96chan/All about TEDx

## All about TEDx
{
 "metadata": {
  "name": "All About TEDx"
 },
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 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<span id=\"goal\"></span>\n"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "All About TEDx"
     ]
    },
    {
     "cell_type": "heading",
     "level": 4,
     "metadata": {},
     "source": [
      "TEAM : Chan Kim, JT Huang"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Our Goal"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "TED is a nonprofit devoted to Ideas Worth Spreading. It started out (in 1984) as a conference bringing together people from three worlds: Technology, Entertainment, and Design. The TED Open Translation Project brings TED Talks beyond the English-speaking world by offering subtitles, interactive transcripts and the ability for any talk to be translated by volunteers worldwide. The project was launched with 300 translations, 40 languages and 200 volunteer translators; now, there are more than 32,000 completed translations from the thousands-strong community. The TEDx program is designed to give communities the opportunity to stimulate dialogue through TED-like experiences at the local level.\n",
      "\n",
      "Our project wants to encourage people to translate TEDx Talk as well by showing how TEDx Talk videos are translated and spreaded among different languages, places and topics, and comparing the spreading status with TED Talk videos.\n",
      "\n",
      "The questions we are trying to answer:\n",
      "\n",
      "* How are the TEDx videos distributed among different languages and places?\n",
      "* How is the spreading status of TEDx videos comparing to that of TED videos?"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<span id=\"outline\"></span>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Outline"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<span id=\"outline\"></span>\n",
      "<a href=\"#goal\">1. Our Goal</a><br>\n",
      "<a href=\"#dataset\">2. Dataset</a><br>\n",
      "<a href=\"#prep\">3. Data collection and cleaning</a><br>\n",
      "<a href=\"#stat\">4. Basic Statistics: by language</a><br>\n",
      "<a href=\"#stat2\">5. Basic Statistics: by country</a><br>\n",
      "<a href=\"#viz1\">6. Trends of TEDx over past 5 years by language</a><br>\n",
      "<a href=\"#viz2\">7. Comparison between TED and TEDx by language</a><br>\n",
      "<a href=\"#next\">8. What's next?</a>\n",
      "\n",
      "\n",
      "\n"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<span id=\"dataset\"></span>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "About Dataset"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Since TEDx did not provide any API for people to retrieve video data, we write our own scrapper to crawl various attributes of the TEDx videos.\n",
      "And since all TEDx videos are on YouTube, we also use YouTube API to retrieve more interesting information about the videos.\n",
      "\n",
      "* **TEDx Website**\n",
      "    * Language\n",
      "    * Event\n",
      "    * Country\n",
      "    * Topic\n",
      "\n",
      "* **YouTube API**\n",
      "    * Uploaded Timestamp\n",
      "    * Title\n",
      "    * Tags\n",
      "    * Thumbnail\n",
      "    * Duration\n",
      "    * Like Count\n",
      "    * Rating\n",
      "    * Rating Count\n",
      "    * View Count\n",
      "    * Favorite Count\n",
      "    * Comment Count\n"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<span id=\"prep\"></span>\n",
      "<a href=\"#outline\">Go to Top</a>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "TEDx Web Scrapper"
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Stage 1. Get Type Portal Links from TEDx Home URL"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "First, we try to get all the type portal links from [TEDx home URL](http://tedxtalks.ted.com).\n",
      "\n",
      "We try to find out all the links begin with the following strings in the [TEDx home URL](http://tedxtalks.ted.com) with [Beautiful Soup](http://www.crummy.com/software/BeautifulSoup/).\n",
      "\n",
      "* **Language** Pages: '/browse/talks-by-language/', EX:\n",
      "    * Korean: '/browse/talks-by-language/korean'\n",
      "    * Chinese: '/browse/talks-by-language/chinese'\n",
      "* **Event** Pages: '/browse/talks-by-event/', EX:\n",
