Tumo.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction To Python"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Let's learn python!\n"
     ]
    }
   ],
   "source": [
    "print \"Let's learn python!\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3\n"
     ]
    }
   ],
   "source": [
    "one = 1\n",
    "two = 2\n",
    "three = one + two\n",
    "print three"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hello world\n"
     ]
    }
   ],
   "source": [
    "hello = \"hello\"\n",
    "world = \"world\"\n",
    "helloworld = hello + \" \" + world\n",
    "print helloworld"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n"
     ]
    }
   ],
   "source": [
    "one = 1\n",
    "two = 2\n",
    "# What do you think this will be?\n",
    "print one/two\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.5\n"
     ]
    }
   ],
   "source": [
    "one = 1.0\n",
    "two = 2\n",
    "print one/two"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2\n",
      "2.5\n"
     ]
    }
   ],
   "source": [
    "print 5/2\n",
    "print 5.0/2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Structures"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Lists"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 2, 3]\n"
     ]
    }
   ],
   "source": [
    "my_list = [1, 2, 3]\n",
    "print my_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 2, 3, 4]\n"
     ]
    }
   ],
   "source": [
    "my_list.append(4)\n",
    "print my_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 2 3\n"
     ]
    }
   ],
   "source": [
    "print my_list[0], my_list[1], my_list[2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4 3 2\n"
     ]
    }
   ],
   "source": [
    "print my_list[-1], my_list[-2], my_list[-3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 2, 3, 'hello', 'how', 'are', 'you']\n"
     ]
    }
   ],
   "source": [
    "weird_list = [1, 2, 3, \"hello\", \"how\", \"are\", \"you\"]\n",
    "print weird_list"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Dictionaries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "my_dict = {\"one\": 1, \"two\": 2, \"hello\": \"world\"}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_dict[\"one\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exercise: turn a list into a dictionary of counts\n",
    "```\n",
    "[\"\"]...\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Reading data from file and the pandas dataframe"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How to read data with \"normal\" python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Center,First name,Surname,Gender,DOB,Attending since,Address,Choice 1 ,Choice 2,Choice 3 ,Choice 4 ,Choice 5 ,Choice 6 \r\n",
      "\n",
      "Yerevan,Arman,Hovhannisyan,Male,1998-07-31,2011-08-16,\"Հայաստան, Երևան, Վարդանանց փողոց 126/1\",Filmmaking,Photography,Graphic Design,Programming,Music,Writing\r\n",
      "\n"
     ]
    }
   ],
   "source": [
    "with open(\"data.csv\", \"r\") as f:\n",
    "    content = f.readlines()\n",
    "    print content[0]\n",
    "    print content[1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How do you structure this data?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Arman', 'Hovhannisyan']\n"
     ]
    }
   ],
   "source": [
    "# hint\n",
    "string = \"Arman,Hovhannisyan\"\n",
    "split = string.split(\",\")\n",
    "print split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[['Arman', 'Hovhannisyan'], ['Lilit', 'Tikoyan']]\n"
     ]
    }
   ],
   "source": [
    "# hint 2\n",
    "strings = [\"Arman,Hovhannisyan\", \"Lilit,Tikoyan\"]\n",
    "splits = []\n",
    "for string in strings:\n",
    "    splits.append(string.split(\",\"))\n",
    "print splits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[['Arman', 'Hovhannisyan'], ['Lilit', 'Tikoyan']]\n"
     ]
    }
   ],
   "source": [
    "strings = [\"Arman,Hovhannisyan\", \"Lilit,Tikoyan\"]\n",
    "\n",
    "# Using the list comprehension\n",
    "splits = [string.split(\",\") for string in strings]\n",
    "\n",
    "print splits"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## How can you use list comprehension and the split function to structure the data?\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data = []\n",
