intersection-Intersection is performed using & operator.\n",
    "# initialize A and B\n",
    "A = {1, 2, 3, 4}\n",
    "B = {3,4, 5, 6}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{3, 4}"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A.intersection(B)"
   ]
  },
  {
   "attachments": {
    "set%20diference.png": {
     "image/png": "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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![set%20diference.png](attachment:set%20diference.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Difference-performed using - operator.\n",
    "# initialize A and B\n",
    "A = {1, 2, 3, 4, 5}\n",
    "B = {4, 5, 6, 7, 8,9}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "A-B"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{6, 7, 8, 9}"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "B"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1, 2, 3, 4, 5}"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A"
   ]
  },
  {
   "attachments": {
    "set%20symmtric%20difference.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![set%20symmtric%20difference.png](attachment:set%20symmtric%20difference.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Symmetric Difference-Symmetric difference is performed using ^ operator.\n",
    "# initialize A and B\n",
    "A = {1, 2, 3, 4, 5}\n",
    "B = {4, 5, 6, 7, 8}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1, 2, 3, 6, 7, 8}"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A ^ B"
   ]
  },
  {
   "attachments": {
    "Set%20Methods.png": {
     "image/png": 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1+l4cyU2xuKx9bHTVD5UTuXtWbqTloJW0tdHTjAAAnMur7m77cVdy66vcpMT1d6bnaUmNJt4DXLLFzbC4chfXtd8ajacP8XS3jPeNkU1pULfyMjZSRox9XldnmWYEAOBcTrq7BXDpFttWAACuHbtb4E1jdwsA2Bh2twAAANgOdrcAAADYDna3AAAA2A52twAAANgOdrcAAADYDna3AAAA2A52twAAANgOdrcAAADYjmN2tz8DAAAAl6ruWVfE393+FQAAALg8R/5mQh0NAAAAXBJ2twAAANgOdrcAAADYDna3AAAA2A52twAAANgOdrcAAADYDna3AAAA2A52twAAANiO19zdfrx//+72Qz1oFsF0WI8/3LYW8DYdcsucnt2JV3sjnv3DAgCc32XvbpcZ1/xaBQ6RrvnVf43bf8ucw5luw/XzsgW8v/9YD/Yask/4YT1tVQCA07no3e38urBeXiDYsHyF369tH/feMmfB7jbE7hYALsVJd7fpTdLIG8XeAl0PB8HobWEleYNgs+r1bZf+sAU79JaRO24Yn0l+v4fSPXZ7WwfFd5bXbP26uqk3Bd6/94p9VlmQr0TWfXs7ZMqpLNYl51GH90hwBovsYKZsWtJAFtO6PVQmnVcFAHgtZ/ruNr9T8jM/teQ9uDsYv6x4eWCj+jWvl/na3TEFvdcK3M/3TmfV69i0J5tqK09NCaXpiwt6UxmpKMutY6TZK0mm19TEkUxb0mTCecSUvXOmtiQxdJfPVWpab2kO8wAAXtGJd7f2wO/K+0FeHv7SCIP9rTGQVGBbZH80Ng+8ZSxoVrdYKbGpSTKNlux0SJITemLU66vRpkxUFtnlqGZau2RqcKSrHpYdDhmyw5miJanSL+FUReWKwzwAgFd0yt1tegXUx72/U+RdtCdoreBlIanAppRNlKuX/+G3TJGOzfI2SdVrzJpeu99kUrJb1s56YtQrMe2Op2w009qlP6peDCV02eGQITucKVrSLA2tn+v+eQAAr+jUu9v6CrAHf20eHgzfFpbJGwSbZNd7vfKzfqkffMt8uO33RnDveCiNrU3Ns7bOX6TintH/WF6mXvTKwqQpE6VoD3+8v08tzbR2ydTgyIuZlCal5xFTdjjTckki+FyDEx/nAQC8olPubss7IEt/zUTeKQcG59dFfx8BG2NXe7vwC7/YD71l+v1mwfk2GQbUfr3FpgUUfZjp0/TEqTcFaq80h4nmdWqmtVtmzfOBTZu1jun15sxEs1dmmpekos5WNKkFF6sCALyW0+5un0tfRYm9ZXhzAAAAYNUJd7f5a4xnsSL565Cyo01foJTW3/3d36V/AAAAAKPL/u4WAAAAeAp2twAAANgOdrcAAADYDna3AAAA2A52twAAANgOdrcAAADYDna3AAAA2A52twAAANiOY3a3PwMAAACXqu5ZV8Tf3dYWAAAAcEmO/M2E2gIAAAAuCbtbAAAAbAe7WwAAAGwHu1sAAABsB7tbAAAAbAe7WwAAAGwHu1sAAABsB7tbAAAAbMd5d7efHm5uHj7Vg6M93r17V8qk1t1jiQJ4LXYnlhuxN1bZQ+CFbtr9c51feiSZF3jM7WTTnHoKALhi17e7XTzXL/ENBxyj7oyK69q89NswvB+He/bqdrdPWPDLndtkLD18oi/rhKUB4FyubXc7vz6eXxO4CLqvuLI9Rt9o9oYaTubldoDhXC/vCQs+4U9tXMUJJzphaQA4lxPvbtMjuUpPZt2JelcP2XO1abH8TL8rcaswPuILLQpcL91XjFe63xk1lrpvbuodZIN6gtwdPVaLDiXlIDWHRA1pwSq4TVOsJPaGk/zUlWeut7SWD5Yx8DJtjMw1D7bO/gFZWk+Q4vOgYG2eVLN8Hct1jj1pAXd3efBiYB+Xau/7KRbLVUhxqRec0UCqyGdYlYgfz4sAgKtx0t1telLWR+Snhzt73NrTtT5109O5Pn896Hp3fh77Y9bi8zM3DALXZrwp+kWt7Xatp1jNlVtEMhcJJep3isVq7zhpbkqZvz0+1M6Ij+2VfQohc5TqLWcosFyGGpY0zRUNtpjMEkwTDQrXpnOPox5atJHe1PaDXKQeeb1FUKJ9vm6MSnHvGNa25zPMP9YhEnyYAHCtTrm7nZ+wPZIeq6o+YjXsie35a/ojWIVB4NrYhdyNF73KN4bcF3qL+M5EbwrPaFGL1LzUp3J3mbFmzHTMcjqdt7OgF9P19nWEyxBlRV0Z1OZaO4c2pzR98nCQd+e2r60F27B+PNIT1bavNekFpbJOMo6shlUsJ+rVlGdXlmjGRanSE84OANflFXe34cO3BvsTdpFo8WlYHASuTb/q053gt04PC7kv9BbxVL0pJKMkWKBVXNxgKnWZZW9a3FCttkpM5+08z+iMfSE7lpENFZo2VzhYRkjTU8NBGrT2+tqsZN8OCl2mtvNRr9ELSmWdZBxZjatYTLSstktKqz/WcKIwCADX5ZS72/ScbI/b4DcT5PFc/vTTH6vpAVyaiyd29AD3osA1033FcO/YdqRd9fWPw+VG0HsiuoWGhHSQftOzH0d34uOdLqO3q3AOC5aSvaGGKrqctJpeYLkMlQbJqPIrATrpNFjmlKZMHg0K17YISrOHG5lpaJfseugDpYRWG0dW43SLiUqHNSQ6fYbzjzXV7EXlU51nB4DrctLdbXkkF/mBaYf9weld42s8Se/fkphC/kyfj8eawBUb9xX5bqjHad9STfeF3hJDhT5ouD9y2eEWypGqdEzTDXq+36ZpRB86FC/akNSl67V2n2BexmhelMw1D7bOVlqaOnkwSLutLQWSdDiPUTLT0M5qFflMZTqdeRpZyCqWE8mac04Srq7RwU2LtSJzAQC4Fife3Z6APteNPNoBAADw1p1wd5v//f+F5cLp64aywU2tvLe1rj//+c+5FwAAAG/X9X13CwAAAKxhdwsAAIDtYHcLAACA7WB3CwAAgO1gdwsAAIDtYHcLAACA7WB3CwAAgO1gdwsAAIDtOGZ3+zMAAABwqeqedUX83e1fAQAAgMtz5G8m1NEAAADAJWF3CwAAgO1gdwsAAIDtYHcLAACA7WB3CwAAgO1gdwsAAIDtYHcLAACA7WB3CwAAgO24ut3th9t3797ff7TWx/v3tQXgDUi3fHL7oQZm9nzgoQAAb92V7W4X7y572/Eqw1akf3Prdl/YaZ+3Y4+3TfHOdfwoTri7ZeMMANfiqna3wSvd3jhv7iWPjdLt056t1Fvc3a6cM7tbAMDCiXe36c1T1ReQvSKK/qLIb6fbFi5pw4ukHYRvN+sM3njA9dGrftqzVTkmt1UeIDeBj0vVbm9zYkqSQ7n5vHAPOe+MepN5eI/oFMuJh5MLb+u5kJyzZgcfRXCamifBLiru55ZDfhitFgBwSU66u00vhPom+Hh/ay+V9BKRl1Xpy2+WmtZHWLC9hSxWentDSSJw1ewCb9ey3x5ju90DGhvuDO+woO7k5LDnDBPe93IzSXSpTIt+uE0FJRKuw/stWFdssZ2lvZC3BmM4Os1h/RZdzqcVPtznziFU1ypFAAAX7ZS72/k94u80eX/oi8TfIC0qvTq6mycBrpNd4J1c6Ro2+XIfbhq9M7yj30qFHrb8lGxkrlHtz+a7TGatNNIXohPPq9NeFxbywYMxrPV6lZSillUs0eg6SqTbsVQAwOW52N1tTdYaOrqbJwGuU7/4rSEbKbknuuGm0TvDOxbD9FDyEztsOziVwjVtUatYVDEa6QvRsbLscuPONbKwkAxWY1hn61VWRi6kLJMTtUwTxQAAl+iUu9v0OmgvlT2/mdCz/M8629vG30qS6PobDLhyun0a7h27D9pFXn+DYLwXfKDkajWzKJ5yLNnLzvfWWFVrFRrd/ZsJnqX3czoKyiZhIW8NxrDMltq1I03l4fLLB+7DrQ7J7VS0V62fuZYGAFyyk+5u60sia++F9J4ZApJjhrfX8nW2PDb+AgOu3Lh9yvdFPe53zXQjlcN+D+W/UVXuiLHacGjtnKO3XnAbedX30e7W+Lra8B7RybqxiC5pMhcKbv+ipuZErWntnr/zVPtcusI52GqEiwAAXI4T724PsfrSsg5/1xT67jJBBoBLsrhnnW4+AQB4OSfc3eavOfbru9t6nNnwvumtoRws36iUl2VKaK/Nf/mXf8n/BHBZVna3q5teAACe6QK+uwUAAABeCLtbAAAAbAe7WwAAAGwHu1sAAABsB7tbAAAAbAe7WwAAAGwHu1sAAABsB7tbAAAAbMcxu9ufAQAAgEtV96wr4u9uawsAAAC4JEf+ZkJtAQAAAJeE3S0AAAC2g90tAAAAtoPdLQAAALaD3S0AAAC2g90tAAAAtoPdLQAAALaD3S0AAAC241y728e7dzcPn2rr7jHHUjPJHdp+FWkBZfbUaksEcH0+PdzsepTs6X4ae148q5iPt1Z/8KSnUH0gSvNVPfdEAeBszr+77ewN05/l2n4Vi/XZIftbnFndxRS79xGvfsMc7CRbopMUPdz46T93MdF4meFyftSHnugrrPh67ocTefMfALD0irtbDT33BfFM86PBIq+5ILxFT7gjrudldpJb+6KeF89dTDReYq98ruLQlbzCxXk998OJvPkPAFg68e423XNNfTDaIzLdhfaP6ubhP6SdcnxUe5jme/eupOV72Ie3Wzo9eu/u6kB/CMsKauZK9cWTwWJeBDgD3T2M1+TicpeLOg+w7pbr4+SGSEnx/eGFg6vdO6PeYRl9qT4mh6RET3HT7F5RCy7XvSwqx22dVqg08+dRnxxedU+3LmQ+d+nLXcEKM19WcOrhFDZicUI3/8//VVs1x0e1mfQUFqPbvPtXWINzdZXK3MwJi0FyXunYBtVlpOFlkLfCGedYikQ/pupJU3ryVKeYE9JguZVEyu2fifVZZiG1e6yN1bPJeT7jonzRC3i3hxYFakowBHhjTrq7TbdYvcutWW8za5WYh1bbdtOWZr57+wMjPx3qgZZr47w/BWvmp4e71BtV7zVUGAROZ7w2++UXXe4aG67V8dpv5Ywc9pxhwodebiaJ3bCsh9wbrTQamqXk1vN4l3LTEutwH5WCtTmcW1i0xy21N4Kie7rTnFNQ+EKSlO11a4emWIJnV+EUnugxbWo7PIWVea0Rr9DnSLGoukplam0fHAzyOUqwHKTRJdWLRzNGsVSklZR+12cZDoIpU2hXoTAhxYJUk6aqPbJGWc0iIUclM5F1WM80z9Cdb1Ipn3p7zV5yHgK8Pafc3eqt6vdbux31FhxvR7v1xXzvpmxVRi7KtWE9VoTVW/ogDAKno9e1XHsaNvmKnm6IduAdFtSLXw9bfr0bZK6R3i2LG8mUdS3mULlrsQzXFtHZbJ7Zh+n4PmRRdF5nr5W62jQ+we5uz5tmKnTU+grVskY8RR+tNaWZ5lU5eVqMKiOlhM/RG01YXWmZNms0aFyRHaVRj3c3D4/ezGXWBqtcSCvWeiNN6CnBlMNgPZ8mTIgSC5lXl+ADrNXX1TI0sxwp7ylqv4StpsozDTXnIcDbc5m72+m2HIM6sluUy9m6giKs3tIHYRA4nX4JW0Ou8B4W0w3RDrxjMUwPJT+xw/aSVClc0xa1VJqwvUmjtNWh1qGLWNytfZiO70OGonYwrbPX0g/KJ9jd7XmLmRodNaZYO1jhLJ6ij9bh0hznrdYX02mwz9EbTVhdaZmWHA1axOzw7rFsL6158/DQJz5gcKHBXGN5hotRdhhPOQyOPqswIUosZF5pygBr9XW1DM1cHq2yQu0mjZYTVZEhwNtzyt2t3IXp3lve7nqPLtpyMP+RZznqh+2PXhYl+hwt0X8zYU/1wmI9DTiHxSXsV+58uY+XrA+UXK1mFsVTjiV72fDlKFW1Vta/gfNMmT0d5JUuluG06O7fTNB5Sv9Q1A+8pLV6Q1bU7uk93VFFpaNWVphSpPL0x8PhFH201lyUl4PnPRtlXgumWFRdSZmUWsoEg8YVlZSak5fnndGMUUwrWrt3dwdPmTpq25pzoTAhzkxkXl2CD0hRaeYEzTRpxl5++tgtueW2cemfvUDwQAiGAG/PSXe35cZN0i/e1xvYQuV200eGtuvdW5Xc6SZthY3X1XJ6ew95QfXgGWARWRBwBsFd4Bd30zJqqBz2azr/5ZdyKY/VhkNr55zgVlBe1W9fESwqCrYqwQSeXDt9QT07WveiaLBOC/VGr9WD+7p9ZfGZ9/7cFa/Qa5gdJcJno9aUpkkLbkqunkI2z6slfA7NrKG5upLCu5fUMoNTSMkyNpxxjqWI9GqB5uApvfp8htmcIMUWZGHSHAfUlfnaNDPzGYNFhZ295nDG7XBnPeCNOPHu9mosnl92yFMBeOumjQgA4AqccHdb/93xGqTlpn/1LRvc1CpvNOv6n//5n9QC8GbU78ES9rYAcH347hYAAADbwe4WAAAA28HuFgAAANvB7hYAAADbwe4WAAAA28HuFgAAANvB7hYAAADbwe4WAAAA23HM7vZnAAAA4FLVPeuK+LvbvwIAAACX58jfTKijAQAAgEvC7hYAAADbwe4WAAAA28HuFgAAANvB7hYAAADbwe4WAAAA28HuFgAAANvB7hYAAADbca7d7Yfbd+/vP9bW7YccS80kd2j7ivl5Hi99FP5h9U8LuDxHXfAf79+f50Y/dqLwrCx47nvR1n+h9//xH8aTfyaHDzj0Yow/1mMvlue53B+xkZ+yNesL+tAf/UWfGd6A8+9uO734N3Mj7H6+7u4tljmHPktw9exH7fZeKK9lvFcPuaTXXc59/5JndYD1Ex+mPvjzOfsHecbHkp3bgT+MQ39sZ/+0RsP0r7yWAx2zyuec2clvQLwBr7i71dBmLubdJ7L/NIMngoW28dlgj+u4I8ZL9HnrfM4L8GW95FkdYP3Eh6kP/nzO/kHaMs81n53bgT+MQ39sZ/+0RsP0r7yWAx1zQzznzE5+A+INOPHuNl3gTb1a62PR/lG9v/83aaccH9Wu8Hyj3Ja0fMP48Hb/pPvh9rYO9DtDVlAz5+qhus4kz17a+2dpUQ2Vwb7mGphXIjM5C+5cKTYiXVztBz1eCX7p1Fjqfv/er8OeIFdPj8kV2bvlIDWHRA1pwUR6cnZa884bwmPOelN4WSsaluq387S19IReVooslmrqRCWrPUCCRCmS88OzsuD0iQVz+uceLTKHltM5H5srx8uWpDJ8vd7Q1wto2RzzisH5hCX8wwhOt4em1RirVsO6DJ15UbEP8JE5p7d1fUGwh6RwdKJePo3dcbUYqdTKrw1afhiy2hRZG+Zp0QTRmiqpX7LWZvBz6LHlWEtJ//TMtJYaHPPbIo1nh+uc1mcWS5EKQQHgMCfd3aaLtF6d1qzXv7VKzEOrbbsRSjPfEf1CT0ftQMu1cd6fgjXz4/1t6o2qh3rhYb7FLKUps0j5bliO98pBX4nF2qQijmJrxiui/8y13S4Fv/hys/ZL5iKhRP1CsljtHSfNTSnz1w/3tbPT3jw8nGdZc9CDU61pWKpfM2SqnqkF5qWOE0mdNo2bVtJyvMOCubF7Tqn+8f6+DfTQ/BGPhtWltJY3dFQ9tl7PeY6WHcdawV1lPLUlyqrq6aacGtLKnQWlu/UPZ9IqfrhNvX2Aj9R5rTUVkVYfJYVTc1qXlE/9c81Y7w8HhZN6qx7McwXrHzJXae16cS5mKM0hz3+WLeZvyxKQ9YTBYZE1qFN0w7y+vh6aLyvgSKfc3fYr3vjVGt0b2k7XusrJ441i2aqMXJRrw3qsCKuHWg0js+ssLayzLFbRleHL0SpnyKQijmJr5gsm07DJV5BcktKUC0yvGc9oUb9k1y5D0y/Vkc6nMw7Vc63Gs6s+/VBrbSmtvjR93M6lxhP1oNKE+KyGxvqcqZDxWi3Spa5xOqVTD2nWbh1ascTW67XlFiVnzNZ+E53XXMIiuVGXInO3niRalsXqFNrbozq86F0+MqftDua1NqmiFE7dy2VpJe3X+kJn8DmnQeGHoZnxsBRU87BVNqPRJQ/j2kdU0roU67O7vvw2rLb7elQO9hFr6y0T60Ql0rXlLdcCPNFl7m6ne2IMhpf+olzO1hUU8R0XaTWMDNJZWlhn6f2ps0Z9eDR6IJOKOIqt6ZeHNfxCGa6aRq4evZA8Va8ZySgJFmgVw8uwSF1m2TuO0MW1OXfULPr8Q2Y4TOpLc5majoOlxhP1oBorRmfljWJtzsKSTS4yli6iWKFTD2nWLh2pdA325NV6qaPW85wxe5gxEJawQTpfWpNvTHrPOFFhsamaRBeFTe/ykbLoteA0rxSOurWS9mv9zmq1hHDOPkgm9QTNjIcNGU0YXJFyzTxdW25ftuuzu758TW/BcD19xO716vqCpYQx4GlOubuVSzRdzLXZL3+9gBdtOZj/8KLeGn4PTX/8N8zREv3PWqbqIa+n08ksXntMLU1ZcZRYDvwoPM/Kgj4K26WXh180w/VnB/2Pf6W79XqFFJVmv6jsIP0eaz+OLsMPt7qM3q6GckOCtUtHUHOQFpGDU61pmNSXZh+3e6nxRD2oppVo3X5W++e0OjJPGzCd1zidGkpqmrVLh2ek7tJcrScdaRmlOWanI5mlPE5FWMJaqWF9PrKkpX/K+lp3Z8Ggu0dluE1SC04nmRZSs6KPQ/vtYPmR+2moPo+mSlREc4aDvFv6NTMeFq1/HGbScc9pgotTxvmQ1JJ58w9dPpZDfzNh1yKlnFtZX0/0pfQ84Dgn3d2WCzxJL9R6tVoovGHkYs6Xe1Vy5Z4pWmHjdbWc3y2tVuudq8d6Xv77JTVT5tUVt7Ccp6fKbqLVLIfBSlJosSgLyUzYLr2E69VRj+WyKxG5TvSSGSr4BaiXTy47XGI5UpWOabpR7c5dOqO1W+G5prLeNkhrrSxFUlsz5R2y1D6RDxhmV7oSmSq1+1QHzDmfQhzU6QYtN+XFy+7VgsfNXK+v1p9DWjbbeUZhCQvlRl+L6SU9Pyg2nkcb41FdTZuidfWe9Lekpnz9OKKF9ZA8kYXPkxKjhbmhVOlfGxR9GDWWImvD+gym9GumWRw2/uG1CbWSjpgzJbVELKUMsEZfWQ9Gi5RY/CkHs0bBVmUuABzoxLvbzdG7/DSWM8izBACAJ7wY0kaRVwjenhPubvO/em2KnVTZe9bjE0gfnM3RNripmR9M1vXv//7vKQQAeNtsz3rglpXdLd4mvrsFAADAdrC7BQAAwHawuwUAAMB2sLsFAADAdrC7BQAAwHawuwUAAMB2sLsFAADAdrC7BQAAwHYcs7v9GQAAALhUdc+6Iv7utrYAAACAS3LkbybUFgAAAHBJ2N0CAABgO9jdAgAAYDvY3QIAAGA72N0CAABgO9jdAgAAYDvY3QIAAGA72N0CAABgO861u328e3fz8Km27h5z7KV9erjR0umwHKdWnR3A0fw2fi3y+LBmYgs69JkSL//Q0QCAa3H+3e3pDLvbeavL/haXrW7Xigu5XMf76By38YEWN/hB9iz/gs4OAPAcW93dzvNZ5KkvQ+Cc9KK9lJ3Wxe5uj1nKnjEXdHYAgOc48e42vRub+uKwV0h9W1qr6u8Uyc9JntJz8uv2rsRLIUmS0tN7yicGLpFetdOusqqx1H1zU28WG9QT5BLvsVp0KCkHqTkkOu8qfWmFd3c+bU3bVcJIlTJlnrzew7rk6TSNx9oKUt8YrcFFfg/J/NH6ppJt5FzKIv1Tt2AvHJ01AODVnHR3m94O/qKobwBr5ZhH7O3zkLMk/9PD3fjC6On5jdLeNuWw1snvzNxhrfl9EwaBizHcEr4T1Xa7e1JMLnu/7lvmIqFE2+gcq73jpK3ZSUljyXPVPSW0wuND7kwhGVyaQ958mhZLodajk3owqmH/bDEd4/rooTsqtajVsodxAIDXd8rdrb0f9P3jr4L8fkhvD9NeIEbzm5qVlU5965hWznhPVCkOAhcjbZia8RJX+SKWu0BviPk2SzyjRf1eSH2qD6q0utaXGfaVsESj995QtNUsaV2LLar1SBtW2z2oUoKf6jjGhSWjUkOGNMfPCADw6l5vd1uVl0ju0/widdbkXmDxKpFy3jNXMmEQuBj9Gk/XvV+rPSzkLtAbwlPlvtCMkiC3go6OjP26lD7DvhJFyjI5cRjRamrtps/R9Yimh8HK5tK8aYq10WGuBKV52AcAADibU+5u5QWQnv+1acH0JrBIeyH0l4N1tbdE+c2EqMDiVSKHMtwHujoxcKH0qpWLOV3i/dKtv8Ujl73eEF4hRaXZr3w7SL852o/zRD5r+c0BMQxerrB27C7xeKdDcluK+jpTq08lp9lGH/qbCcsanqjVRFgyLKUZ0kypLRMAcAFOurvNr4AsvVDru6C9S/Lbo+qvBg+W7H7sBaZXyZDTeoYXVdbmBS7UeNHm69pvmma6C/SGGCr0QcOdkMvGN5AJbpFaJhfR+tbu2TtL9HX0lWi65s+ZGsuJfVZrhEsJarSQPIWUj27rqodzKYtI0dZMw/r8AIDXd+Ld7etZvHHsMHivATg/toMAgFM64e62fuvxGvL8+YuY/A5Nrba3/ed//uf8TwCvhN0tAOCUNvvdLQAAAN4gdrcAAADYDna3AAAA2A52twAAANgOdrcAAADYDna3AAAA2A52twAAANgOdrcAAADYjmN2tz8DAAAAl6ruWVfE393+FQAAALg8R/5mQh0NAAAAXBJ2twAAANgOdrcAAADYDna3AAAA2A52twAAANgOdrcAAADYDna3AAAA2A52twAAANiOk+5uP9y+u/1Q2xfi2CXZuHfv7z+25qWdFrAddofVe+1oR9znH+/fH3FfH/tAOaHTLCk99sxzfzBHO+7HA+Ctes3vbl/gJXaAl3gqLld6ga80XL+6gSh23xrX864/6C4fT+fgB8OzPwWd6RQf6bl+TAd/YsdaOZHTzjtUP9dHeYYPE8AZsLvdL6hgIR6AeGF6Q+y5Oc73rn+ug+7y8XQOfjA8+1PQmU7xkZ7rx3TwJ3aslQlOO+9Q/XxX/Mk/TABncNLdrT0myvMoPS9ub98PX0pZrKkPLY94oA3LgzyhPX3SI2+MGE37Pz2hl2iPSB/bH5oy4ThHz2gsKDMCLyBdfu2iGq86v6RzzC/d8KoubbmYU1J4bUvh4HL2zqh3WEZfqo/JISnRUybB6cS3YVNKLYcpK1Hn8xVESY0l50/utoVktZ4WnEKfKBg+L9AjelptWF1E1SabxwyVLW08D1+S6V19rEWC62Dg1Wsdn2AYMM5ro2pvGl9GeitaymjZP1YvpYIfjy9WZ/dPdBCcyHL8YtpoCIArcLbd7fDsKc8ci/oDQ+J9nAwrR+3g4/197fdIfbSmOi344dbKaGEvnWvXsJdJwdr0YX3III4Cx/MLcbhqtd0uu5WrenHd9nJGDnvOMGG+pVZIYjcs6z73RiuNhk6m05mWKjwW9RbB7NEZ6uJSsVbN4zpFK6p6LBw+LlBmsw7P6CnDZOUjjcZYrKV9vL9NIcnKB6U3lathr5wGT0El1b3sMIEbwu0gla0lLLRjKSLsH6rnqrvWZQm5qYmjIblcDMH4YdpgCICrcL7vbuV5MT2jyoHKHUNCeWrpc6sGutzj5auU5ZHW3R9lSZ9HJ+yFpopZHAWOZ9dUJxeXhk2+QuOr2niHBeXuGQ5bfr2DZK5R7c+0VlHWtZhD5a7FMmLT6UxLLc2uxMZhqg3bc4Y6kxazdo3rpGY6lb6+cLgG84HKHUNGnU0micb06k7Pw5fUG6bPo6ma0AzVe7KOEmO4lLMCtx+kKV1FX4oI+4fqOsrapSMFVUqIyhc1Wzqj8cO08xAA1+GSdrd+UEWxFDQpHj7GvHw1ZrVuiwZz64S90FQxi6PA8fQ6lCu/h0V8VRvvWAzTQ8lP7LDeUoMUrmmLWipNaHJilLZjqJtOZ1pqyqhBTx6HqTasssPoDIeZtJi1a1wzIn2icPiwwOGgiYIpVj/Sle7lkoZV9iX1humFNFUTmqF6T9ZRYhH+cPv+/kPZ0abS915KZ4rOKewfquuovsaoVBQbWNl2MYS5w7SFDAFwHS5md5ueM/1BM//mQU7w7vJMsn6p63842mLH/GaC12uZY4HKgr404CUsLr921aULsF+B9daYruo6UHK1mlkUTzmW7GXni3ysqrWytJXxerkts6eD+SZeKbWYPliqZlioNsdhqg6zhNYf5upMmmDtGk9RCU9/ON3WFw/XYFm4n9j8yxyWoOed29GYFKtjjvrNBJ3EV9dIdc/VUWIRTrO0wamMd4ZLEXuXOgyzdu1Is/Sc8vGE9RPrkAIlJxiv00ZDAFyF19zd5gdGUo/Tk6Yq2TrMs5NlhaQ/erxOnz3JpYLZx5HBOoPnmoVkZcBL0MuvXp/1uF7CScuooXLYr+X8F4b6Za/XqB5aO+f4LSA3gfOq76MtabCoKNiq9BmDmfq4PCZaqlROq2k1dJhqw/acoS5Ol2btXack+vpWho8LbNMl87B4qnmMxhaFU0JfkukFezmLaNvndl5d6/RRSueth21Mmlqrz0sZBf1aXUtbuye1nCT3a+JoSl0JtpAdhkMAXIGT7m43Y/lst2MedcCTcecAAE7vhLvb+m+81y+dTPpioW5wUzO/oa3rP//zP1MIwAE++p/0AgBwKnx3CwAAgO1gdwsAAIDtYHcLAACA7WB3CwAAgO1gdwsAAIDtYHcLAACA7WB3CwAAgO1gdwsAAIDtOGZ3+zMAAABwqeqedUX83W1tAQAAAJfkyN9MqC0AAADgkrC7BQAAwHawuwUAAMB2sLsFAADAdrC7BQAAwHawuwUAAMB2sLsFAADAdrC7BQAAwHacdHf7ePfu7rG2L8TrLslmv3n4VA+OZUVqldS6tA8Yb8tRl/Snh5vn3weHOHai8KwseO67zdbPHf7CXvLHeMk/H7320zqTu/849IZ42TNLb6q1eVMf1zhO4DW/uw1fIS/ukh5Au8/4oM9jkWSHPBm2wn6Y7gy3xnHGG+qgi3bV5dycL3lWB1g/8WHqgz+fy/ggT/6xPcGpPpHjfj6v64ify3PObDnd3ukt4Qo+RVwbdrfntPuMD/g85pOxyBk+RJyDXgDnuTmOMV6Dz1vn5dycL3lWB1g/8WHqgz+fy/ggL+miPdUnctzP51Uds8rnnNl4GRxSyXIu5sLBZpx0d2tXebms0+V+d1f+cKRd+BZr6rXvEQ+0YXmQJ7RbId05Y8Ro2v/XE3qJdqf52H7vyYRDxcCiUGmvjPeZelRDfWxTC3tknslZbPdKcS3S5dN+lOOPeroUUvfNjV9pPUEujx6Ta653y0FqDoka0oKJ9OTstOadl7zHnPWm8LJWNCzVb+dpa+kJvawUWSzV1IlK1t1d8CEVUiTnh2dlwekTC+b0zz1aZA4tp3M+NleOly1JZfh6vaGvF9CyOeYVg/NJvbt/xmXQYu0qPI9pFV6wT+I1g1BQpwW91PSJ2Pg6cOW8lNcpYxbnGE2dTGvUueKZKh9Z0lbWGHxUy7GWkvvko8j3jw+YV6kxjXZDsWWoVJYKKSV1a6GgghnWBbyIs+1u210oF7tF/YrWm6CNk2HlqB18enio/R6R11gLPt5ZGS3spXPtGvYyKVib47BZL6Spi/GlGc7khtHeq/P3uXpDhUFcIbkA9McfXQp+eeVm7ZfMRUKJ+qVisdo7TpqbUuZvjw+1s9PePDycZ1lz0INTrWlYql8zZKqeqQXmpY4TSZ02jZtW0nK8w4K5sXtOqV4fU2No/ohHw+pSWssbOqoeW6/nPEfLjmOt4FzGgm1qz03BmtpX0RtLOmEfOK5CB1tPbg6h/FlGa10UryM0c9CG5dbu7JSwLOwzmHDqaI25lI9bI8X9HddCqW5pDmlyhbdge/HJwLqgMJjq5abU0O5uGFOu/GgpEvPaRVChGNOAF3C+727bleyXsUbTgcodQ0K+MYzfAzXQ5R4vX+n95N39Tkz6PDrhVGgk3T6Djm9RnWlRv5tHD92mdFhwXlMYxBWaL4ksuhTkqpZmSq2XkF4VwwWaG35Rpj6Vu8uMfjEOdD6dcaieazWeXfXph1prS2n1penjdi41nqgHlSbEZzU01udMhYzXapEudY3TKZ16SLN269CKJbZery23KDljtvab+bx0SdbOI2U1nqCJg2HCljWuIh2p1FNjnpTGqqmOtesKxuqincG4XI86L2Zasg6Kp7YM1YM+bFWqZ2QlOq7NVrO6nG6J4wn09fRxQzBapdSQMaIMkhNZW4qnLNY1VagWacDzXdLudrrko1gK1tsjvAG9fDVmtW6/y02fRyecCo2k22fQ8S2qM/X+1Fmj8ejxoJFJXRjEFeo/c2vsuRT8qtGmpOpVIRklwQKtoo5eSF1m2TuO0MW1OXfULPr8Q2Y4TOpLc5majoOlxhP1oBorRmfljWJtzsKSTS4yli6iWKFTD2nWLh2pdA325NV6qaPW85wxe5gxognWziP7apKWsFppmLBljasYjwY2oH2W0Qw60pe1Ws9K1LgW86jzYqYlDysIpx4ymjC4xpKjE26zhadmiWPMVy/5HowWJDXCOarUZ1J3mDaUntaVSIUqTAOe42J2t/l6b9f3/JsHOcG7yy1l/VK3/DlH6muxY34zwevtvt08VVYu4605BX1tsqgo0UjVdFD+iHM8l8JiPgrXTC8AvyzCS0GuBL0oomttSEgH6fdY+3GeyGfNN9HjnS6jt6uh3JBg7dIR1BykReTgVGsaJvWl2cftXmo8UQ+qaSVat5/V/jmtjszTBkznNU6nhpKaZu3S4RmpuzRX60lHWkZpjtnpSGYpjxqlS7J2SfVq3q+JA5kwNcM1p4I+TfqULMGXVXLTP/ug+V5I7VpDo4N+BsNyPSrSkpa5OiieOgUlWj7PYZiR0s5GSrXcL+N8SGr1avVGSQM80/L6enqt0pTgcpWSGK4vuPKjpbS+TGqatXvH1wW8lNfc3ZYbzP8Vznqakj1c/z07WVZI+i3kdfrsSS4VzD6OjNYZ6sPzL/0PM2Wy8hZO24oW7qmy19j3eZSMcVUWkZlwzewHLj/LfDXU4+lSkAtBr4mhgl9ieoHkssM1lCNV6QiuPFW7c5fOaO1WeK6prLcN0lorS5HU1kx5hyy1T+QDhtmVrkSmSu0+1QFzzqcQB3W6QctNefGye7XggTLX66v1J42WzXaeUertUWvLguqYXquFhuLGU42OHxI1K3dMgWRaq9axti7Vk5yfwcp5KV9B722hFNgzdVJjOpdZHDY+XZtQKumIOdF4bl1bHSCr1EUGq/S6478CN8GIaCktlA9ldhNVWCwLeBkn3d2+OXbrnvomXUxhh/MzCAAux7jDweG7uTO8Uk5u7znwFsMpnHB3W/8N7c2wUy63cT0+gfy52iT1YZFa+algXX/+859zLwBcFna3I/kD+j327gyvgr+zZv0tBrwsvrsFAADAdrC7BQAAwHawuwUAAMB2sLsFAADAdrC7BQAAwHawuwUAAMB2sLsFAADAdrC7BQAAwHYcs7v9GQAAALhUdc+6Iv7u9q8AAADA5TnyNxPqaAAAAOCSsLsFAADAdrC7BQAAwHawuwUAAMB2sLsFAADAdrC7BQAAwHawuwUAAMB2sLsFAADAdpx0d/vh9t3th9peZ1nv7z/W1nq+pwU+3r9f7wxZuVovtQ5YJoBm59247shh1+F1T85mv7Sn2AUuCcBbcQHf3Z7hpWCb3/E5u5iTxzAugF2Gbvc9MV3RZ3bwTTsu9AXu9TOf+ROme4GTO53zLO61L8uDXMUiATzTm9zdzo83i1zuiwlvhN4Je+6K135DH3zTjgt9gXv9zGf+hOnO8CA73nkW99qX5UGuYpEAnumku1t7otaniLWq/ohNz5imBlfza24f27tbxBJqMz+6blt/Licz9WrLp5sXAF6JXdb9IhwvUr8fwivabxwZl6rd3vYbRw6jO8lDjd8SXrO34mq6shz0w3K8NsyXUc9DEiVtKmhpMqAkesvLDjW63u39e9YfDenSxPPJSYnlh7g48Nq9V8x1Rja6hKNleGlPqlotGZYGeUJwJnLumvd/fIk5w/padR/b1y4TDhXFPCp/XPXx3itl2jP09RWWObzmyqQANuEsu9v0HKsPko/39/m5kx459QnkvTvyJZgeT7U7P9FSvzUkNFXueVmbZhAGgTMarnu/YrXdLtPVK9o7LNjLGTnsOcOE7UbrWm9Kr/dUnyiqtqhX7kjpNeEwTWkTSOLCULAfpPy+2jIw9U1ziWGx/ankoWD9wRAhaw4n9KBl1t42zTDCu0NhcR8UL8OibenxXDJsyN7x2eRCLfjh1uqMSxtq17CXScHaHIc10aiUGaQa7fFJZIV9kng2ANtylt1tfvAMDyWL1GeOPorW801Pa1lJe1B5vRap7RLV4FigC4PAGdk12MnFqGGTL+nVK9o7LFjviUwPW35KNjLXoKRZ0u0HabauqVor16WorycJh1lD5QRNHI0F7Sjlfbh9f//Bm3lgr2/GQUVdrYRrpEtdw8h5iApPrrS7GmzdVtBXq3ohEdQRfUZrBMtYRFWJa8KBn42Ur4ZPq3f7WZo+j044FTLhqHECpT0+VAu3jPUaALbjLLvbyg5Ne0jpky14FBnJL0elqVnywKp5+ujqUQ1O0xRhEDgjvcT7dS9hsXpFe8dimB5KfmKHcqOJumlMuWnIvd+1YbVxUcW00HmYBpsoViwmscO0907J1nx/f99Prdc30coqS2snH2VFMRmidM198jS+RrVUybVIG6GDIyt1XJ8xXMYyOs8VBS2267OR8tWY1brlNGUenXAqZMJR8bkn2uNDtXDLWK8BYDvOsbu1p4k8dsqDxR9tKTQ+iqJ8GSEDerc1lqHS9iEtuDwqvADwSvymyO12kabrVa7p/AfF4zU83k21Q6uZRfGUY8ledr4najUvJzu6oFppSfg+tdYWKsNkzekgn58mjpYrTXPWXF1uOao1lmMSi2lmbu9ZfzRErJ5cTUzV+xiLm+F4+hDUWp2uzxguY4iGcy0SvLvOa/3LzyZ3ttgxv5ng9fo6RTRqnEBpj7VraVlhT1ivAWA7zvLdbXqcNP2xkp5dSXrG+/NuZ74+DIsWsRHLZ1hpt4Q6ohxqTiGZwCvRS7xcpXJnNKtXdDlMf0+nXNtjteHQ2us3mtI7JU3Yk6JqSVAxjTM5fW1YzUlKvyYuacFy2Jppdh3Wy0a1wpPfvf5wSKdrtnZL8EXobrbUGor0xHi9K3WaPqM1omW0tfekpibrsIM/Gy00FM6lgtnHkdE61TwqRaLMscfafi59hVPIAwA256S725eUHl4v9zTSJ6tZebgCAADgypxwd5v/9fi5UqH2L99lA1raz5Gq5KJlg5tabW/7xz/+sTQAAABwja7mu1sAAABgL3a3AAAA2A52twAAANgOdrcAAADYDna3AAAA2A52twAAANgOdrcAAADYDna3AAAA2I5jdrc/AwAAAJeq7llXxN/d1hYAAABwSY78zYTaAgAAAC4Ju1sAAABsB7tbAAAAbAe7WwAAAGwHu1sAAABsB7tbAAAAbAe7WwAAAGwHu1sAAABsx0l3t4937+4ea/s4VuHm4VM9eC4rVqul1jNXBrxhR96YL3o/P9+FLeelfXq4eaHTCz8oC/IQBXChLvy72+NfP/ZkH5+9i1I8mnFp7Jp0u6/76fI+s4NvzHGhx9/PL+SVlnOSiU66+jN/UOe/nl/7DgJwWm9ldzs/yyxynjcbcBi92vdc+a/9bj74xhwXevJd0j6vtJyTTHTS1Z/5gzr/9fzadxCA0zrp7taeifX5Ya2qPSSXEXvY9OenP0tT6+ZmSCzRKgjlGdOjq8op0aNMZwRen1/3yyt2z+Vt3S3Xx6Vqd3c5MSXJ4e5bqfH7w2v2VlxNV5aDfliO14b5Mup5SKKkZZ7bu/Ky7lq8fRSm55bMA5ezOIkaaRNI+URq9p7F6ciKF4MT762zeUUtuFzosqgcy6pLU5cvVaOlF9KTKwTz52Ab5pO3ThF0eihXWE438t42nZ7PuHLtGfr6jGWC3TMCuH5n2d3aP9sj5NPDQxyxx01/zHhveibVR1R6HuVoOLY/yKw3NzXm0UEYBF7LcGX75fuky9s7LNjLGTnsOcOE+VZSrTel19uwTxRVW9Qr97P0mnCYprQJJHFdny5VmNeQosvJdK6V5XiBFJwnGGi9x4ee20N+Oq3mKCW3nse7lJvWVIf7qBSsTS+/VrTHLbU35qLDOsvShfauzz8tZL6M5s5h4lpjnE6lqWtPL5Wy43Tt8ZlTdLn89RkBbMFZdrf5kTM8jsJIewjKY8lb/jiax1qWyiNadtFWMgiDwGvR6/jYy9s7LNjvHaOHLX++lQYlzZLuHqXZuqZqrVyXor6eJBxmDZUTNHFJpylJOom168g+gWkZ+5ej1ZMe9GGqLF7XWiJd7tKJBm3Wzpdv+jAd34csiurCS7zX0uX7BDa+p050yPr8pVFn9nQ1d5Z5u1x4nE74ck1bxmr20OND+0pNy1ivAWALzrK7rcpTzZ9VQ8QfRf4Q09b0OJKxmtWM2ZYxP8nCIPBa+nWcrm2/op90eXvHYpgeSn5ih+1WGj3e3Tw8lh1tGvLg92hYbXGHZtNC52EabKJYYT2tYE/SSaxdR/YJTMvYv5wxowqDIvWbnKJFmyiW6Rozq+SZfZiO70OGonbQKvV4r6XLHyYwunShQ9bnH0alJYSXUSKdWqwZpxPDctvI1eyhx4fqSlvGeg0AW3CO3a09R+SBk0JzRB826UHoj6X2bEvRmhiNbYPtYPrjr+VRYTF/bgKvTq72frmb/Ze3D5RcrWYWxVOOJXvZ+Qap1bycbF2CaqUl4fyn3WsLlWGy5nSQz08TR96TxpWmTmLtqd8TNHNlOdaQ6PzbBoO0//cCuZ1yZTW7T0fWaElpVJq+jvZROt7afaFe1A+8pLV6Q1ZUg8HShQ4ZE3T+3LBUKS6jkqAz/bNnhdezsllaT1/Ferb2WLsuOkWlmRPWawDYgrN8d5seJE15oMyR8hgrgbv+LO0x0x6v0VhNbHk1VA7nZ5lFWiZwCeyKlUsyX+f1+JDLuxymv/tTLvSx2nBo7ZwT3kpKb5s0YU+KqiVBxTTO5PS1YTUnKf2auODnerN7d2t63SmUAzqLtaVEzklKTCcY9RmCOZIabCWDIp5