      "    * TEDxBerkeley: '/browse/talks-by-event/tedxberkeley'\n",
      "    * TEDxStanford: '/browse/talks-by-event/tedxstanford'\n",
      "* **Country** Pages: '/browse/talks-by-country/'\n",
      "    * South Korea: '/browse/talks-by-country/korea'\n",
      "    * Taiwan: '/browse/talks-by-country/taiwan'\n",
      "* **Topic** Pages: '/browse/talks-by-topic/\n",
      "    * Technology: '/browse/talks-by-topic/technology'\n",
      "    * Design: '/browse/talks-by-topic/design'"
     ]
    },
    {
     "cell_type": "heading",
     "level": 4,
     "metadata": {},
     "source": [
      "Sample Code and Results"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import requests\n",
      "from bs4 import BeautifulSoup\n",
      "\n",
      "TEDX_HOME_URL = \"http://tedxtalks.ted.com\"\n",
      "LANG_URL = \"/browse/talks-by-language/\"\n",
      "\n",
      "s = requests.get(TEDX_HOME_URL)\n",
      "soup = BeautifulSoup(s.content)\n",
      "\n",
      "total = 0\n",
      "link_tags = soup.find_all('a', href=True)\n",
      "for link_tag in link_tags:\n",
      "    link = link_tag['href']\n",
      "    lang = link_tag.next_element.next_element.next_element\n",
      "    if link.startswith(LANG_URL):\n",
      "        print(\"Language %s: %s\" % (lang, link))\n",
      "        total += 1\n",
      "\n",
      "print(\"Total: %d\" % (total))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Language American Sign Language: /browse/talks-by-language/asl\n",
        "Language Azerbaijani: /browse/talks-by-language/azerbaijani\n",
        "Language Galician: /browse/talks-by-language/galician\n",
        "Language Arabic: /browse/talks-by-language/arabic\n",
        "Language Bulgarian: /browse/talks-by-language/bulgarian\n",
        "Language Catalan: /browse/talks-by-language/catalan\n",
        "Language Chinese: /browse/talks-by-language/chinese\n",
        "Language Croatian: /browse/talks-by-language/croatian\n",
        "Language Czech: /browse/talks-by-language/czech\n",
        "Language Dutch: /browse/talks-by-language/dutch\n",
        "Language English: /browse/talks-by-language/english\n",
        "Language Estonian: /browse/talks-by-language/estonian\n",
        "Language Finnish: /browse/talks-by-language/finnish\n",
        "Language French: /browse/talks-by-language/french\n",
        "Language German: /browse/talks-by-language/german\n",
        "Language Greek: /browse/talks-by-language/greek\n",
        "Language Hebrew: /browse/talks-by-language/hebrew\n",
        "Language Hindi: /browse/talks-by-language/hindi\n",
        "Language Hungarian: /browse/talks-by-language/hungarian\n",
        "Language Icelandic: /browse/talks-by-language/icelandic\n",
        "Language Indonesian: /browse/talks-by-language/indonesian\n",
        "Language Italian: /browse/talks-by-language/italian\n",
        "Language Japanese: /browse/talks-by-language/japanese\n",
        "Language Korean: /browse/talks-by-language/korean\n",
        "Language Lithuanian: /browse/talks-by-language/lithuanian\n",
        "Language Malay: /browse/talks-by-language/malay\n",
        "Language Polish: /browse/talks-by-language/polish\n",
        "Language Portuguese: /browse/talks-by-language/portuguese\n",
        "Language Rajasthani: /browse/talks-by-language/rajasthani\n",
        "Language Romanian: /browse/talks-by-language/romanian\n",
        "Language Russian: /browse/talks-by-language/russian\n",
        "Language Slovak: /browse/talks-by-language/slovak\n",
        "Language Slovene: /browse/talks-by-language/slovene\n",
        "Language Spanish: /browse/talks-by-language/spanish\n",
        "Language Swedish: /browse/talks-by-language/swedish\n",
        "Language Tamil: /browse/talks-by-language/tamil\n",
        "Language Thai: /browse/talks-by-language/thai\n",
        "Language Turkish: /browse/talks-by-language/turkish\n",
        "Language Ukrainian: /browse/talks-by-language/ukrainian\n",
        "Language Urdu: /browse/talks-by-language/urdu\n",
        "Total: 40\n"
       ]
      }
     ],
     "prompt_number": 68
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Stage 2: Get Video Links in Type Portal Links"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Then we go to each type portal link to get video links, and the type will become the attribute of the video.\n",
      "\n",