    "with open(\"data.csv\", \"r\") as f:\n",
    "    rows = f.readlines()\n",
    "    data = [row.split(\",\") for row in rows]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Center', 'First name', 'Surname', 'Gender', 'DOB', 'Attending since', 'Address', 'Choice 1 ', 'Choice 2', 'Choice 3 ', 'Choice 4 ', 'Choice 5 ', 'Choice 6 \\r\\n']\n"
     ]
    }
   ],
   "source": [
    "print data[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Yerevan',\n",
       " 'Arman',\n",
       " 'Hovhannisyan',\n",
       " 'Male',\n",
       " '1998-07-31',\n",
       " '2011-08-16',\n",
       " '\"\\xd5\\x80\\xd5\\xa1\\xd5\\xb5\\xd5\\xa1\\xd5\\xbd\\xd5\\xbf\\xd5\\xa1\\xd5\\xb6',\n",
       " ' \\xd4\\xb5\\xd6\\x80\\xd6\\x87\\xd5\\xa1\\xd5\\xb6',\n",
       " ' \\xd5\\x8e\\xd5\\xa1\\xd6\\x80\\xd5\\xa4\\xd5\\xa1\\xd5\\xb6\\xd5\\xa1\\xd5\\xb6\\xd6\\x81 \\xd6\\x83\\xd5\\xb8\\xd5\\xb2\\xd5\\xb8\\xd6\\x81 126/1\"',\n",
       " 'Filmmaking',\n",
       " 'Photography',\n",
       " 'Graphic Design',\n",
       " 'Programming',\n",
       " 'Music',\n",
       " 'Writing\\r\\n']"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### What happened?\n",
    "\n",
    "```\n",
    " '\"\\xd5\\x80\\xd5\\xa1\\xd5\\xb5\\xd5\\xa1\\xd5\\xbd\\xd5\\xbf\\xd5\\xa1\\xd5\\xb6',\n",
    " ' \\xd4\\xb5\\xd6\\x80\\xd6\\x87\\xd5\\xa1\\xd5\\xb6',\n",
    " ' \\xd5\\x8e\\xd5\\xa1\\xd6\\x80\\xd5\\xa4\\xd5\\xa1\\xd5\\xb6\\xd5\\xa1\\xd5\\xb6\\xd6\\x81 \\xd6\\x83\\xd5\\xb8\\xd5\\xb2\\xd5\\xb8\\xd6\\x81\n",
    "```\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Working with data can be hard!\n",
    "* Non standard characters\n",
    "* Commas in the data\n",
    "* Missing values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# The solution: use a Pandas Dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Center</th>\n",
       "      <th>First name</th>\n",
       "      <th>Surname</th>\n",
       "      <th>Gender</th>\n",
       "      <th>DOB</th>\n",
       "      <th>Attending since</th>\n",
       "      <th>Address</th>\n",
       "      <th>Choice 1</th>\n",
       "      <th>Choice 2</th>\n",
       "      <th>Choice 3</th>\n",
       "      <th>Choice 4</th>\n",
       "      <th>Choice 5</th>\n",
       "      <th>Choice 6</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Yerevan</td>\n",
       "      <td>Arman</td>\n",
       "      <td>Hovhannisyan</td>\n",
       "      <td>Male</td>\n",
       "      <td>1998-07-31</td>\n",
       "      <td>2011-08-16</td>\n",
       "      <td>Հայաստան, Երևան, Վարդանանց փողոց 126/1</td>\n",
       "      <td>Filmmaking</td>\n",
       "      <td>Photography</td>\n",
       "      <td>Graphic Design</td>\n",
       "      <td>Programming</td>\n",
       "      <td>Music</td>\n",
       "      <td>Writing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Yerevan</td>\n",
       "      <td>Hasmik</td>\n",
       "      <td>muradyan</td>\n",
       "      <td>Female</td>\n",
       "      <td>1999-03-08</td>\n",
       "      <td>2017-06-07</td>\n",
       "      <td>Նոր Նորքի 8-րդ զանգված, Երևան, Հայաստան</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Yerevan</td>\n",
       "      <td>Levon</td>\n",
       "      <td>Hambardzumyan</td>\n",
       "      <td>Male</td>\n",
       "      <td>1995-05-14</td>\n",
       "      <td>2011-08-25</td>\n",
       "      <td>Զաքարիա Քանաքեռցի փողոց, Երևան, Հայաստան</td>\n",
       "      <td>Filmmaking</td>\n",
       "      <td>Photography</td>\n",
       "      <td>Writing</td>\n",
       "      <td>Drawing</td>\n",
       "      <td>Game Development</td>\n",
       "      <td>3D Modeling</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Yerevan</td>\n",
       "      <td>Mariam</td>\n",
       "      <td>Tigranyan</td>\n",
       "      <td>Female</td>\n",
       "      <td>1999-01-01</td>\n",
       "      <td>2012-01-18</td>\n",
       "      <td>Հայաստան, Yerevan, Սևակի 2 նր բ տ 26</td>\n",
       "      <td>Game Development</td>\n",
       "      <td>Programming</td>\n",
       "      <td>New Media</td>\n",
       "      <td>Photography</td>\n",
       "      <td>Motion Graphics</td>\n",
       "      <td>Robotics</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Dilijan</td>\n",
       "      <td>Manvel</td>\n",
       "      <td>Muradyan</td>\n",