cO336nh0vdCjaRw0fS2/0Wj0YL93V7twVzt8bfWrTpunCzmBqnW7kFeQc5oky7bG2V+szTqFgRgDX76S724tizzJ9jtlh/HwEAADA9Trh7jb/i/GlSAtK/65eNripVfa21vXf//3fqQUAAIDr93a+uwUAAMD2sbsFAADAdrC7BQAAwHawuwUAAMB2sLsFAADAdrC7BQAAwHawuwUAAMB2sLsFAADAdhyzu/0ZAAAAuFR1z7oi/u72rwAAAMDlOfI3E+poAAAA4JKwuwUAAMB2sLsFAADAdrC7BQAAwHawuwUAAMB2sLsFAADAdrC7BQAAwHawuwUAAMB2nHR3++H23e2H2r4KH+/fvytLTq339x9LGMDAbu1jbo8jh60LC9rNe+337oU8OtNj8Loe4QCQveXvbpdvxsWjfAPvSFwVuyDd7mvvtbcdB29Tx4UePGzdixfc7SQf9MlX/QzD2s52mZ3/ej7/jADOid1tPYheORbh+Yez0StwvhoHr/1u3rM8Ny704GHrXrzgbif5oE++6mcY1na2y+z81/P5ZwRwTifd3dqDsj4/rFW1J+cyYg+b/lD1B2xq3d6+18QkPZnGWH5W3ZaaNqcn9CfYcowvoKT4pM5iPABxLnoJ5gu6X3t+seaYXN55gFynPi5Vq/dOSpJDuZW88HTxW6Ua85q9FVfTleWgH5bjtWG+jHoekihpBxa0pNqU9PYBCZ+1z7Fn/aOpugf6bMECfdr+WTZ9EouVEsF4s/O8pLP3xmXmFS/WlrrbY1Wn8rRgguUn5cl6elUeLyteDjbLNY7L8kUlawv2GcsEu2cEcP3OsrtNT776CPl4fx9H7HHTHzPem55JtZmeR6U5DK6j8tNqePjV9of71TESk6gKg8BpjBdpfDnXW0pjHjXeYUG5vvWw5wwT5ttQtd6UXm+uPlFUbVGv3DrSa8JhmtImkMSFwwpOc9fngBgWW05+CEXrV2nq2vPx/tZyJeCFUrA2vZTMMxiG9dRp/O7zEsOM8zJy1JulvzeSlDtlDNMH6xxJPX/UT+M1NkqFa08vpcsahQvOUWnumRHAFpxld5sfOcPjKIz0h6M/lrzlj6M6tutTeDUbZvrIlTFafJi/C4PAaZTLtpBbQ8MmX5HT9d4OvGO4vMfDll9vC5lrUNIs6faDNFvXVK2V61LU15OEw6yhcoImjg4oaCklWCrvKGS81gHrF32SZgj0dYUL1KDReWs8TNWgpwZKf7GjTLhizRzOvmdrddODPkzVk2tVTDReJxqEa1zNHnp8qI3r6S1jvQaALTjL7rYqTzV9BkrEH0X+ENPWnsdSFEwxszpGi6cMP2jCIHAa/YJM94VfeMN1Wo0XtGW0A+9YDNNDyU/ssN2Gow+37+8/lB1tGnLvt0NYLbrLpoXOwzTYRLHigIKWooPTiPocCNiodvL71y8WkywCfV3hAjWYF1Bn8HiY2oPFynmlcB3iiw/LhCvWTCkg2UNGEwaF9bePOUrViQbhGlez4wWncT29ZazXALAF59jd2nNEHjgpNEf0YZMehP5Yas+2FC0J0m8H5U/mZHhK8O5aIBojxc14VFisFwVOTC/BdMHWay9d2/06DP50VwdK7uKCXhRPOZbsZbVek6t5Ob2F5mqlJeF8l60tVIbJmtNBPj9NHB1WMAeD54CzJJ+zlrSs3etXKbn27P7NBF1E6degHKS5fNic2oI7z0tXbL07ymi/J2jmcPbWLh0pKNHplzoGliwF8rBofOubRWtcz9Yea9clpag0c8J6DQBbcJbvbtODpCkPlDlSHmMlcNuflD1m5OEZF/RnlQzro4IpW6gc9mdn19YPnMN4Bearc74PWkYNlcN+cee/2RNez3po7ZwT3BOjlNA60oQ9KaqWBBXTOJPT14bVnKT0a+LS3oK2iF6lmauFJ79n/SNPrp0e0DObF9gT82Ef9f79Ybvb1GiCZXl3KrijjAlWrGtL7dZhbS3R+IKjpegM46fStFE1FBSZ16jLGq0t2GecQvGyAVy5k+5un2/1mXkKi2fm8HAEAADANTjh7jb/i/Gz9N1tPT6lvOS0vy0b3NRqe9svv/wy/xMAAACX7sK/uwUAAACegN0tAAAAtoPdLQAAALaD3S0AAAC2g90tAAAAtoPdLQAAALaD3S0AAAC2g90tAAAAtuOY3e3PAAAAwKWqe9YV8Xe3tQUAAABckiN/M6G2AAAAgEvC7hYAAADbwe4WAAAA28HuFgAAANvB7hYAAADbwe4WAAAA28HuFgAAANvB7hYAAADbcem7208PN+/e3T2m5uNdawG4fnZHv/YNnR4q5ubhUw2cRHqK8egCgPO57N3t8q1wAa9D4FTqVqs48YbrEpzpdl7fW55w1zmUPuXu1j7EN3CpAMDTXPTudn5w22uCRzk2Sq/3t7BpefXd7Qk/ZHa3APCKTrq7TQ/eu7ub5XdR6VlftCd+fvrftW+uWjR6blsmz3Jsk17w44bIeqoaS903N35r9QTZRPVYLTqUlIPUHBI1pAUrX4wPSEsPbnU1T2ODWvW5M0UOPkM9lcWDRE5lsS4fnTrkDEpe737KiqrFpMGyMk9rcwykShuzPGM/DlYBAG/WqXe37bGd3wz9pVEfxNYssfwY92BpWjB45ls3j3FsUr8fyh3RrnNtt8vf7ye9eSRzkVCifvNYrPaOk+amlPnb40PtjPhYa83TqWAaX07UmcpIxZopxaXZK0mmF9XEkcyb2n6Qx8jsvfjOFakhLOkyp8xuCT53pRXKT2GIBJ8dAKA6+Xe37cHbnszDc7wl6GNbg8Fjuz/VgY2xa7uTi1zDZnnH6M3T7p3xPvGMFvV7K/Wp3F1mDO6+Qsf4dD1dp27WpmmrqeGiB2sZacpEZZFdjmqmtUumBkeLVfe2Ly1p46WOlhwHNsOkemBtX5bq2U05wXFRqvTE0wPA28buFrgQ/X6xhmxZeljIHaM3j6fqfSIZJUFuLR29kLrMsjctbqg2tsapm3Calhh2SlD74ykbzbR26Q/LZ4tVS7m2tKSNlzpaMlrHYlI9sPa+ZQ1SWv0phDPF0wPA23au3a0166PcW94vD/rUrIOi53Z/NwBboxe83CZ5f1PbdvCQWos7pvV6BbmPNCEdpN8d7cd5Ip81/wn4450uo7ercA7Ns7aXb4JpPDHqlFXrCfhEKdrD88eS2iVTgyMvNrbLGJknD5c6WnIc2AyT6oG1a3p01mL+KaQyUief8cr0APC2nXp328kTOD+kM3ni14jp74Tgwe2vBmBrxus93xT1WO6kEkmd9UaR5lihDxpumVzW7zGTI1XpmKYb9Py0TfYF9kxrD/WrcJqWOHemSO2V5jDRvE7NtHbLrHk+sNJiQ+GkF2/hQ1YkZNKVZeV40/pdX4CsPIi1InMBAHizzvXd7W769FfLuBXkGQ4AAIBV59jd5m8Wdum72HrcWIn8xUTZ0aavLUrLuv73f/83tQAAAABx0t0tAAAAcFbsbgEAALAd7G4BAACwHexuAQAAsB3sbgEAALAd7G4BAACwHexuAQAAsB3sbgEAALAdx+xufwYAAAAuVd2zroi/u/0rAAAAcHmO/M2EOhoAAAC4JOxuAQAAsB3sbgEAALAd7G4BAACwHexuAQAAsB3sbgEAALAd7G4BAACwHexuAQAAsB3b391+vH//7t3th9p6f/+xhAE834fbV76nbAH57q7txBak0V0OXr49PHh2AMC12PruNu1o5TXHOwqXq27Oiou9Tsdb6uDt4ekt7vWDXN7u9oI+UAC4Whvf3c6vCos89Q0InIVerZe7ybnY3e0xSzl4DLtbALgiJ93dpgf17e17/ybKAlV9PaY35fv3OaP9gWIhO9Aeqw/94e0qB6k5JMZvCotJceBi6OU6XOVnv3E8pAUT6cnZac31HpfxUU21rJ+Ob2/nc5jO2yzGWkru89Q0Y4sO+dHy9i6wdlvAE6dlpfQ9P455GZY0fXReWYYCAJ7o1LtbeXekx3t7YltPbua3Qn99tCe6ZC4SSrSNzjF/LbSpetB7RRgEXt94DbdrfGif5caRMn/9cF87O+3Nw8N5ljXVXD9FWihVzM0hra2896b+Wxvbe3TWIX9aitTQMS4Y1AeHy0ox6a79krm2jLlmvCIAwFOc/Ltbf1Cnh7nIPfJUl6YMtFYLSkaL9hdF7lOLbhEGgdend0i/6l/jxikzrtwmOp/OOFTPtRrPrqb6Q81WsmR1OeYLb9qkPq62V5eiNXRMt3vQyrLaKqTp1aOK4XpXVgQAeJLz7m6nx/a+t4I89YeMkmCBVlFHd9LvwiDw+vplbw25V/xucHK966XvqdY6/sYpUlfbiYlxhC6uzbmjppL6w4hWUks3lriItUkPX4rWiObYM2hlWW2EDu6pUcVwvSsrAgA8yRl3t+kJ3x/xH+/vU2vfWyFHpdnfEHaQfs+tH6ch8q6of5wavSks5qOAy6GXa7qe5c7o1+w5bpwPt7qM3q6GckOCtUtHUFPN9aWmLzy1+kz1vHPpnnnYbyZMS/FEn2wQDLJMGbNcVor1VfnH4xPtXkZuB2cBADjOGXe3Jj3jq9Kx961QDnRINbxjshypwkKZRYZRwKUYr9Z8Pdfjfg+c58aZphvV7tylM1q7FZ5rqqm+pmt+tBDPbQuoA56wlFY3bfT7GDUNsoAnTstK6bW2NIcVzcvYs952DAB4spPubi+AvmuMHYYvMwCvZ3GbAgDwHCfc3eYvIF6ZLSN/FZLfnKlV97Z///d/n/4B4AKwuwUAvKCtf3cLAACAt4TdLQAAALaD3S0AAAC2g90tAAAAtoPdLQAAALaD3S0AAAC2g90tAAAAtoPdLQAAALbjmN3tzwAAAMClqnvWFfF3t7UFAAAAXJIjfzOhtgAAAIBLwu4WAAAA28HuFgAAANvB7hYAAADbwe4WAAAA28HuFgAAANvB7hYAAADbwe4WAAAA2/EWd7ePd+/uHmv7iT493NSx1rp5+NSDSerQ9quwk3tXFpaW0pYIXBO5u5Rd3E+4otMN8Gr34Qtb+UB28LOXsSnYHk/avgbpyWZ4pAE4xFZ3t097Dx7MXxlOpzrRtAdbzC/vNVy++v4udv/gogvxMj3vlhjPc2+tIeF6PqPiZdcbVdOP53k/l7Nb+3DOfBpX9qkBbxi72ycJnrEaetn305MF09vn8IoLwpPoRbvnAn7lK+0Jnncnjue5t9aQcD