rwet notes 2018-02-23

notes-2018-02-23.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# notes for 2018-02-23\n",
    "\n",
    "    // javascript\n",
    "    for (let i = 0; i < 100; i++) { console.log(i); ellipse(random(width),\n",
    "      random(height), 100,\n",
    "         100);\n",
    "    }\n",
    "    \n",
    "    for item in list:\n",
    "        print()\n",
    "        print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "cheeses = [\"cheddar\", \"camembert\", \"brie\", \"parmesan\", \"gorgonzola\", \"goat\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cheddar\n",
      "camembert\n",
      "brie\n",
      "parmesan\n",
      "gorgonzola\n",
      "goat\n"
     ]
    }
   ],
   "source": [
    "print(\"\\n\".join(cheeses))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import random"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CAMEMBERT\n",
      "CHEDDAR\n",
      "GORGONZOLA\n",
      "PARMESAN\n"
     ]
    }
   ],
   "source": [
    "for item in random.sample(cheeses, 4):\n",
    "    yell_cheese = item.upper()\n",
    "    print(yell_cheese)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "💩\n",
      "1\n",
      "💩\n",
      "2\n",
      "💩\n",
      "3\n",
      "💩\n",
      "4\n",
      "💩\n",
      "5\n",
      "💩\n",
      "6\n",
      "💩\n",
      "7\n",
      "💩\n",
      "8\n",
      "💩\n",
      "9\n",
      "💩\n",
      "10\n",
      "💩\n",
      "11\n",
      "💩\n",
      "12\n",
      "💩\n",
      "13\n",
      "💩\n",
      "14\n",
      "💩\n",
      "15\n",
      "💩\n",
      "16\n",
      "💩\n",
      "17\n",
      "💩\n",
      "18\n",
      "💩\n",
      "19\n",
      "💩\n"
     ]
    }
   ],
   "source": [
    "for i in range(20):\n",
    "    print(i)\n",
    "    print(\"💩\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "50\n",
      "55\n",
      "60\n",
      "65\n",
      "70\n",
      "75\n",
      "80\n",
      "85\n",
      "90\n",
      "95\n"
     ]
    }
   ],
   "source": [
    "for i in range(50, 100, 5):\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "    // javascript\n",
    "    for (let x = 0; x < width; x += 50) {\n",
    "    }\n",
    "    \n",
    "    for i in range(0, width, 50):\n",
    "        # something here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## write a computer-generated acrostic\n",
    "\n",
    "    seed phrase (phrase to spell out)\n",
    "    source text (draw the lines of poetry)\n",
    "    \n",
    "    ROBERT FROST"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "words = open(\"frost.txt\").read().split()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "r_words = [item for item in words if item.startswith(\"r\")]\n",
    "o_words = [item for item in words if item.startswith(\"o\")]\n",
    "b_words = [item for item in words if item.startswith(\"b\")]\n",
    "e_words = [item for item in words if item.startswith(\"e\")]\n",
    "t_words = [item for item in words if item.startswith(\"t\")]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['one', 'one', 'other,', 'on', 'one']"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "o_words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Roads\n",
      "One\n",
      "By,\n",
      "Equally\n",
      "Roads\n",
      "Trodden\n"
     ]
    }
   ],
   "source": [
    "import random\n",
    "print(random.choice(r_words).capitalize())\n",
    "print(random.choice(o_words).capitalize())\n",
    "print(random.choice(b_words).capitalize())\n",
    "print(random.choice(e_words).capitalize())\n",
    "print(random.choice(r_words).capitalize())\n",
    "print(random.choice(t_words).capitalize())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "roads\n",