       "      <td>Male</td>\n",
       "      <td>2003-01-17</td>\n",
       "      <td>2016-11-29</td>\n",
       "      <td>Հայաստան, Տավուշի մարզ, գ․ Բերքաբեր, 5, 13</td>\n",
       "      <td>Game Development</td>\n",
       "      <td>3D Modeling</td>\n",
       "      <td>Drawing</td>\n",
       "      <td>Animation</td>\n",
       "      <td>Robotics</td>\n",
       "      <td>Music</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Center First name        Surname  Gender         DOB Attending since  \\\n",
       "0  Yerevan      Arman   Hovhannisyan    Male  1998-07-31      2011-08-16   \n",
       "1  Yerevan     Hasmik       muradyan  Female  1999-03-08      2017-06-07   \n",
       "2  Yerevan      Levon  Hambardzumyan    Male  1995-05-14      2011-08-25   \n",
       "3  Yerevan     Mariam      Tigranyan  Female  1999-01-01      2012-01-18   \n",
       "4  Dilijan     Manvel       Muradyan    Male  2003-01-17      2016-11-29   \n",
       "\n",
       "                                      Address         Choice 1      Choice 2  \\\n",
       "0      Հայաստան, Երևան, Վարդանանց փողոց 126/1        Filmmaking  Photography   \n",
       "1     Նոր Նորքի 8-րդ զանգված, Երևան, Հայաստան               NaN          NaN   \n",
       "2    Զաքարիա Քանաքեռցի փողոց, Երևան, Հայաստան        Filmmaking  Photography   \n",
       "3        Հայաստան, Yerevan, Սևակի 2 նր բ տ 26  Game Development  Programming   \n",
       "4  Հայաստան, Տավուշի մարզ, գ․ Բերքաբեր, 5, 13  Game Development  3D Modeling   \n",
       "\n",
       "        Choice 3     Choice 4          Choice 5     Choice 6   \n",
       "0  Graphic Design  Programming             Music      Writing  \n",
       "1             NaN          NaN               NaN          NaN  \n",
       "2         Writing      Drawing  Game Development  3D Modeling  \n",
       "3       New Media  Photography   Motion Graphics     Robotics  \n",
       "4         Drawing    Animation          Robotics        Music  "
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "data = pd.read_csv('data.csv')\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Center</th>\n",
       "      <th>First name</th>\n",
       "      <th>Surname</th>\n",
       "      <th>Gender</th>\n",
       "      <th>DOB</th>\n",
       "      <th>Attending since</th>\n",
       "      <th>Address</th>\n",
       "      <th>Choice 1</th>\n",
       "      <th>Choice 2</th>\n",
       "      <th>Choice 3</th>\n",
       "      <th>Choice 4</th>\n",
       "      <th>Choice 5</th>\n",
       "      <th>Choice 6</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>Yerevan</td>\n",
       "      <td>Hasmik</td>\n",
       "      <td>Hovhannisyan</td>\n",
       "      <td>Male</td>\n",
       "      <td>1999-01-01</td>\n",
       "      <td>2012-01-18</td>\n",
       "      <td>Նոր Նորքի 8-րդ զանգված, Երևան, Հայաստան</td>\n",
       "      <td>Filmmaking</td>\n",
       "      <td>Photography</td>\n",
       "      <td>New Media</td>\n",
       "      <td>Drawing</td>\n",
       "      <td>Motion Graphics</td>\n",
       "      <td>Writing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Center First name       Surname Gender         DOB Attending since  \\\n",
       "count         5          5             5      5           5               5   \n",
       "unique        2          5             5      2           5               5   \n",
       "top     Yerevan     Hasmik  Hovhannisyan   Male  1999-01-01      2012-01-18   \n",
       "freq          4          1             1      3           1               1   \n",
       "\n",
       "                                        Address   Choice 1      Choice 2  \\\n",
       "count                                         5           4            4   \n",
       "unique                                        5           2            3   \n",
       "top     Նոր Նորքի 8-րդ զանգված, Երևան, Հայաստան  Filmmaking  Photography   \n",
       "freq                                          1           2            2   \n",
       "\n",
       "        Choice 3  Choice 4         Choice 5  Choice 6   \n",
       "count           4         4                4         4  \n",
       "unique          4         4                4         4  \n",
