{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mean =  5.44  mode = 5 median = 5\n"
     ]
    }
   ],
   "source": [
    "########################################################################\n",
    "########################################################################\n",
    "# \n",
    "# MeanModeMedian.py \n",
    "# write a function to return the mean, mode and median of the following \n",
    "# numbers\n",
    "#\n",
    "########################################################################\n",
    "########################################################################\n",
    "\n",
    "# 1000 numbers taken from a Poisson distibution\n",
    "numbers = [ 5, 5, 6, 5, 3, 3, 7, 5, 4, 4, 3, 4, 5, 3, 3, 2, 2, 7, 7,\n",
    "            7, 5, 7, 10, 3, 2, 2, 6, 7, 10, 6, 7, 6, 5, 3, 5, 4, 4, 4, 2, 7, 6, 6,\n",
    "            5, 11, 5, 7, 3, 9, 5, 2, 5, 12, 7, 8, 6, 2, 1, 5, 5, 6, 5, 8, 4, 6, 4,\n",
    "            5, 4, 5, 5, 5, 7, 4, 4, 2, 2, 6, 5, 6, 7, 3, 8, 8, 10, 6, 7, 6, 6, 3,\n",
    "            5, 9, 2, 4, 6, 7, 7, 4, 5, 4, 8, 5, 5, 4, 7, 8, 4, 10, 4, 1, 9, 7, 10,\n",
    "            7, 1, 8, 7, 6, 1, 11, 6, 5, 6, 3, 7, 3, 4, 6, 6, 4, 7, 5, 6, 2, 2, 7,\n",
    "            3, 8, 4, 5, 8, 4, 5, 2, 7, 4, 7, 7, 4, 4, 7, 1, 3, 11, 3, 4, 2, 5, 4,\n",
    "            4, 4, 4, 8, 10, 8, 2, 4, 6, 0, 7, 4, 5, 8, 6, 6, 4, 5, 8, 8, 6, 5, 8,\n",
    "            11, 4, 6, 6, 2, 5, 2, 5, 2, 6, 4, 9, 7, 10, 6, 2, 11, 8, 5, 1, 4, 5,\n",
    "            3, 5, 4, 3, 8, 0, 6, 13, 5, 3, 8, 3, 6, 8, 2, 4, 4, 4, 4, 2, 2, 6, 5,\n",
    "            7, 2, 6, 7, 2, 4, 6, 5, 4, 12, 4, 9, 1, 12, 5, 6, 11, 6, 8, 9, 2, 9,\n",
    "            3, 5, 10, 7, 8, 6, 4, 7, 6, 7, 5, 4, 2, 8, 4, 1, 8, 5, 2, 7, 5, 8, 4,\n",
    "            6, 3, 2, 6, 4, 3, 7, 2, 8, 6, 6, 7, 4, 7, 5, 4, 7, 3, 4, 7, 7, 3, 5,\n",
    "            4, 6, 7, 9, 5, 8, 2, 4, 6, 11, 7, 9, 2, 3, 2, 6, 6, 7, 7, 5, 4, 4, 3,\n",
    "            5, 4, 4, 5, 7, 5, 2, 5, 4, 3, 6, 5, 5, 5, 7, 3, 7, 4, 7, 4, 3, 4, 7,\n",
    "            3, 9, 3, 6, 6, 7, 4, 2, 3, 7, 5, 5, 6, 4, 6, 9, 3, 4, 2, 3, 4, 9, 8,\n",
    "            5, 7, 8, 6, 3, 1, 5, 5, 1, 6, 6, 6, 6, 6, 5, 5, 10, 2, 4, 2, 5, 8, 4,\n",
    "            7, 6, 4, 3, 3, 7, 6, 3, 8, 4, 5, 6, 4, 2, 9, 7, 4, 9, 4, 7, 4, 1, 9,\n",
    "            2, 6, 5, 7, 3, 5, 4, 8, 4, 9, 5, 9, 6, 5, 4, 4, 6, 6, 4, 9, 9, 7, 1,\n",
    "            4, 5, 10, 6, 7, 4, 4, 10, 3, 3, 3, 3, 5, 4, 6, 4, 11, 2, 10, 4, 4, 7,\n",
    "            3, 10, 5, 5, 10, 5, 8, 7, 5, 6, 5, 6, 7, 3, 5, 10, 9, 3, 4, 3, 5, 5,\n",
    "            9, 6, 4, 4, 8, 8, 5, 6, 5, 4, 3, 10, 7, 6, 7, 5, 3, 8, 5, 7, 8, 2, 9,\n",
    "            11, 5, 3, 4, 5, 4, 4, 8, 2, 5, 3, 1, 2, 5, 6, 11, 4, 6, 3, 5, 7, 9, 5,\n",
    "            10, 4, 7, 10, 5, 4, 1, 8, 3, 8, 5, 6, 4, 5, 2, 6, 6, 7, 11, 6, 6, 4,\n",
    "            6, 8, 4, 3, 5, 4, 5, 3, 8, 8, 3, 5, 7, 9, 7, 5, 8, 0, 8, 3, 10, 3, 8,\n",
    "            9, 7, 4, 4, 1, 3, 5, 3, 5, 4, 3, 6, 8, 3, 3, 7, 2, 4, 9, 8, 4, 8, 3,\n",
    "            6, 7, 7, 5, 4, 5, 3, 4, 3, 2, 2, 3, 5, 11, 6, 1, 5, 8, 3, 6, 2, 7, 4,\n",
    "            5, 6, 6, 4, 5, 2, 4, 6, 5, 4, 9, 6, 2, 9, 8, 4, 5, 7, 12, 1, 7, 7, 5,\n",
    "            7, 5, 5, 10, 8, 3, 7, 2, 7, 3, 8, 4, 3, 8, 4, 7, 6, 5, 4, 7, 3, 3, 4,\n",