2fUfGy6w2qaejaPpy1H/3zLq8nO/N0AI522t2tPQuq/EgYHg3tID1mb27KH5KlSB+jz+GdCcYnykE/zMf5SX5XYnZsvX2oZ/rKAlKwjrWaaUQqXd39h7RzzmJVJXJzd5fT+skXbXpdq4+LFjpVz0P7gMqyphguU7o62lU4/jAXP2u56vIA+SH7uFRNrjU59GtICveQ886od1hGX6qPySEp0VMKG1yL+pJ7q3bKBDk3PoduMVmutvNWWiwpkzl7kZbWD9JC2iPJIn1MX9PeBJ0oB/1wOlc7tt4+VDKDE5APoXbXsTps/6MqZcszc1qukRXqic3Lm4fOOaO+nDrAl+fzJHKy+UOuval8qeutuegoWpKXL6Fhuv1nAeAVnXJ3a88Cf5o9pNvfnz+pszwR0iNCHkoSrU+MgxJqs5eVuYdhSTS1BT1hQdJ8KmuVmIfW231Ga8i6ZJFDuTau96dgyywLjar3WVQvjIs3Xg/9hxn9rDU2/OS9w4JyrelhzxkmzHfoCknshmU95N5opdHQrHWkQfWSb2NSrAzSirl/OofBMFkuXHN6h47r07mhu5yUZ1lnrZ4W4pXbnH2SwxJas5XVuYdhJpz608NdTyhSiZrn1fpYnWCtbeVzM8V6MFyurtArzMubhw7zlQ9Zpe6obqsy0Hhrp1F1FRYq48OiTmM7LmadLhgC4HKccnebbv/Fv9a2J4I8GeKmPEb2JlhL5ag8hcZhxvrKUW/sJmleyVplAi2+WJ8qydOyVB65KNeHtVgVVZ+zTK+Bi6c/VPlJRj9rvUyGn7x3WFB/8nrY8lOykblGtT+br6KyrsUcKnctliHKKmyOu0dp5i5rlUFpBb48rVWGLAyT6dhe0DLUtLTSP4RbUSkeN2XCfQmppVJU1zsMM339vRGyQXLGPlcfG3TnUSona385UrlHV9gm7nN10dAy4dp5yEn4MnQyNcTLSBszX1FhUWH9iyWVSFe6LNhz5iEALscpd7fV+BCwI/0zpOFRo08df4zsTfCWG2I6zOQlDI3dJM0rWatMoMXj9YldyyoW5Ur2vNCo+pxleg1cvP5DtYb8eKOf9XjtyE/eOxbD9FDyEzuMXtMpXNMWtVSa0OTEKG3H0Me7m4fHsv+wrLsHv1T7VTudZ6+VRsg5FMNkOrYX3LEcoSfVBuuEUkWaMuG+BEntxpgMM2UJ2gjZoFZhmKuPDbqXUxXavzyqdFibuM/VhUOz1OMfspOT8NHRGpMxvn5FhUUnuqRwxjm4dhYAXtcJd7d227dbXh8n5WngDwPp0zR/jByU0MP1T1iHp5AOM9ZXjlK8Ze35zYTaaUN9bBmqxZdtOSh/7jssK1frh8Gfhw1zjAuNquvQrp8sLp5eHX6lHfCz9oGSq9XMonjKsWQvO187Y1WtlaWdhNfLbZk9Hcx34iin+2rlZrCe0h7XpbWsvVzwYjIdOxRcLlEEJ1Xbw/Zf+qQpEx6S4AXLva/rHYaZvv48sGbFv5kgE5RmH6sTLNtyED1MguUOK7R2yZ6XNw9d+ZCbNHUN+iqixGSM5zORlXhfWNQdeDHrdHvOAsDrOuV3t+VRU8jTZPFwkUPt8QfG3oRy0MioJKXrMGPJ/cgHSsKkFct/U6QkWqjMpMXniZq6qmHRphc2va6W69nzQufqi+kTS1pEcLHGqyNfG37dNC2jhsphv47yX/MpP/Gx2nBo7ZzTh5ngMvGqdtlrrSJYVBRsVVYmaOE0sKdYRytZC+ZDa/eZrL1jyalLq0vBYIlipVNnNnIoTZlwb4IvNfFRSU6XYUbX7wMloemdz3xULfqlsCkdukJra+Wi9U5Dp9mWeoJOEKe24mV6XXYq0trJXFSESwqCMl04BMCFOOXuNmaPB54Fp2IPXP1w+ayBF2D3le6TAACX7YS72/qvtcKC/d+tawgvJ3/q6QuFsqNNH3Xb2/7rv/5r/ieAp1r8OyMA4NKd/7tbAAAA4FTY3QIAAGA72N0CAABgO9jdAgAAYDvY3QIAAGA72N0CAABgO9jdAgAAYDvY3QIAAGA7jtnd/gwAAABcqrpnXRF/d/tXAAAA4PIc+ZsJdTQAAABwSdjdAgAAYDvY3QIAAGA72N0CAABgO9jdAgAAYDvY3QIAAGA72N0CAABgO9jdAgAAYDve4u72w+272w+1/UQf79/XsdZ6f/+xB5PUoe3r5af5DPmjyFVSq31YWPeMC/Ol2VI28xN7+sfqZy9jrZnkDm1fmDMtzT8iIZ/WhXmRJ9ouJ58AwNNsdXcbPnyfL3qG6VQnmvbc9jyqD3mSL3LscAsfzLU55CdVjalXdyG/6IKDYvrxPOFTPbcTLu3MF8jLnskpPpeh5gk/eADHYHf7JMEzTENbecTtOY8DTnP+/C2yhY/mujzhghxTT755eWkvuuCgmIYu+MM54dLOfIE84dI9wMtWK4aap5gAwDOcdndrj8AqPwmHJ2I7SI+F9+/Ln+enSB/TnhV7E4xPlIN+mI/zk+e2xOzYevtQz/SVBaRgHWs104hUurr9N2nnnMWqSuT97W1O6ydftOl1rT4uWuhcPVLXmaXZc3v/JD0qoVpHTrlG5pX0mYTFdi0U/gmlj69eJv7z1s+5xXZfP//6fy9+UnOBZvlDXVnBPN9gUT+vpf3I20H650vf73KcAnmqI+73NK6p3XWsDvu3RQkf1Upa9nCXy/C6EF2hnti8vGlolNSMPXa0sow27pCPupLPJo+W4l7PgnVkr9T7VNDroVxhOZ3yVO/b/4FGJxWV2lupJi5WuDbM06IJgiUBeBmn3N3a88Dv6Pt0H9uN3SLWWW7tdLPrA8Oj9dY/KKE2e1mZexiWRFNb0BMWJM2nslaJeWi93We0hqxLFjmUa+N6fwq2zLLQsHqkFzZDPZmkNGUSrd75aoduPWgrsViftAuDEP0HmX4m02ftn78F8+00RILrR0ebuYAaUg9YwfzDDOpbqNbsA1I5qVz7fZLDEmrTJ5DJdVjSc6SyBT2hsLQ2yIuF9VfaVr40LeYJ4XJ1hb3CvLxo6DDh9FOU3tReLKMe9bKLWJ1LZxVjWIp7x5PXWHu1dKuxsoqBV0rZLb1HU3Ba44ph0GGVhprhMGmlhHkCACdzyt1tvo3HG7k9ENo/JTQ25bmwN8FaKkflsTIOM9ZXjnpjN0nzStbyh9XcHa9qXpbKIxfl+rAWq8LqkV7D9Nl1kh6VSRaLqJMErzMTrUQn7cIgRP8J9B9UaZdg/UH0D374ySS5Z/jZjEdTgcE4MFpBOJ+I6rc6Xk/m0SmfkGAtVaLePQ4z1lWOeiNig3qBYa4+NujOU6mcrLn5SOUeXWGfuM/VrQ01KyeiU0/L6GPa9LIMXdE4sNGMaaLS0Rq71zj32jjVz3N3gawuQrOtXaJ9XevV5lL7KnnCUDMcloJqHgbgVE65u63Ko6s+hcpzot/+Rm52ve8tr6bsTfCWG2I6zOQlDI3dJM0rWatMoMXj9YldyyoW5Ur2vNCweqTXMH3QMHOLyiTeb8EW9SnD4Uon7cIgRP8J6Gfag5Ud19tp+DE0YzBK8QKDMTVaQTjfbKxvg6zZSpRAa2tBn3BvgreEBnWY6ZP3RsQG9QLDXH1s0L2cqtDc5VGhw/rEfa4uGlpZV/RT1BHjaK3eppdl6IriaTVjmqh06BzGDqM1VtKrxZpxOpHG1Q4fp9nWLlHrllhQLSq1r5InDDXDYUNGEwYBvLQT7m7tLpbbXW99e6j57S19mhY+uNYTerj+WZf3Gh1m+qMqxVvWnt9MqJ021MfOT7BlWw76n9T6snK1fvjhPirnc4wLDatHpJ5PJ0EvvcgsTV+wJ2pmOehH8XkWFuuDEOmfkH58LWifs3/K5fO3Lsmbr5/xKCigxli0gnA+t1Y/jZKrQfo0zSc8KKGHoytOhxnrKkcp3pLC30yQCWqzj9X6i7YclM9E++Pl6gqtXbLn5QVDLSQDe2eztsyheh8oFbTYOLAZp1tMVDpqwzJb4jgoC3rTP3ta8BENfOaUsjyl0i5RCdqgoFpUarXSNJNmxsPytLVpB9EdCuBETvndbbqNG7mdF3e3HGrP+ODZmVAOGhmVpHQdZiy5H/lASZi0YvmvYJREC5WZtPg8UVNXNSza9MKm19VyPXte6Fw91vPSX2XwNXe+4B720xxjy9XU42AlFlosyiI+EyL9I9JPrwf1h9Y+yTmWIvo52/AklYsKKEmNVxCvoVvr1FrDAnWtnrQ3oRw0Ldhmt3wdZmT9MlASmtYpl3ofa40+vbZ94mTOzVphUzp0hdbWylXrDYc28zno1OvLaGFZhq5oGljV8blvMVEZ2hq71xj21tpJq6vTqT5efk66fGu3MUPqvJKo1EolX6CsR1a4NqzPYEq/ZgI4mVPubmN66+N1nOEBu5iCn/qb1bY8AACcyQl3t/VfWIUF+6anhnB2Z/gpWOUySZkltdre9p/+6Z/yP/E22N6Wf60BAJzX+b+7BQAAAE6F3S0AAAC2g90tAAAAtoPdLQAAALaD3S0AAAC2g90tAAAAtoPdLQAAALaD3S0AAAC245jd7c8AAADApap71hXxd7e1BQAAAFySI38zobYAAACAS8LuFgAAANvB7hYAAADbwe4WAAAA28HuFgAAANvB7hYAAADbwe4WAAAA28HuFgAAANtxKbvbx7t3d4+1/RQ27t3NwydrfXq4qS0Ab4nd+7tu/T3dT5OeM0c9qg70oovt0nPS8IAE8EZc93e39szW5/VpXgzAedQtSLH7Sj71Hutoi1vyRbz2yQ7ndLGf/A7PWvM1njCAN++ad7fBY9feQzyIcaV0F7Vnl3ixWw52txfoWT8UdrcArtBJd7f2UG2PRX9Epift3d3N4guqRWrRn6nhmPCpK3WA65Iu83ZDjFe39VQ55rdIGbC4e0pbbpqUJIfxF8NSNL6HJKH1L9Ylx0EJ72zT90hfT7DK4GSbNsxSajOf/l3LqGvw7qB8IlNItJL5Ur1wBuNp85nn3hbOBXI7XI0vVmpqZPdP0SxH9eNd59a6/KMoEfloSmBHNQC4GK+yu23PRQ96aur2WE0Mx/Qhyrp56OI6+QWvt8bQbhe9xoZbYbg/dAMih+PgWdg/rOIhFRoicv+GN2BKbh2PdylXIl4pXKVOpPpcliCDWm7QHZZPweWQwRBdm6Gv0IKt6SQ4Tjytxlpec+oNh6i1UTU2kPCnh4eUOURkHX2eeQgAXKLX+e62PWk9obX6MzXpqeEYHyyG8cA1sSu6k0tbwyZf38OWQ2+F+EYzeij5Siea+0uvlNR0U3p0GjVPqZG+ah3eE8aTzYdNSbZIHaWpPerdUXnvHfvdEA1nsAw112iTGS+gdXuC1mxDfEw4RO0dJVK/8SI10OWeXiWZhgDARWJ3C1wIvd5lO6JXfzNsOfRWiG80o4eS36WBNWEsPkp9dXsTrSsOmnlKjfQZdXhPGNZj0XbQky0hWHqPendU3nvHfjdEwxnicaJNZryAjuoJWrMN8THhELV31Mx6TUrwpYko6EMA4CKdendbH4DpCVkfkfqktXZ9bvZWem56rGaGY8JHce8Frs3iMm9Xstw86SD/efB48fvAlRvNLIpPd4lUlLnd450OT+1oXcM0KiW3jt2/maDTlKAsTTO8gLWmShL17rB8VHGgo1ZnmD8KNc4xTSyrGWrKmB1D1N5Rzvrb+JZqiVI///6JlAmHAMAlOunuNj8Bs/w3IcqzMH4+y5O6D/KHZzwmeL5KGeDK6GVe74N6bD1Ny6ihcrjvRjN6aO3gNumT3NxEG5fe7WuIYm0puwq0Pp9RCkarrIm5y8/VllmSLVRHpc42qEe9e3d5qThqU6b8cAbTaphdJfY+CsOaGpmHLOweJfqajJxSjUw/plQi6gaAy3Pa3e2pLZ7a+mIAgCdJezf2bABw/U64u63/hn8yeZL0tULZ0aY3U9vb/vGPf8z/BIA9+pedfB8JANtw3d/dAgAAAIrdLQAAALaD3S0AAAC2g90tAAAAtoPdLQAAALaD3S0AAAC2g90tAAAAtoPdLQAAALbjmN3tzwAAAMClqnvWFfF3t38FAAAALs+Rv5lQRwMAAACXhN0tAAAAtoPdLQAAALaD3S0AAAC2g90tAAAAtoPdLQAAALaD3S0AAAC2g90tAAAAtuMCd7cfbt+9v/9YD45kNVqR1Lz9kKPAJr3ELRP5eP/+ou4dW090nk87/VOf1Moinyk9xsyuyuGJnWY1L+HYn8Opf34ANuHqdreHvMmWOXbM4xAXb3GdHnKpF7szD69jhuQTbiSeV3ocvfcEz3VSJ7O25jOf2JOupH2esNyr//kBOLsN7m6Dp5+FXu6pDJyGXdt64R6+l3juLSOG5BNuJJ5Xehy99wTPdVIns3aGZz6xvR/0UzxhuVf/8wNwdifd3dpDqT2G/JGUnlS3t+/zn7PpszJlNDWsoT64KQFPaaXCh58FX+6xDJyE3C+Jv9NX7pnjbhmJTPfJIjnfS7ctJtk7Shjv7Wv1deWQLNNPp7DBvs7a2Vo2LP1zOTp1R4+Uypez86Q8beWcWjgXyO2wVF1k1mv2yNrsajnKVzaenMdzoT2rSd1VMG3Q6+VLZDHdQPraGtfOVFKjhUjCdPo5f3/dGtPEFPKE8WMEsEWvsrttT5cUlCdYzbXm9PQZhnuvHFhGaVqsTSriKHBBFhepX93Wak2/Z1Lw6beMh3PHdFNMyfMce0pIhY/397lzCJX7VIsMeocNqmfdxgwNGZ0ya/24rMxfUlpO79BxFgxLtKDnrpXymtOywiEqHBVmmiEelrZgbngt67xf1pp7h0g797VlKJ05/pxrCZ3BhQnDvKt1WzEL5qYmDjXaZQlgw17nu9v2pOpRa/SgJli7i4ernCGTijgKXJDFReqX+vKiT1nH3TJDt/GOakju92dp1449JepdKWdSI11dvqaIOtGH2/f3H7yZ5+hrGEfrmq09l91/UnvOaajrBcJSWrMvpWeGQ1Q4ajgBMcTD0r1hqeGJFVNvCXS9xlqBNHlTcsLlWAWJ+Zl2kuAZw7xrdVUOjhOkIzPPCGCTLnl3m3prdM9wJZOKOApcEL22jV+z0UV/3C2znGMy9OsN5vPtK1FYVrzNKKJYZV23H8qONk963z+HvoZxtC7I2nPZ/Se195ykrhcIS2nNvpSeGQ5R4ai15Q3xsPRijpSzvseT3nDGtWWkjlaz54TLsV6JBeuQBM8Y5l2rO60snMASzZQLYGtOvbutj5H0oKlPGnkOpSdNffyMqaUpTyfPlOEl3I/qn7eFzzQL+ijgMunF7ffBEI/uhKfcMimj3x/BH9FOyZ7bbqHdJaxXhpS8tJZedf6T76WULiekk9U1jKN1zdaey+4/qTyPR+c/ufYSkrpWymvKmB1DVDhqOAFx0InlRv/+Oyw296ZiUm36DZORd6Rxpbm2nBa0Mb3f+XjJHeZdrSvRvFxNTAcyKJgYwLacdHdbnjlJ/ksf5YmSHmqNP7I8/v59f7x5bgrWB1KrWQ77DEYSFg8vC+lUwIUKrmezcs8cd8toteCu0GS9lYZ7aFeJ8BSCYK0RLCF1tXAa2FNkDTpa0lO7T+ra9LtOqlZMeky0EvosC0uFNXskHLIwj9IzHKRyyeqJ9cbu04t6g5hON2gdci2Gy1lkTnWS+fSHeVfqzsvVRJnXhNMC2JTT7m4j9hDyp9ZpLKewY55nuF5nuGcAANiME+5u678nj/qbuh6fQJrbJmn7gdTMe1vr+q//+q8UAq4Ku1sAAA53/u9uAQAAgFNhdwsAAIDtYHcLAACA7WB3CwAAgO1gdwsAAIDtYHcLAACA7WB3CwAAgO1gdwsAAIDtOGZ3+zMAAABwqeqedUWwuwUAAACuFLtbAAAAbAe7WwAAAGwHu1sAAABsB7tbAAAAbAe7WwAAAGwHu1sAAABsB7tbAAAAbAe7WwAAAGzF3/72/wPZN3K0XegL9AAAAABJRU5ErkJggg=="
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![Set%20Methods.png](attachment:Set%20Methods.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#1-Add()-adds an element to the set.\n",
    "fruits = {\"apple\", \"banana\", \"cherry\"}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'apple', 'banana', 'cherry'}"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fruits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "fruits.add(5) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{5, 'apple', 'banana', 'cherry'}"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fruits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#2-clear()-removes all elements in a set.\n",
    "fruits.clear()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "set()"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fruits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "#3-copy()-copies the set.\n",
    "fruits = {\"apple\", \"banana\", \"cherry\"}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = fruits.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'apple', 'banana', 'cherry'}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "#4-difference()-returns a set that contains the difference between two sets.\n",
    "#returned set contains items that exist only in the first set, and not in both sets.\n",
    "x = {\"apple\", \"banana\", \"cherry\"}\n",
    "y = {\"google\", \"microsoft\", \"apple\"}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "z = x.difference(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'banana', 'cherry'}"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "z"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "#5-difference_update()-removes the items that exist in both sets.\n",
    "x.difference_update(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'banana', 'cherry'}"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "#6-discard()-removes the specified item from the set.\n",
    "#it will not raise an error if specified item does not exist\n",
    "fruits.discard(\"banana\") "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'apple', 'cherry'}"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fruits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "fruits.discard(\"banana\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'apple', 'cherry'}"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fruits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "#7-intersection()-returns a set that contains the similarity between two or more sets.\n",