       "top     New Media   Drawing  Motion Graphics   Writing  \n",
       "freq            1         1                1         1  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Center</th>\n",
       "      <td>Yerevan</td>\n",
       "      <td>Yerevan</td>\n",
       "      <td>Yerevan</td>\n",
       "      <td>Yerevan</td>\n",
       "      <td>Dilijan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>First name</th>\n",
       "      <td>Arman</td>\n",
       "      <td>Hasmik</td>\n",
       "      <td>Levon</td>\n",
       "      <td>Mariam</td>\n",
       "      <td>Manvel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Surname</th>\n",
       "      <td>Hovhannisyan</td>\n",
       "      <td>muradyan</td>\n",
       "      <td>Hambardzumyan</td>\n",
       "      <td>Tigranyan</td>\n",
       "      <td>Muradyan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gender</th>\n",
       "      <td>Male</td>\n",
       "      <td>Female</td>\n",
       "      <td>Male</td>\n",
       "      <td>Female</td>\n",
       "      <td>Male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DOB</th>\n",
       "      <td>1998-07-31</td>\n",
       "      <td>1999-03-08</td>\n",
       "      <td>1995-05-14</td>\n",
       "      <td>1999-01-01</td>\n",
       "      <td>2003-01-17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Attending since</th>\n",
       "      <td>2011-08-16</td>\n",
       "      <td>2017-06-07</td>\n",
       "      <td>2011-08-25</td>\n",
       "      <td>2012-01-18</td>\n",
       "      <td>2016-11-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Address</th>\n",
       "      <td>Հայաստան, Երևան, Վարդանանց փողոց 126/1</td>\n",
       "      <td>Նոր Նորքի 8-րդ զանգված, Երևան, Հայաստան</td>\n",
       "      <td>Զաքարիա Քանաքեռցի փողոց, Երևան, Հայաստան</td>\n",
       "      <td>Հայաստան, Yerevan, Սևակի 2 նր բ տ 26</td>\n",
       "      <td>Հայաստան, Տավուշի մարզ, գ․ Բերքաբեր, 5, 13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Choice 1</th>\n",
       "      <td>Filmmaking</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Filmmaking</td>\n",
       "      <td>Game Development</td>\n",
       "      <td>Game Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Choice 2</th>\n",
       "      <td>Photography</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Photography</td>\n",
       "      <td>Programming</td>\n",
       "      <td>3D Modeling</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Choice 3</th>\n",
       "      <td>Graphic Design</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Writing</td>\n",
       "      <td>New Media</td>\n",
       "      <td>Drawing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Choice 4</th>\n",
       "      <td>Programming</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Drawing</td>\n",
       "      <td>Photography</td>\n",
       "      <td>Animation</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Choice 5</th>\n",
       "      <td>Music</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Game Development</td>\n",
       "      <td>Motion Graphics</td>\n",
       "      <td>Robotics</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Choice 6</th>\n",
       "      <td>Writing</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3D Modeling</td>\n",
       "      <td>Robotics</td>\n",
       "      <td>Music</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                      0  \\\n",
       "Center                                          Yerevan   \n",
       "First name                                        Arman   \n",
       "Surname                                    Hovhannisyan   \n",
       "Gender                                             Male   \n",
       "DOB                                          1998-07-31   \n",
       "Attending since                              2011-08-16   \n",
       "Address          Հայաստան, Երևան, Վարդանանց փողոց 126/1   \n",
       "Choice 1                                     Filmmaking   \n",
       "Choice 2                                    Photography   \n",
       "Choice 3                                 Graphic Design   \n",
       "Choice 4                                    Programming   \n",
       "Choice 5                                          Music   \n",