      "on\n",
      "be\n",
      "equally\n",
      "roads\n",
      "the\n"
     ]
    }
   ],
   "source": [
    "for item in \"robert\":\n",
    "    print(random.choice([word for word in words if word.startswith(item)]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "database??\n",
    "\n",
    "\"r\" -> [\"robert\", \"road\"]\n",
    "\"o\" -> [\"other\", \"of\"],\n",
    "...\n",
    "\n",
    "hey database, give me all of the words that start with \"r\", \"o\", \"b\",... \n",
    "\n",
    "DICTIONARY!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "planet_dist = {\"Mercury\": 0.387, \"Venus\": 0.723, \"Earth\": 1.0, \"Mars\": 1.523}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Earth': 1.0, 'Mars': 1.523, 'Mercury': 0.387, 'Venus': 0.723}"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "planet_dist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(planet_dist)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.723"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "planet_dist[\"Venus\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "0.723",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-47-6ba718764fb3>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mplanet_dist\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0.723\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m: 0.723"
     ]
    }
   ],
   "source": [
    "planet_dist[0.723]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"Mars\" in planet_dist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"Nibiru\" in planet_dist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"Nibiru\" not in planet_dist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "planet_dist[\"Jupiter\"] = 5.2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Earth': 1.0, 'Jupiter': 5.2, 'Mars': 1.523, 'Mercury': 0.387, 'Venus': 0.723}"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "planet_dist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "planet_dist[\"Jupiter\"] = 5.3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Earth': 1.0, 'Jupiter': 5.3, 'Mars': 1.523, 'Mercury': 0.387, 'Venus': 0.723}"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "planet_dist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "planet_dist[\"Jupiter\"] += 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Earth': 1.0, 'Jupiter': 7.3, 'Mars': 1.523, 'Mercury': 0.387, 'Venus': 0.723}"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "planet_dist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "number_words = {0: \"zero\", 1: \"one\", 2: \"two\", 3: \"three\"}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'two'"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "number_words[2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "planet_moons = {\n",
    "    \"Mercury\": [],\n",
    "    \"Venus\": [],\n",
    "    \"Earth\": [\"Moon\"],\n",
    "    \"Mars\": [\"Phobos\", \"Deimos\"],\n",
    "    \"Jupiter\": [\"Io\", \"Europa\", \"Ganymede\", \"Callisto\"]\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(planet_moons[\"Earth\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(planet_moons[\"Earth\"][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "planet_moons[\"Earth\"].append(\"Allison\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Earth': ['Moon', 'Allison'],\n",
       " 'Jupiter': ['Io', 'Europa', 'Ganymede', 'Callisto'],\n",
       " 'Mars': ['Phobos', 'Deimos'],\n",
       " 'Mercury': [],\n",
       " 'Venus': []}"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "planet_moons"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "what we want to end up with:\n",
    "\n",
    "    {'a': [\"as\", \"above\"],\n",