    "x = {\"apple\", \"banana\", \"cherry\"}\n",
    "y = {\"google\", \"microsoft\", \"apple\"}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "z = x.intersection(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'apple'}"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "z"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "#8-intersection_update()-removes the items that is not present in both sets\n",
    "x.intersection_update(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'apple'}"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "#9-isdisjoint()-returns True if none of the items are present in both sets, otherwise it returns False.\n",
    "x = {\"apple\", \"banana\", \"cherry\"}\n",
    "y = {\"google\", \"microsoft\", \"facebook\"}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "z = x.isdisjoint(y) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "z"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "#10-issubset()-returns True if all items in the set exists in the specified set, otherwise it retuns False.\n",
    "\n",
    "x = {\"a\", \"b\", \"c\"}\n",
    "y = {\"f\", \"e\", \"d\", \"c\", \"b\", \"a\"}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "z = x.issubset(y) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "z"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "#11-issuperset()-returns True if all items in the specified set exists in the original set, otherwise it retuns False.\n",
    "x = {\"f\", \"e\", \"d\", \"c\", \"b\", \"a\"}\n",
    "y = {\"a\", \"b\", \"c\"}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "z = x.issuperset(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "z"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'banana'"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#12-pop()-removes a random item from the set\n",
    "fruits = {\"apple\", \"banana\", \"cherry\"}\n",
    "fruits.pop() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "'banana'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32m~\\AppData\\Local\\Temp/ipykernel_4588/198021992.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;31m#13-remove()removes the specified element from the set.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;31m#it will raise an error if the specified item does not exist\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mfruits\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mremove\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"banana\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m: 'banana'"
     ]
    }
   ],
   "source": [
    "#13-remove()removes the specified element from the set.\n",
    "#it will raise an error if the specified item does not exist\n",
    "fruits.remove(\"banana\") "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'apple', 'cherry'}"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fruits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "fruits.remove(\"apple\") "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'cherry'}"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fruits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "#14-symmetric_difference()-returns a set that contains all items from both set, but not the items that are present in both sets.\n",
    "x = {\"apple\", \"banana\", \"cherry\"}\n",
    "y = {\"google\", \"microsoft\", \"apple\"}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "z = x.symmetric_difference(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'banana', 'cherry', 'google', 'microsoft'}"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "z"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "#15-symmetric_difference_update() method updates the original set by removing items that are present in both sets\n",
    "x = {\"apple\", \"banana\", \"cherry\"}\n",
    "y = {\"google\", \"microsoft\", \"apple\"}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "x.symmetric_difference_update(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'banana', 'cherry', 'google', 'microsoft'}"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "#16-union()-returns a set that contains all items from the original set, and all items from the specified sets.\n",
    "x = {\"apple\", \"banana\", \"cherry\"}\n",
    "y = {\"google\", \"microsoft\", \"apple\"}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "z = x.union(y) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'apple', 'banana', 'cherry', 'google', 'microsoft'}"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "z"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "#17-update()-updates the current set, by adding items from another set.\n",
    "#If an item is present in both sets, only one appearance of this item will be present in the updated set.\n",
    "x.update(y) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'apple', 'banana', 'cherry', 'google', 'microsoft'}"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Yuvraj Sutar \n",
    "* yuvrajsutar009@gmail.com"
   ]
  }
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