       "Choice 6                                        Writing   \n",
       "\n",
       "                                                       1  \\\n",
       "Center                                           Yerevan   \n",
       "First name                                        Hasmik   \n",
       "Surname                                         muradyan   \n",
       "Gender                                            Female   \n",
       "DOB                                           1999-03-08   \n",
       "Attending since                               2017-06-07   \n",
       "Address          Նոր Նորքի 8-րդ զանգված, Երևան, Հայաստան   \n",
       "Choice 1                                             NaN   \n",
       "Choice 2                                             NaN   \n",
       "Choice 3                                             NaN   \n",
       "Choice 4                                             NaN   \n",
       "Choice 5                                             NaN   \n",
       "Choice 6                                             NaN   \n",
       "\n",
       "                                                        2  \\\n",
       "Center                                            Yerevan   \n",
       "First name                                          Levon   \n",
       "Surname                                     Hambardzumyan   \n",
       "Gender                                               Male   \n",
       "DOB                                            1995-05-14   \n",
       "Attending since                                2011-08-25   \n",
       "Address          Զաքարիա Քանաքեռցի փողոց, Երևան, Հայաստան   \n",
       "Choice 1                                       Filmmaking   \n",
       "Choice 2                                      Photography   \n",
       "Choice 3                                          Writing   \n",
       "Choice 4                                          Drawing   \n",
       "Choice 5                                 Game Development   \n",
       "Choice 6                                      3D Modeling   \n",
       "\n",
       "                                                    3  \\\n",
       "Center                                        Yerevan   \n",
       "First name                                     Mariam   \n",
       "Surname                                     Tigranyan   \n",
       "Gender                                         Female   \n",
       "DOB                                        1999-01-01   \n",
       "Attending since                            2012-01-18   \n",
       "Address          Հայաստան, Yerevan, Սևակի 2 նր բ տ 26   \n",
       "Choice 1                             Game Development   \n",
       "Choice 2                                  Programming   \n",
       "Choice 3                                    New Media   \n",
       "Choice 4                                  Photography   \n",
       "Choice 5                              Motion Graphics   \n",
       "Choice 6                                     Robotics   \n",
       "\n",
       "                                                          4  \n",
       "Center                                              Dilijan  \n",
       "First name                                           Manvel  \n",
       "Surname                                            Muradyan  \n",
       "Gender                                                 Male  \n",
       "DOB                                              2003-01-17  \n",
       "Attending since                                  2016-11-29  \n",
       "Address          Հայաստան, Տավուշի մարզ, գ․ Բերքաբեր, 5, 13  \n",
       "Choice 1                                   Game Development  \n",
       "Choice 2                                        3D Modeling  \n",
       "Choice 3                                            Drawing  \n",
       "Choice 4                                          Animation  \n",
       "Choice 5                                           Robotics  \n",
       "Choice 6                                              Music  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    Yerevan\n",
       "1    Yerevan\n",
       "2    Yerevan\n",
       "3    Yerevan\n",
       "4    Dilijan\n",