      "We will go through page 1, page 2, until there is no other pages in that type attribute. \n",
      "For example, we will go to 'http://tedxtalks.ted.com/browse/talks-by-language/icelandic?page=1', then 'http://tedxtalks.ted.com/browse/talks-by-language/icelandic?page=2' and stop at ''http://tedxtalks.ted.com/browse/talks-by-language/icelandic?page=3' to get all the 28 videos in Icelandic.\n",
      "\n",
      "In 'http://tedxtalks.ted.com/browse/talks-by-language/icelandic?page=1' we can find the video link '/list/search%3Atag%3A%22icelandic%22/video/TEDxReykjavik-Eythor-Edvardsson' by using Beautiful Soup and the regular expression. For example, the second video in 'http://tedxtalks.ted.com/browse/talks-by-language/icelandic?page=1'\n",
      "\n",
      "`<a id=\"mvp_grid_panel_img_1\" href=\"/list/search%3Atag%3A%22icelandic%22/video/TEDxReykjavik-Eythor-Edvardsson\" class=\"mvp_thumbnail_magnified\" style=\"position: relative; width: 293px; height: 220px; background-image: url('http://s3.amazonaws.com/magnifythumbs/GZL3TH25NHYK1LB6.jpg'); filter: progid:DXImageTransform.Microsoft.AlphaImageLoader( src='http://s3.amazonaws.com/magnifythumbs/GZL3TH25NHYK1LB6.jpg',  sizingMethod='scale');\" title=\"TEDxReykjavik - Eythor Edvardsson -\"></a>`"
     ]
    },
    {
     "cell_type": "heading",
     "level": 4,
     "metadata": {},
     "source": [
      "Sample Code and Results"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import re\n",
      "\n",
      "VIDEO_LINK_PREFIX = \"mvp_grid_panel_img_\"\n",
      "MSG_CLASS = \"mvp_padded_message\"\n",
      "EMPTY_PAGE_MSG = \"This page is empty.\"\n",
      "\n",
      "portal_url = \"http://tedxtalks.ted.com/browse/talks-by-language/icelandic\"\n",
      "page = 1\n",
      "while(True):\n",
      "    # EX: http://tedxtalks.ted.com/browse/talks-by-language/icelandic?page=1\n",
      "    url = portal_url + \"?page=\" + str(page)\n",
      "    print(\"Reading URL: \" + url)\n",
      "    s = requests.get(url)\n",
      "    soup = BeautifulSoup(s.content)\n",
      "    \n",
      "    # if there is no Next page\n",
      "    # <div class=\"mvp_padded_message\">This page is empty.</div>\n",
      "    msg_tag = soup.find('div', {'class': MSG_CLASS})\n",
      "    if msg_tag and msg_tag.get_text() == EMPTY_PAGE_MSG:\n",
      "        print(\"empty page.\")\n",
      "        break\n",
      "    \n",
      "    link_tags = soup.find_all('a', id=re.compile(VIDEO_LINK_PREFIX), href=True)\n",
      "    for link_tag in link_tags:\n",
      "        link = link_tag['href']\n",
      "        # EX: from /list/search%3Atag%3A%22chinese%22/video/The-tragedy-of-Hong-Kong-Archiv to /video/The-tragedy-of-Hong-Kong-Archiv\n",
      "        pos = link.find(\"/video\")\n",
      "        link = link[pos:]\n",
      "        print(\"video link: %s (attr Language: Icelandic)\" % (link))\n",
      "\n",
      "    page += 1"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Reading URL: http://tedxtalks.ted.com/browse/talks-by-language/icelandic?page=1\n",
        "video link: /video/TEDxReykjavik-Berghildur-Bergrs (attr Language: Icelandic)"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "video link: /video/TEDxReykjavik-Eythor-Edvardsson (attr Language: Icelandic)\n",
        "video link: /video/TEDxReykjavik-Ari-Kristinn-Jons (attr Language: Icelandic)\n",
        "video link: /video/TEDxReykjavik-Danielle-Morrill (attr Language: Icelandic)\n",
        "video link: /video/TEDxReykjavik-Deepa-Iyengar-Jed (attr Language: Icelandic)\n",
        "video link: /video/TEDxReykjavik-Rakel-Solvadottir (attr Language: Icelandic)\n",
        "video link: /video/TEDxReykjavik-Alex-MacNeil-Exit (attr Language: Icelandic)\n",
        "video link: /video/TEDxReykjavik-Daddi-Gudbergsson (attr Language: Icelandic)\n",
        "video link: /video/TEDxReykjavik-Peter-Anderson-Mo (attr Language: Icelandic)\n",
        "video link: /video/TEDxReykjavik-Iceland-Dance-Com (attr Language: Icelandic)\n",
        "video link: /video/TEDxReykjavik-Hrund-Gunnsteinsd (attr Language: Icelandic)\n",
        "video link: /video/TEDxReykjavik-Gudrun-Petursdott (attr Language: Icelandic)\n",
        "video link: /video/TEDxReykjavik-Ingibjorg-Greta-G (attr Language: Icelandic)\n",
        "video link: /video/TEDxReykjavik-Ragnheidur-Harald (attr Language: Icelandic)\n",
        "video link: /video/TEDxReykjavik-Smri-McCarthy-960 (attr Language: Icelandic)\n",