    "            5, 5, 5, 4, 7, 0, 7, 5, 3, 9, 4, 8, 5, 2, 7, 8, 8, 5, 4, 11, 8, 5, 4,\n",
    "            3, 4, 4, 3, 3, 3, 8, 2, 8, 6, 9, 4, 7, 8, 5, 4, 6, 5, 5, 4, 6, 6, 7,\n",
    "            5, 8, 6, 7, 7, 7, 6, 5, 6, 2, 6, 8, 6, 5, 5, 4, 9, 9, 5, 5, 6, 12, 8,\n",
    "            6, 7, 0, 7, 6, 7, 3, 6, 4, 4, 8, 11, 5, 3, 7, 6, 6, 7, 5, 2, 8, 7, 6,\n",
    "            1, 10, 5, 6, 8, 3, 5, 3, 6, 2, 9, 6, 5, 7, 6, 7, 5, 12, 5, 1, 5, 13,\n",
    "            9, 4, 5, 3, 3, 11, 8, 4, 7, 7, 6, 6, 6, 5, 6, 6, 3, 2, 5, 5, 8, 10, 8,\n",
    "            6, 4, 9, 6, 2, 1, 7, 5, 5, 7, 5, 4, 5, 5, 4, 5, 5, 6, 4, 3, 6, 6, 6,\n",
    "            4, 7, 6, 6, 3, 2, 4, 5, 3, 6, 8, 14, 4, 4, 6, 2, 6, 5, 5, 2, 1, 6, 9,\n",
    "            5, 8, 7, 4, 6, 5, 5, 4, 5, 6, 10, 3, 1, 6, 3, 7, 5, 12, 8, 6, 7, 4, 7,\n",
    "            7, 6, 8, 1, 5, 4, 7, 8, 4, 8, 8, 4, 10, 3, 6, 5, 6, 4, 4, 2, 6, 4, 3,\n",
    "            6, 8, 6, 11, 2, 8, 3, 2, 9, 6, 2, 7, 5, 8, 6, 8, 5, 3, 3, 7, 8, 5, 5,\n",
    "            9, 6, 10, 3, 9, 4, 11, 9, 8, 4, 6, 3, 4, 7, 5, 7, 8, 4, 5, 5, 7, 3, 2,\n",
    "            7, 3, 4, 5, 6, 4, 10, 5, 6, 6, 4, 5, 13, 3, 5, 6, 7, 4, 3, 3, 6, 8,\n",
    "            10, 6, 4, 11, 2, 3, 9, 7, 3, 5, 3, 4, 8, 3, 3, 5, 7, 3, 5, 2, 5, 8, 2,\n",
    "            5, 4, 6, 10, 7, 5, 7, 4, 5, 9, 4, 0, 3, 3, 4, 9, 4, 7, 1, 8, 4, 6]\n",
    "\n",
    "# the mean = 5.44\n",
    "# the mode = 5\n",
    "# the median = 5\n",
    "\n",
    "def mmm(numbers):\n",
    "    \"\"\"Return the mean, mode and median of a list of numbers\"\"\"\n",
    "    mean = float(sum(numbers))/len(numbers) # float is necessary as python2 does integer division...\n",
    "    # fill in a dictionary where the key is each value in n and count the entries\n",
    "    entries = dict()\n",
    "    for i in numbers:\n",
    "        if i in entries:    # is there already this value\n",
    "            entries[i] += 1 # increment it\n",
    "        else:               # if not create it\n",
    "            entries[i] = 1  # set first value to 1\n",
    "    maxEntry = 0\n",
    "    mode = 0\n",
    "    # note need iteritems() below if using python2\n",
    "    for k,v in entries.items(): # k = key, i.e. number from n, v=value i.e. count of number\n",
    "        if v > maxEntry:\n",
    "            maxEntry = v\n",
    "            mode = k\n",
    "    nSort = numbers.copy() # must \"deep copy\" numbers to avoid changing the list\n",
    "    nSort.sort()\n",
    "    median = nSort[int(len(nSort)/2)] # int as python3 does float division...\n",
    "    return mean,mode,median\n",
    "\n",
    "mean,mode,median = mmm(numbers)\n",
    "print(\"mean = {:5.3}  mode = {} median = {}\".format(mean,mode,median))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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pNSMXlZOcQ+800j/pa766qt4BvLu9PnSEseuTjCYZPXjw4PQXK0knqS4XlQ8AS/rWF7e2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\nCTAQJEmNgSBJAuD/AyyoV/cQHWvyAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x26a539f6e48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "plt.hist(numbers,bins=max(numbers),normed=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}