    "     'b': [\"both\", \"bent\"],\n",
    "     'c': [\"could\", \"could\", \"claim\"],\n",
    "     ...}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "initials = {}\n",
    "\n",
    "# look at the first letter of each word\n",
    "# check to see if there's already an entry in initials\n",
    "# if the first letter is not already a key: add it with an empty list\n",
    "# if it is, then add the word to the (list) value\n",
    "\n",
    "for item in words:\n",
    "    first_let = item[0].lower()\n",
    "    if first_let not in initials:\n",
    "        initials[first_let] = []\n",
    "    initials[first_let].append(item)\n",
    "    #print(item, first_let, initials)\n",
    "    #print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'a': ['a',\n",
       "  'And',\n",
       "  'And',\n",
       "  'And',\n",
       "  'as',\n",
       "  'as',\n",
       "  'as',\n",
       "  'as',\n",
       "  'And',\n",
       "  'and',\n",
       "  'as',\n",
       "  'about',\n",
       "  'And',\n",
       "  'another',\n",
       "  'a',\n",
       "  'ages',\n",
       "  'and',\n",
       "  'ages',\n",
       "  'a',\n",
       "  'and',\n",
       "  'And',\n",
       "  'all'],\n",
       " 'b': ['both',\n",
       "  'be',\n",
       "  'bent',\n",
       "  'better',\n",
       "  'Because',\n",
       "  'both',\n",
       "  'black.',\n",
       "  'back.',\n",
       "  'be',\n",
       "  'by,'],\n",
       " 'c': ['could', 'could', 'claim,', 'come'],\n",
       " 'd': ['diverged', 'down', 'day!', 'doubted', 'diverged', 'difference.'],\n",
       " 'e': ['equally', 'ever'],\n",
       " 'f': ['far', 'fair,', 'for', 'first', 'for'],\n",
       " 'g': ['grassy'],\n",
       " 'h': ['having', 'Had', 'had', 'how', 'hence:', 'has'],\n",
       " 'i': ['in',\n",
       "  'I',\n",
       "  'I',\n",
       "  'I',\n",
       "  'it',\n",
       "  'in',\n",
       "  'it',\n",
       "  'In',\n",
       "  'I',\n",
       "  'I',\n",
       "  'if',\n",
       "  'I',\n",
       "  'I',\n",
       "  'in',\n",
       "  'I---',\n",
       "  'I'],\n",
       " 'j': ['just'],\n",
       " 'k': ['kept', 'knowing'],\n",
       " 'l': ['long', 'looked', 'lay', 'leaves', 'leads', 'less'],\n",
       " 'm': ['morning', 'made'],\n",
       " 'n': ['not', 'no'],\n",
       " 'o': ['one', 'one', 'other,', 'Oh,', 'on', 'one'],\n",
       " 'p': ['perhaps', 'passing'],\n",
       " 'r': ['roads', 'really', 'roads'],\n",
       " 's': ['sorry',\n",
       "  'stood',\n",
       "  'same,',\n",
       "  'step',\n",
       "  'should',\n",
       "  'shall',\n",
       "  'sigh',\n",
       "  'Somewhere'],\n",
       " 't': ['Two',\n",
       "  'travel',\n",
       "  'traveler,',\n",
       "  'To',\n",
       "  'the',\n",
       "  'Then',\n",
       "  'took',\n",
       "  'the',\n",
       "  'the',\n",
       "  'Though',\n",
       "  'that',\n",
       "  'the',\n",
       "  'there',\n",
       "  'them',\n",
       "  'the',\n",
       "  'that',\n",
       "  'trodden',\n",
       "  'the',\n",
       "  'to',\n",
       "  'telling',\n",
       "  'this',\n",
       "  'Two',\n",
       "  'took',\n",
       "  'the',\n",
       "  'travelled',\n",
       "  'that',\n",
       "  'the'],\n",
       " 'u': ['undergrowth;'],\n",
       " 'w': ['wood,',\n",
       "  'where',\n",
       "  'was',\n",
       "  'wanted',\n",
       "  'wear;',\n",
       "  'worn',\n",
       "  'way',\n",
       "  'way,',\n",
       "  'with',\n",
       "  'wood,'],\n",
       " 'y': ['yellow', 'Yet']}"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "initials"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [],
   "source": [