        "video link: /video/TEDxReykjavik-Skli-Mogensen-960 (attr Language: Icelandic)\n",
        "video link: /video/TEDxReykjavik-Edda-Bjrgvinsdtti (attr Language: Icelandic)\n",
        "video link: /video/TEDxReykjavik-Margrt-Dra-Ragnar (attr Language: Icelandic)\n",
        "video link: /video/TEDxReykjavik-Jnas-Antonsson-96 (attr Language: Icelandic)\n",
        "video link: /video/TEDxReykjavik-Guni-Gunnarsson-9 (attr Language: Icelandic)\n",
        "Reading URL: http://tedxtalks.ted.com/browse/talks-by-language/icelandic?page=2\n",
        "video link: /video/TEDxReykjavik-Gumundur-Oddur-96 (attr Language: Icelandic)"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "video link: /video/TEDxReykjavik-Andri-Heiar-Krist (attr Language: Icelandic)\n",
        "video link: /video/TEDxReykjavik-Kristin-Drfjr-960 (attr Language: Icelandic)\n",
        "video link: /video/TEDxReykjavik-Gurn-Lilja-Gunnla (attr Language: Icelandic)\n",
        "video link: /video/TEDxReykjavik-Teitur-orkelsson (attr Language: Icelandic)\n",
        "video link: /video/TEDxReykjavik-orvaldur-orsteins (attr Language: Icelandic)\n",
        "video link: /video/TEDxReykjavik-Mary-Frances-Davi (attr Language: Icelandic)\n",
        "video link: /video/TEDxReykjavik-Torfi-G-Yngvason (attr Language: Icelandic)\n",
        "Reading URL: http://tedxtalks.ted.com/browse/talks-by-language/icelandic?page=3\n",
        "empty page."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      }
     ],
     "prompt_number": 13
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Stage 3: Get the YouTube ID of the Video"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Since all TEDx videos are on YouTube, and we also use YouTube API to get other interesting information of the videos, we use YouTube ID as the key to represent the video.\n",
      "And because Beautiful Soup does not parse through the tag `<embed>` so we just use the regualr expression to get the YouTube ID.\n",
      "\n",
      "For example, in the video 'http://tedxtalks.ted.com/video/TEDxReykjavik-Eythor-Edvardsson' we can find its YouTube ID: 'bzF4GPguPL8'\n",
      "\n",
      "`<embed type=\"application/x-shockwave-flash\" src=\"http://www.youtube.com/v/bzF4GPguPL8&amp;rel=0&amp;fs=1&amp;showsearch=0&amp;enablejsapi=1&amp;modestbranding=1&amp;autoplay=1&amp;playerapiid=mvp_swfo_embed_V8C4K631YLWW0QF3_1299136773\" width=\"634\" height=\"382\" style=\"undefined\" id=\"mvp_swfo_embed_V8C4K631YLWW0QF3_1299136773\" name=\"mvp_swfo_embed_V8C4K631YLWW0QF3_1299136773\" quality=\"high\" allowfullscreen=\"true\" allowscriptaccess=\"always\" wmode=\"opaque\" loop=\"false\">`"
     ]
    },
    {
     "cell_type": "heading",
     "level": 4,
     "metadata": {},
     "source": [
      "Sample Code and Results"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "VIDEO_ID_RE = b\"\"\"\n",
      "<embed.*\\ src=\\\\\\\\\\\".*/v/(.*?)\\\\\\\\\\\".*>.*</embed>\n",
      "\"\"\"\n",
      "url = \"http://tedxtalks.ted.com/video/TEDxReykjavik-Eythor-Edvardsson\"\n",
      "s = requests.get(url)\n",
      "html = s.content\n",
      "video_ids = re.findall(VIDEO_ID_RE, html, re.IGNORECASE|re.VERBOSE)\n",
      "for video_id in video_ids:\n",
      "        # NOTE: byte string => need decode\n",
      "        print(\"YouTube ID: %s (%s)\" % (url, video_id.decode('utf-8')))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "YouTube ID: http://tedxtalks.ted.com/video/TEDxReykjavik-Eythor-Edvardsson (bzF4GPguPL8)\n"
       ]
      }
     ],
     "prompt_number": 18
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "YouTube API"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#https://developers.google.com/youtube/articles/view_youtube_jsonc_responses\n",
      "#https://developers.google.com/youtube/2.0/developers_guide_jsonc\n",
      "\n",
      "import requests\n",
      "import json\n",
      "import time\n",
      "\n",
      "user_id = \"tedxtalks\"\n",
      "page = 1\n",
      "maxcount = 25\n",
      "count = 0\n",
      "start_index = 0\n",
      "\n",
      "# Obtaining Total page number\n",
      "s = requests.get(\"https://gdata.youtube.com/feeds/api/users/\"+user_id+\"/uploads?v=2&alt=jsonc&start-index=1&max-result=1\")\n",
      "data = [json.loads(row) for row in s.content.split(\"\\n\") if row]\n",
      "totalcount = data[0]['data']['totalItems']\n",