       "Name: Center, dtype: object"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"Center\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exercise: Create a map of {center: number of students}\n",
    "## For example:\n",
    "`{ \"Yerevan\": 10, \"Dilijan\": 5, ...}`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Yerevan': 1}"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Hint\n",
    "m = {}\n",
    "# m[\"Yerevan\"]\n",
    "# ERROR!\n",
    "\n",
    "m.get(\"Yerevan\", 0)\n",
    "# 0\n",
    "\n",
    "m[\"Yerevan\"] = m.get(\"Yerevan\", 0) + 1\n",
    "m"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Solution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'Dilijan': 1, 'Yerevan': 4}\n"
     ]
    }
   ],
   "source": [
    "counts = {}\n",
    "for center in data[\"Center\"]:\n",
    "    counts[center] = counts.get(center, 0) + 1\n",
    "print counts"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plotting with Seaborn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10c2f0510>"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10b56bcd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plot = sns.countplot()\n",
    "%matplotlib inline\n",
    "sns.countplot(x='Center', data=data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Exercise: write a function to create a count map out of any column\n",
    "\n",
    "#### Turn this:\n",
    "```\n",
    "counts = {}\n",
    "for center in data[\"Center\"]:\n",
    "    counts[center] = counts.get(center, 0) + 1\n",
    "print counts\n",
    "```\n",
    "#### Into a Function\n",
    "\n",
    "```\n",
    "def count(column):\n",
    "    ...\n",
    "``` \n",
    "\n",
    "#### So that we can run this:\n",
    "```\n",
    "count(\"Center\")\n",
    "```\n",
    "\n",
    "#### And get this:\n",
    "```\n",
    "{'Dilijan': 1, 'Yerevan': 4}\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def list_to_counts(column):\n",
    "    counts = {}\n",
    "    for item in data[column]:\n",
    "        counts[item] = counts.get(item, 0) + 1\n",
    "    return counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Dilijan': 1, 'Yerevan': 4}"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list_to_counts(\"Center\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{nan: 1, 'Game Development': 2, 'Filmmaking': 2}\n"
     ]
    }
   ],
   "source": [
    "c1 = list_to_counts(\"Choice 1 \")\n",
    "print c1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## What is \"nan\", how to get rid of it?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Center</th>\n",
       "      <th>First name</th>\n",
       "      <th>Surname</th>\n",
       "      <th>Gender</th>\n",
       "      <th>DOB</th>\n",
       "      <th>Attending since</th>\n",
       "      <th>Address</th>\n",
       "      <th>Choice 1</th>\n",
       "      <th>Choice 2</th>\n",
       "      <th>Choice 3</th>\n",
       "      <th>Choice 4</th>\n",
       "      <th>Choice 5</th>\n",
       "      <th>Choice 6</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Yerevan</td>\n",
       "      <td>Arman</td>\n",
       "      <td>Hovhannisyan</td>\n",
       "      <td>Male</td>\n",
       "      <td>1998-07-31</td>\n",
       "      <td>2011-08-16</td>\n",
       "      <td>Հայաստան, Երևան, Վարդանանց փողոց 126/1</td>\n",
       "      <td>Filmmaking</td>\n",
       "      <td>Photography</td>\n",
       "      <td>Graphic Design</td>\n",
       "      <td>Programming</td>\n",
       "      <td>Music</td>\n",
       "      <td>Writing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Yerevan</td>\n",
       "      <td>Hasmik</td>\n",
       "      <td>muradyan</td>\n",
       "      <td>Female</td>\n",
       "      <td>1999-03-08</td>\n",
       "      <td>2017-06-07</td>\n",
       "      <td>Նոր Նորքի 8-րդ զանգված, Երևան, Հայաստան</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Yerevan</td>\n",
       "      <td>Levon</td>\n",
       "      <td>Hambardzumyan</td>\n",
       "      <td>Male</td>\n",
       "      <td>1995-05-14</td>\n",
       "      <td>2011-08-25</td>\n",
       "      <td>Զաքարիա Քանաքեռցի փողոց, Երևան, Հայաստան</td>\n",
       "      <td>Filmmaking</td>\n",
       "      <td>Photography</td>\n",
       "      <td>Writing</td>\n",