    "seed_phrase = \"academics\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "A\n",
      "Could\n",
      "As\n",
      "Difference.\n",
      "Ever\n",
      "Morning\n",
      "It\n",
      "Come\n",
      "Stood\n"
     ]
    }
   ],
   "source": [
    "acrostic = [random.choice(initials[item]).capitalize() for item in seed_phrase]\n",
    "print(\"\\n\".join(acrostic))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### using json!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "animals = open(\"common.json\").read()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'{\\n  \"animals\":\\n    [\\n      \"aardvark\",\\n      \"alligator\",\\n      \"alpaca\",\\n      \"antelope\",\\n      \"ape\",\\n      \"armadillo\",\\n      \"baboon\",\\n      \"badger\",\\n      \"bat\",\\n      \"bear\",\\n      \"beaver\",\\n      \"bison\",\\n      \"boar\",\\n      \"buffalo\",\\n      \"bull\",\\n      \"camel\",\\n      \"canary\",\\n      \"capybara\",\\n      \"cat\",\\n      \"chameleon\",\\n      \"cheetah\",\\n      \"chimpanzee\",\\n      \"chinchilla\",\\n      \"chipmunk\",\\n      \"cougar\",\\n      \"cow\",\\n      \"coyote\",\\n      \"crocodile\",\\n      \"crow\",\\n      \"deer\",\\n      \"dingo\",\\n      \"dog\",\\n      \"donkey\",\\n      \"dromedary\",\\n      \"elephant\",\\n      \"elk\",\\n      \"ewe\",\\n      \"ferret\",\\n      \"finch\",\\n      \"fish\",\\n      \"fox\",\\n      \"frog\",\\n      \"gazelle\",\\n      \"gila monster\",\\n      \"giraffe\",\\n      \"gnu\",\\n      \"goat\",\\n      \"gopher\",\\n      \"gorilla\",\\n      \"grizzly bear\",\\n      \"ground hog\",\\n      \"guinea pig\",\\n      \"hamster\",\\n      \"hedgehog\",\\n      \"hippopotamus\",\\n      \"hog\",\\n      \"horse\",\\n      \"hyena\",\\n      \"ibex\",\\n      \"iguana\",\\n      \"impala\",\\n      \"jackal\",\\n      \"jaguar\",\\n      \"kangaroo\",\\n      \"koala\",\\n      \"lamb\",\\n      \"lemur\",\\n      \"leopard\",\\n      \"lion\",\\n      \"lizard\",\\n      \"llama\",\\n      \"lynx\",\\n      \"mandrill\",\\n      \"marmoset\",\\n      \"mink\",\\n      \"mole\",\\n      \"mongoose\",\\n      \"monkey\",\\n      \"moose\",\\n      \"mountain goat\",\\n      \"mouse\",\\n      \"mule\",\\n      \"muskrat\",\\n      \"mustang\",\\n      \"mynah bird\",\\n      \"newt\",\\n      \"ocelot\",\\n      \"opossum\",\\n      \"orangutan\",\\n      \"oryx\",\\n      \"otter\",\\n      \"ox\",\\n      \"panda\",\\n      \"panther\",\\n      \"parakeet\",\\n      \"parrot\",\\n      \"pig\",\\n      \"platypus\",\\n      \"polar bear\",\\n      \"porcupine\",\\n      \"porpoise\",\\n      \"prairie dog\",\\n      \"puma\",\\n      \"rabbit\",\\n      \"raccoon\",\\n      \"ram\",\\n      \"rat\",\\n      \"reindeer\",\\n      \"reptile\",\\n      \"rhinoceros\",\\n      \"salamander\",\\n      \"seal\",\\n      \"sheep\",\\n      \"shrew\",\\n      \"silver fox\",\\n      \"skunk\",\\n      \"sloth\",\\n      \"snake\",\\n      \"squirrel\",\\n      \"tapir\",\\n      \"tiger\",\\n      \"toad\",\\n      \"turtle\",\\n      \"walrus\",\\n      \"warthog\",\\n      \"weasel\",\\n      \"whale\",\\n      \"wildcat\",\\n      \"wolf\",\\n      \"wolverine\",\\n      \"wombat\",\\n      \"woodchuck\",\\n      \"yak\",\\n      \"zebra\"\\n    ]\\n}\\n'"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "animals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "animals_data = json.loads(open(\"common.json\").read())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['aardvark',\n",
       " 'alligator',\n",
       " 'alpaca',\n",
       " 'antelope',\n",
       " 'ape',\n",
       " 'armadillo',\n",
       " 'baboon',\n",