      "pagenumber = totalcount/maxcount +1\n",
      "\n",
      "key = ['id', 'uploaded', 'category', 'title', 'tags', 'thumbnail', 'duration', 'likeCount', 'rating', 'ratingCount', 'viewCount', 'favoriteCount', 'commentCount'] \n",
      "tedx ={'id':'',\n",
      "        'data':{   'uploaded':'','title':'','tags':'','thumbnail':'','duration':'','likeCount':'','rating':'','ratingCount':'','viewCount':'','favoriteCount':'','commentCount':''}\n",
      "    }\n",
      "\n",
      "# Obtaining Data from each page (sample)\n",
      "for index in range(1,2): #range(1,pagenumber):\n",
      "    # changing index number \n",
      "    if index == 1:\n",
      "        start_index = 1\n",
      "    else:\n",
      "        start_index = index*maxcount\n",
      "    s = requests.get(\"https://gdata.youtube.com/feeds/api/users/\"+user_id+\"/uploads?v=2&alt=jsonc&start-index=\"+str(start_index)+\"&max-result=\"+str(maxcount))\n",
      "    data = [json.loads(row) for row in s.content.split(\"\\n\") if row]\n",
      "    metadata = data[0]['data']['items']\n",
      "    \n",
      "    # obtaining each data in a page (25 items)\n",
      "    for i in range(5):#len(metadata)):\n",
      "        count +=1\n",
      "        u = metadata[i]\n",
      "\n",
      "        #missing key-value pair\n",
      "        for j in key:\n",
      "            if j=='id':\n",
      "                tedx['id']=u['id']\n",
      "            elif j =='thumbnail':\n",
      "                tedx['data'][j] = u[j][u'hqDefault']\n",
      "            elif j == 'title': \n",
      "                tedx['data'][j] = u[j].encode('utf-8')\n",
      "            else:\n",
      "                tedx['data'][j] = u[j] if not j in list(set(key) -set(u.keys())) else '-'\n",
      "        \n",
      "        the_dump = json.dumps(tedx)\n",
      "        print the_dump\n",
      "    # delay\n",
      "    time.sleep(1)\n",
      "\n",
      "# https://developers.google.com/youtube/2.0/developers_guide_jsonc "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "{\"data\": {\"uploaded\": \"2013-05-02T08:46:29.000Z\", \"rating\": \"-\", \"tags\": \"-\", \"likeCount\": \"-\", \"commentCount\": 0, \"ratingCount\": \"-\", \"duration\": 960, \"category\": \"People\", \"viewCount\": 2, \"title\": \"Corporate rebels: Peter Vander Auwera at TEDxBrusselsChange\", \"favoriteCount\": 0, \"thumbnail\": \"http://i.ytimg.com/vi/GgdwNiOwajg/hqdefault.jpg\"}, \"id\": \"GgdwNiOwajg\"}\n",
        "{\"data\": {\"uploaded\": \"2013-05-02T06:43:09.000Z\", \"rating\": 5.0, \"tags\": \"-\", \"likeCount\": \"3\", \"commentCount\": 0, \"ratingCount\": 3, \"duration\": 1134, \"category\": \"Tech\", \"viewCount\": 39, \"title\": \"One Chance at Life - What Would You Do: Chuck Berry at TEDxQueenstown\", \"favoriteCount\": 0, \"thumbnail\": \"http://i.ytimg.com/vi/5LMMIu813zQ/hqdefault.jpg\"}, \"id\": \"5LMMIu813zQ\"}\n",
        "{\"data\": {\"uploaded\": \"2013-05-02T05:47:59.000Z\", \"rating\": 4.75, \"tags\": \"-\", \"likeCount\": \"15\", \"commentCount\": 2, \"ratingCount\": 16, \"duration\": 866, \"category\": \"People\", \"viewCount\": 130, \"title\": \"The Habbits of Highly Boring People: Chris Sauve at TEDxCarletonU\", \"favoriteCount\": 0, \"thumbnail\": \"http://i.ytimg.com/vi/3rbVQNTzCh8/hqdefault.jpg\"}, \"id\": \"3rbVQNTzCh8\"}\n",
        "{\"data\": {\"uploaded\": \"2013-05-02T05:05:34.000Z\", \"rating\": 5.0, \"tags\": \"-\", \"likeCount\": \"4\", \"commentCount\": 0, \"ratingCount\": 4, \"duration\": 924, \"category\": \"People\", \"viewCount\": 21, \"title\": \"A Selfless Good Deed: Trevor Deley at TEDxCarletonU\", \"favoriteCount\": 0, \"thumbnail\": \"http://i.ytimg.com/vi/OvZlGIT1tOA/hqdefault.jpg\"}, \"id\": \"OvZlGIT1tOA\"}\n",
        "{\"data\": {\"uploaded\": \"2013-05-02T04:24:49.000Z\", \"rating\": 5.0, \"tags\": \"-\", \"likeCount\": \"2\", \"commentCount\": 0, \"ratingCount\": 2, \"duration\": 858, \"category\": \"Sports\", \"viewCount\": 14, \"title\": \"Fishing for the Future: Dr. Steven Cooke at TEDxCarletonU\", \"favoriteCount\": 0, \"thumbnail\": \"http://i.ytimg.com/vi/Wsz8Wn76h-4/hqdefault.jpg\"}, \"id\": \"Wsz8Wn76h-4\"}\n"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Merged Results"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now that we've got the video attributes from both TEDx website and YouTube, we can merge these attributes."