       "      <td>Drawing</td>\n",
       "      <td>Game Development</td>\n",
       "      <td>3D Modeling</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Yerevan</td>\n",
       "      <td>Mariam</td>\n",
       "      <td>Tigranyan</td>\n",
       "      <td>Female</td>\n",
       "      <td>1999-01-01</td>\n",
       "      <td>2012-01-18</td>\n",
       "      <td>Հայաստան, Yerevan, Սևակի 2 նր բ տ 26</td>\n",
       "      <td>Game Development</td>\n",
       "      <td>Programming</td>\n",
       "      <td>New Media</td>\n",
       "      <td>Photography</td>\n",
       "      <td>Motion Graphics</td>\n",
       "      <td>Robotics</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Dilijan</td>\n",
       "      <td>Manvel</td>\n",
       "      <td>Muradyan</td>\n",
       "      <td>Male</td>\n",
       "      <td>2003-01-17</td>\n",
       "      <td>2016-11-29</td>\n",
       "      <td>Հայաստան, Տավուշի մարզ, գ․ Բերքաբեր, 5, 13</td>\n",
       "      <td>Game Development</td>\n",
       "      <td>3D Modeling</td>\n",
       "      <td>Drawing</td>\n",
       "      <td>Animation</td>\n",
       "      <td>Robotics</td>\n",
       "      <td>Music</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Center First name        Surname  Gender         DOB Attending since  \\\n",
       "0  Yerevan      Arman   Hovhannisyan    Male  1998-07-31      2011-08-16   \n",
       "1  Yerevan     Hasmik       muradyan  Female  1999-03-08      2017-06-07   \n",
       "2  Yerevan      Levon  Hambardzumyan    Male  1995-05-14      2011-08-25   \n",
       "3  Yerevan     Mariam      Tigranyan  Female  1999-01-01      2012-01-18   \n",
       "4  Dilijan     Manvel       Muradyan    Male  2003-01-17      2016-11-29   \n",
       "\n",
       "                                      Address         Choice 1      Choice 2  \\\n",
       "0      Հայաստան, Երևան, Վարդանանց փողոց 126/1        Filmmaking  Photography   \n",
       "1     Նոր Նորքի 8-րդ զանգված, Երևան, Հայաստան                                  \n",
       "2    Զաքարիա Քանաքեռցի փողոց, Երևան, Հայաստան        Filmmaking  Photography   \n",
       "3        Հայաստան, Yerevan, Սևակի 2 նր բ տ 26  Game Development  Programming   \n",
       "4  Հայաստան, Տավուշի մարզ, գ․ Բերքաբեր, 5, 13  Game Development  3D Modeling   \n",
       "\n",
       "        Choice 3     Choice 4          Choice 5     Choice 6   \n",
       "0  Graphic Design  Programming             Music      Writing  \n",
       "1                                                              \n",
       "2         Writing      Drawing  Game Development  3D Modeling  \n",
       "3       New Media  Photography   Motion Graphics     Robotics  \n",
       "4         Drawing    Animation          Robotics        Music  "
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.fillna(\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data_clean = data.fillna(\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{nan: 1, 'Game Development': 2, 'Filmmaking': 2}\n"
     ]
    }
   ],
   "source": [
    "c1 = list_to_counts(\"Choice 1 \")\n",
    "print c1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def list_to_counts(column):\n",
    "    counts = {}\n",
    "    for item in data_clean[column]:\n",
    "        if item:\n",
    "            counts[item] = counts.get(item, 0) + 1\n",
    "    return counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'Game Development': 2, 'Filmmaking': 2}\n"
     ]
    }
   ],
   "source": [
    "c1 = list_to_counts(\"Choice 1 \")\n",
    "print c1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### What does \"`if item:`\" do?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\"\" is False!\n"
     ]
    }
   ],
   "source": [
    "if \"\":\n",
    "    print '\"\" is True!'\n",
    "else:\n",
    "    print '\"\" is False!'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x107d44890>"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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+/npgDXAt3bfBS0fafaeqvpvkOmB1v3xn4D3pBuF7GHj6yD4OAt5DFyLfnKOOCwGqu7vr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\nSFKjDABJapQBIEmNMgAkqVEGgCQ16v8BmZrzsb63UCwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10c267c90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "sns.countplot(x='Choice 1 ', data=data)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Filmmaking': 2, 'Game Development': 2}"