       " 'badger',\n",
       " 'bat',\n",
       " 'bear',\n",
       " 'beaver',\n",
       " 'bison',\n",
       " 'boar',\n",
       " 'buffalo',\n",
       " 'bull',\n",
       " 'camel',\n",
       " 'canary',\n",
       " 'capybara',\n",
       " 'cat',\n",
       " 'chameleon',\n",
       " 'cheetah',\n",
       " 'chimpanzee',\n",
       " 'chinchilla',\n",
       " 'chipmunk',\n",
       " 'cougar',\n",
       " 'cow',\n",
       " 'coyote',\n",
       " 'crocodile',\n",
       " 'crow',\n",
       " 'deer',\n",
       " 'dingo',\n",
       " 'dog',\n",
       " 'donkey',\n",
       " 'dromedary',\n",
       " 'elephant',\n",
       " 'elk',\n",
       " 'ewe',\n",
       " 'ferret',\n",
       " 'finch',\n",
       " 'fish',\n",
       " 'fox',\n",
       " 'frog',\n",
       " 'gazelle',\n",
       " 'gila monster',\n",
       " 'giraffe',\n",
       " 'gnu',\n",
       " 'goat',\n",
       " 'gopher',\n",
       " 'gorilla',\n",
       " 'grizzly bear',\n",
       " 'ground hog',\n",
       " 'guinea pig',\n",
       " 'hamster',\n",
       " 'hedgehog',\n",
       " 'hippopotamus',\n",
       " 'hog',\n",
       " 'horse',\n",
       " 'hyena',\n",
       " 'ibex',\n",
       " 'iguana',\n",
       " 'impala',\n",
       " 'jackal',\n",
       " 'jaguar',\n",
       " 'kangaroo',\n",
       " 'koala',\n",
       " 'lamb',\n",
       " 'lemur',\n",
       " 'leopard',\n",
       " 'lion',\n",
       " 'lizard',\n",
       " 'llama',\n",
       " 'lynx',\n",
       " 'mandrill',\n",
       " 'marmoset',\n",
       " 'mink',\n",
       " 'mole',\n",
       " 'mongoose',\n",
       " 'monkey',\n",
       " 'moose',\n",
       " 'mountain goat',\n",
       " 'mouse',\n",
       " 'mule',\n",
       " 'muskrat',\n",
       " 'mustang',\n",
       " 'mynah bird',\n",
       " 'newt',\n",
       " 'ocelot',\n",
       " 'opossum',\n",
       " 'orangutan',\n",
       " 'oryx',\n",
       " 'otter',\n",
       " 'ox',\n",
       " 'panda',\n",
       " 'panther',\n",
       " 'parakeet',\n",
       " 'parrot',\n",
       " 'pig',\n",
       " 'platypus',\n",
       " 'polar bear',\n",
       " 'porcupine',\n",
       " 'porpoise',\n",
       " 'prairie dog',\n",
       " 'puma',\n",
       " 'rabbit',\n",
       " 'raccoon',\n",
       " 'ram',\n",
       " 'rat',\n",
       " 'reindeer',\n",
       " 'reptile',\n",
       " 'rhinoceros',\n",
       " 'salamander',\n",
       " 'seal',\n",
       " 'sheep',\n",
       " 'shrew',\n",
       " 'silver fox',\n",
       " 'skunk',\n",
       " 'sloth',\n",
       " 'snake',\n",
       " 'squirrel',\n",
       " 'tapir',\n",
       " 'tiger',\n",
       " 'toad',\n",
       " 'turtle',\n",
       " 'walrus',\n",
       " 'warthog',\n",
       " 'weasel',\n",
       " 'whale',\n",
       " 'wildcat',\n",
       " 'wolf',\n",
       " 'wolverine',\n",
       " 'wombat',\n",
       " 'woodchuck',\n",
       " 'yak',\n",
       " 'zebra']"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "animals_data[\"animals\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['hippopotamus',\n",
       " 'ferret',\n",
       " 'crocodile',\n",
       " 'parrot',\n",
       " 'salamander',\n",
       " 'llama',\n",
       " 'fish',\n",
       " 'tiger',\n",
       " 'horse',\n",
       " 'guinea pig']"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# random animal\n",
    "random.sample(animals_data[\"animals\"], 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "x = {\"a\": 1, \"b\": 2}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "del x[\"a\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'b': 2}"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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