     ]
    },
    {
     "cell_type": "heading",
     "level": 4,
     "metadata": {},
     "source": [
      "Sample Code and Results"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import json\n",
      "\n",
      "SITE_JSON = \"tedx_video.json\"\n",
      "YOUTUBE_JSON = \"tedx_v7.txt\"\n",
      "SITE_ATTR_LIST = ['lang', 'event', 'country', 'topic']\n",
      "\n",
      "# import JSON from TEDx website and make video_dict\n",
      "site_json_file = open(SITE_JSON)\n",
      "site_json = json.load(site_json_file)\n",
      "site_json_file.close()\n",
      "video_dict = {}\n",
      "for video in site_json:\n",
      "    vid = site_json[video]['id']\n",
      "    video_dict[vid] = {}\n",
      "    for attr in SITE_ATTR_LIST:\n",
      "        if attr in site_json[video]:\n",
      "            video_dict[vid][attr] = site_json[video][attr]\n",
      "\n",
      "# get JSON from YouTube and print to merged result file\n",
      "merged_cnt = 0\n",
      "with open(YOUTUBE_JSON, \"r\") as youtube_json_file:\n",
      "    for line in youtube_json_file:\n",
      "        if merged_cnt >= 10:\n",
      "            break\n",
      "        youtube_json = json.loads(line)\n",
      "        vid = youtube_json['id']\n",
      "        merged_video = youtube_json['data']\n",
      "        merged_video['id'] = vid\n",
      "        if vid in video_dict:\n",
      "            attr_cnt = 0\n",
      "            for attr in SITE_ATTR_LIST:\n",
      "                if attr in video_dict[vid]:\n",
      "                    merged_video[attr] = video_dict[vid][attr]\n",
      "                    attr_cnt += 1\n",
      "            if attr_cnt == 4:\n",
      "                print(json.dumps(merged_video))\n",
      "                merged_cnt += 1"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "{\"uploaded\": \"2013-04-24T08:42:45.000Z\", \"rating\": 4.6, \"lang\": \"English\", \"tags\": \"-\", \"country\": \"Spain\", \"id\": \"JcqXD5JgVXw\", \"title\": \"Wonder and beauty in education: Catherine L'Ecuyer at TEDxManresa\", \"event\": \"TEDxManresa\", \"likeCount\": \"9\", \"commentCount\": 0, \"topic\": \"Education\", \"ratingCount\": 10, \"duration\": 1087, \"category\": \"Nonprofit\", \"favoriteCount\": 0, \"thumbnail\": \"http://i.ytimg.com/vi/JcqXD5JgVXw/hqdefault.jpg\", \"viewCount\": 900}\n",
        "{\"uploaded\": \"2013-04-23T10:09:17.000Z\", \"rating\": 4.8974357, \"lang\": \"English\", \"tags\": \"-\", \"country\": \"Greece\", \"id\": \"s6KM9MxY5ZM\", \"title\": \"Learning is a Game: Ed Cooke at TEDxThessaloniki\", \"event\": \"TEDxThessaloniki\", \"likeCount\": \"38\", \"commentCount\": 5, \"topic\": \"Education\", \"ratingCount\": 39, \"duration\": 1187, \"category\": \"Education\", \"favoriteCount\": 0, \"thumbnail\": \"http://i.ytimg.com/vi/s6KM9MxY5ZM/hqdefault.jpg\", \"viewCount\": 2152}\n",
        "{\"uploaded\": \"2013-04-23T07:26:23.000Z\", \"rating\": 5.0, \"lang\": \"Czech\", \"tags\": \"-\", \"country\": \"Czech Republic\", \"id\": \"pZsORC8sgl4\", \"title\": \"Architektura jako starost o m\\u00edsto kde \\u017eijeme: Roman Brychta at TEDxHradecKralove\", \"event\": \"TEDxHradecKralove\", \"likeCount\": \"1\", \"commentCount\": 0, \"topic\": \"Education\", \"ratingCount\": 1, \"duration\": 981, \"category\": \"Education\", \"favoriteCount\": 0, \"thumbnail\": \"http://i.ytimg.com/vi/pZsORC8sgl4/hqdefault.jpg\", \"viewCount\": 89}\n",