      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c = list_to_counts('Choice 1 ')\n",
    "c"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exercise: What is the most common topic across all choices?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "key: two\n",
      "value: 2\n",
      "----------------\n",
      "key: one\n",
      "value: 1\n",
      "----------------\n"
     ]
    }
   ],
   "source": [
    "# hint: use iteritems()\n",
    "m = {\"one\": 1, \"two\": 2}\n",
    "for key, value in m.iteritems():\n",
    "    print \"key: {}\".format(key)\n",
    "    print \"value: {}\".format(value)\n",
    "    print \"----------------\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'Robotics': 2, 'Game Development': 3, '3D Modeling': 2, 'Photography': 3, 'New Media': 1, 'Programming': 2, 'Writing': 2, 'Graphic Design': 1, 'Animation': 1, 'Music': 2, 'Filmmaking': 2, 'Drawing': 2, 'Motion Graphics': 1}\n"
     ]
    }
   ],
   "source": [
    "c1 = list_to_counts('Choice 1 ')\n",
    "c2 = list_to_counts('Choice 2')\n",
    "c3 = list_to_counts('Choice 3 ')\n",
    "c4 = list_to_counts('Choice 4 ')\n",
    "c5 = list_to_counts('Choice 5 ')\n",
    "c6 = list_to_counts('Choice 6 ')\n",
    "\n",
    "total_counts = {}\n",
    "for count_map in [c1, c2, c3, c4, c5, c6]:\n",
    "    for choice, count in count_map.iteritems():\n",
    "        if choice != \"nan\":\n",
    "            total_counts[choice] = total_counts.get(choice, 0) + count\n",
    "\n",
    "print total_counts\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exercise: use pylab to plot this data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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lLm8InDVrltujo0888YS8vLw0ceJEt3NnZGS4DUJ3qlWrJrvdrqVLlzodnT1z5oxmzZrl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\nCmYJIYQQQojTomCWEEIIIYQ4rf8Apcb+S2Y+HhsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10ad15390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### EXAMPLE - Change this to plot total_counts\n",
    "\n",
    "import matplotlib.pyplot as plt; plt.rcdefaults()\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    " \n",
    "x_ticks = ('Python', 'C++', 'Java', 'Perl', 'Scala', 'Lisp')\n",
    "y_pos = np.arange(len(x_ticks))\n",
    "values = [10,8,6,4,2,1]\n",
    " \n",
    "plt.bar(y_pos, values, align='center', alpha=0.5)\n",
    "plt.xticks(y_pos, x_ticks)\n",
    "plt.ylabel('Usage')\n",
    "plt.title('Programming language usage')\n",
    " \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0 1 2 3 4 5]\n"
     ]
    }
   ],
   "source": [
    "print y_pos"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Change the above to plot total_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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l1uT26NGjWsGVpIiICHXs2FFZWVkuH6e4uFiVlZXujgcAAIDrgOXO5F7J2bNnddNNN11z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\nIYQQQow6/x/To/vcKjmF0wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10c4eb250>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt; plt.rcdefaults()\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    " \n",
    "topics = total_counts.keys()\n",
    "y_pos = np.arange(len(topics))\n",
    "performance = total_counts.values()\n",
    " \n",
    "plt.bar(y_pos, performance, align='center', alpha=0.5)\n",
    "plt.xticks(y_pos, topics)\n",
    "plt.ylabel('Number of students')\n",
    "plt.title('Course')\n",
    "plt.xticks(rotation=70)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exercise: Order by count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt; plt.rcdefaults()\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    " \n",
    "topics = total_counts.keys()\n",
    "y_pos = np.arange(len(topics))\n",
    "performance = total_counts.values()\n",
    " \n",
    "plt.bar(y_pos, performance, align='center', alpha=0.5)\n",
    "plt.xticks(y_pos, topics)\n",
    "plt.ylabel('Number of students')\n",
    "plt.title('Course')\n",
    "plt.xticks(rotation=70)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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