Dictionary exercise

dictionaries.ipynb

{
 "metadata": {
  "name": "dictionaries"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Dictionaries"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Constructing a dictionary"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "d = {'hello': 'A greeting'}"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "d['hello']"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 2,
       "text": [
        "'A greeting'"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Here 'hello' is called the **key** and 'A greeting' is the **value**."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### A more general dictionary"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "k = {'hello': 'A greeting', 1: 'One'}\n",
      "k[1]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 4,
       "text": [
        "'One'"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Note that now the **key** is a number and the **value** is a string."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Modifying a dictionary"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "y = {1: 2, 3: 4}\n",
      "y[1] = y[1] + 1\n",
      "\n",
      "y[1]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "3"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Worked examples"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "## Construct a dictionary that maps three words to three sentences\n",
      "oxford = {...}"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "my_dict = {'hello': 'world'}\n",
      "... ## look up 'hello', should return 'world'"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "## Construct a dictionary that maps three numbers to three words\n",
      "number_map = {...}"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "concept_map = {...}\n",
      "concept_map['donkey']  ## should return \"is an animal\""
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "histogram = {'a': 5, 'b': 7, 'd': 9}\n",
      "... # increase the count of 'b' by 2\n",
      "histogram['b'] # should yield 9 "
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Advanced challenge: use the histogram above, and generate a list\n",
      "# containing the corresponding items.\n",
      "#\n",
      "# E.g., histogram = {'a': 3, 'b': 2} => ['a', 'a', 'a', 'b', 'b']\n",
      "#       histogram = {'a': 1, 'd': 4} => ['a', 'd', 'd', 'd', 'd']\n",
      "\n",
      "output = []\n",
      "for key in histogram:\n",
      "    ..."
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Real-world example\n",
      "\n",
      "When trying to break simple ciphers (e.g., <http://en.wikipedia.org/wiki/Substitution_cipher>) it is\n",
      "often useful to count the number of times each letter occurs in a piece of text.  In the following example,\n",
      "we count such occurrences and plot them."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "text = \"\"\"\n",
      "Hereupon Legrand arose, with a grave and stately air, and brought me the beetle\n",
      "from a glass case in which it was enclosed. It was a beautiful scarabaeus, and, at\n",
      "that time, unknown to naturalists\u2014of course a great prize in a scientific point\n",
      "of view. There were two round black spots near one extremity of the back, and a\n",
      "long one near the other. The scales were exceedingly hard and glossy, with all the\n",
      "appearance of burnished gold. The weight of the insect was very remarkable, and,\n",
      "taking all things into consideration, I could hardly blame Jupiter for his opinion\n",
      "respecting it.\"\"\""
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 18
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "frequency = {}\n",
      "alphabet = 'abcdefghijklmnopqrstuvwxyz'\n",
      "for l in alphabet:\n",
      "    frequency[l] = 0\n",
      "\n",
      "for l in text.lower():\n",
      "    if l and l in alphabet:\n",
      "        frequency[l] += 1\n",
      "\n",
      "print frequency"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "{'a': 48, 'c': 16, 'b': 9, 'e': 58, 'd': 16, 'g': 13, 'f': 9, 'i': 34, 'h': 22, 'k': 5, 'j': 1, 'm': 6, 'l': 21, 'o': 30, 'n': 35, 'q': 0, 'p': 9, 's': 27, 'r': 31, 'u': 12, 't': 41, 'w': 12, 'v': 3, 'y': 6, 'x': 2, 'z': 1}\n"
       ]
      }
     ],
     "prompt_number": 19
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np\n",
      "import matplotlib.pyplot as plt\n",
      "\n",
      "x = np.arange(26)\n",
      "f = [frequency[alphabet[l]] for l in x]\n",
      "\n",
      "plt.stem(x, f)\n",
      "plt.xticks(x, alphabet);"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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4MLiJiGSGwU1EJDMMbiIimWFwExHJDIObiEhmZP0gBXeekMKnqhCR3Mk2uN15QgqfqkJE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\nbiIimWFwExHJzP8Bu8WxaIVedlUAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x3ce7810>"
       ]
      }
     ],
     "prompt_number": 20
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now, have a look at this Morse code table.  Is there any correlation between the *length* of each\n",
      "code and the table above?\n",
      "<p/>\n",
      "<img src=\"http://upload.wikimedia.org/wikipedia/commons/b/b5/International_Morse_Code.svg\" width=\"300px\"/>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}