        "{\"uploaded\": \"2013-04-23T07:25:08.000Z\", \"rating\": 5.0, \"lang\": \"Czech\", \"tags\": \"-\", \"country\": \"Czech Republic\", \"id\": \"HeSH7cKTs0s\", \"title\": \"Kdy\\u017e se chce, tak to jde... V\\u011b\\u0159te n\\u00e1m, testovali jsme to na lidech: Dan P\\u0159ib\\u00e1\\u0148 at TEDxHradecKralove\", \"event\": \"TEDxHradecKralove\", \"likeCount\": \"82\", \"commentCount\": 6, \"topic\": \"Education\", \"ratingCount\": 82, \"duration\": 1031, \"category\": \"Education\", \"favoriteCount\": 0, \"thumbnail\": \"http://i.ytimg.com/vi/HeSH7cKTs0s/hqdefault.jpg\", \"viewCount\": 2799}\n",
        "{\"uploaded\": \"2013-04-23T07:24:51.000Z\", \"rating\": 5.0, \"lang\": \"Czech\", \"tags\": \"-\", \"country\": \"Czech Republic\", \"id\": \"Bkrku3_sv88\", \"title\": \"Geometrie trojrozm\\u011brn\\u00e9ho \\u017eivota: Jan Han\\u00e1k at TEDxHradecKralove\", \"event\": \"TEDxHradecKralove\", \"likeCount\": \"1\", \"commentCount\": 0, \"topic\": \"Education\", \"ratingCount\": 1, \"duration\": 883, \"category\": \"Education\", \"favoriteCount\": 0, \"thumbnail\": \"http://i.ytimg.com/vi/Bkrku3_sv88/hqdefault.jpg\", \"viewCount\": 92}\n",
        "{\"uploaded\": \"2013-04-23T07:24:17.000Z\", \"rating\": 5.0, \"lang\": \"Czech\", \"tags\": \"-\", \"country\": \"Czech Republic\", \"id\": \"zNS7kdSMVac\", \"title\": \"Psan\\u00edm k sebepozn\\u00e1n\\u00ed: Ji\\u0159\\u00ed Van\\u011bk at TEDxHradecKralove\", \"event\": \"TEDxHradecKralove\", \"likeCount\": \"2\", \"commentCount\": 0, \"topic\": \"Education\", \"ratingCount\": 2, \"duration\": 874, \"category\": \"Education\", \"favoriteCount\": 0, \"thumbnail\": \"http://i.ytimg.com/vi/zNS7kdSMVac/hqdefault.jpg\", \"viewCount\": 243}\n",
        "{\"uploaded\": \"2013-04-22T21:18:14.000Z\", \"rating\": 4.6363635, \"lang\": \"English\", \"tags\": \"-\", \"country\": \"United States\", \"id\": \"hktzJ7QNcMU\", \"title\": \"Empowering Women and Girls: Halima Hima at TEDxChange\", \"event\": \"TEDxChange\", \"likeCount\": \"10\", \"commentCount\": 0, \"topic\": \"Entertainment\", \"ratingCount\": 11, \"duration\": 1419, \"category\": \"Entertainment\", \"favoriteCount\": 0, \"thumbnail\": \"http://i.ytimg.com/vi/hktzJ7QNcMU/hqdefault.jpg\", \"viewCount\": 173}\n",
        "{\"uploaded\": \"2013-04-20T00:51:52.000Z\", \"rating\": 4.6363635, \"lang\": \"English\", \"tags\": \"-\", \"country\": \"United States\", \"id\": \"845UrCAFTsQ\", \"title\": \"Iconic toilets: Mathew Lippincott at TEDxConcordiaUPortland\", \"event\": \"TEDxConcordiaUPortland\", \"likeCount\": \"20\", \"commentCount\": 6, \"topic\": \"Education\", \"ratingCount\": 22, \"duration\": 648, \"category\": \"Education\", \"favoriteCount\": 0, \"thumbnail\": \"http://i.ytimg.com/vi/845UrCAFTsQ/hqdefault.jpg\", \"viewCount\": 1104}\n",
        "{\"uploaded\": \"2013-04-18T09:38:39.000Z\", \"rating\": 5.0, \"lang\": \"English\", \"tags\": \"-\", \"country\": \"India\", \"id\": \"MiwjplU6kAc\", \"title\": \"Three laws of user experience: Apala Lahiri Chavan at TEDxGolfLinksPark\", \"event\": \"TEDxGolflinkspark\", \"likeCount\": \"10\", \"commentCount\": 2, \"topic\": \"Education\", \"ratingCount\": 10, \"duration\": 1393, \"category\": \"Education\", \"favoriteCount\": 0, \"thumbnail\": \"http://i.ytimg.com/vi/MiwjplU6kAc/hqdefault.jpg\", \"viewCount\": 1069}\n",
        "{\"uploaded\": \"2013-04-18T02:18:44.000Z\", \"rating\": 4.2941175, \"lang\": \"English\", \"tags\": \"-\", \"country\": \"United States\", \"id\": \"5-YIxJEyBBs\", \"title\": \"Crowd sourcing the feminine intelligence of the planet: Jensine Larsen at TEDxConcordiaUPortland\", \"event\": \"TEDxConcordiaUPortland\", \"likeCount\": \"14\", \"commentCount\": 6, \"topic\": \"Education\", \"ratingCount\": 17, \"duration\": 1149, \"category\": \"Education\", \"favoriteCount\": 0, \"thumbnail\": \"http://i.ytimg.com/vi/5-YIxJEyBBs/hqdefault.jpg\", \"viewCount\": 432}\n"
       ]
      }
     ],
     "prompt_number": 29
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<span id=\"stat\"></span>\n",
      "<a href=\"#outline\">Go to Top</a>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Basic Statistics"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now that we've merged all the information we got, we can try to discover some basic statistics of these videos."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<img src=\"https://dl.dropboxusercontent.com/u/12327764/comparison_picture.png\">"
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Load JSON Data and Convert Them into DataFrame"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pandas as pd\n",
      "from pandas import Series, DataFrame\n",
      "import json\n",
      "\n",
      "TEDX_JSON_FILE = \"final_tedx.json\"\n",
      "tedx_video_list = []\n",
      "with open(TEDX_JSON_FILE, \"r\") as tedx_json_file:\n",
      "    for line in tedx_json_file:\n",
      "        tedx_video_list.append(json.loads(line))\n",
      "    tedx_df = DataFrame(tedx_video_list)\n",
      "tedx_df.set_index('id', inplace=True, drop=True)\n",
      "tedx_df"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 93,
       "text": [
        "<class 'pandas.core.frame.DataFrame'>\n",
        "Index: 29982 entries, ew0ovccWuQg to QZkUPZr1Zbc\n",
        "Data columns:\n",
        "category         27081  non-null values\n",
        "commentCount     27081  non-null values\n",
        "country          19813  non-null values\n",
        "duration         27081  non-null values\n",
        "event            23177  non-null values\n",
        "favoriteCount    27081  non-null values\n",
        "lang             24061  non-null values\n",
        "likeCount        27081  non-null values\n",
        "rating           27081  non-null values\n",
        "ratingCount      27081  non-null values\n",
        "tags             27081  non-null values\n",
        "thumbnail        27081  non-null values\n",
        "title            27081  non-null values\n",
        "topic            13332  non-null values\n",
        "uploaded         27081  non-null values\n",
        "viewCount        27081  non-null values\n",
        "dtypes: float64(1), object(15)"
       ]
      }
     ],
     "prompt_number": 93
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Statistics by Language"
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Number of Videos by Language"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Conclusion?"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "tedx_df['lang'].value_counts()[:10]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 94,
       "text": [
        "English       17479\n",
        "Spanish        1388\n",
        "Portuguese     1002\n",
        "Korean          654\n",
        "French          559\n",
        "Arabic          471\n",
        "Russian         397\n",
        "Japanese        289\n",
        "Italian         253\n",
        "Polish          158"
       ]
      }
     ],
     "prompt_number": 94
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "tedx_df[tedx_df.lang!='English']['lang'].value_counts().plot(kind=\"bar\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 95,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x18f04610>"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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z5+Dq6loerhmGYSot5RLg33jjDQAlPWkyMjKwZ88euLi4lIdrhmGYSku5pWiW\nLl2KcePGobCwEJMnT8Z//vOf8nLNMAxTKTGZWjT/Fjdu3MDff/+N58+fAyh52Dt8+PB/RUthYSFO\nnjyJ/Px8oZ5I165d1ewyMzMFvQBgaWlZnjINQsrxff78OWrWrFmmPqQg9fiX9Tb+DV61Tenb7wMH\nDmjsSFGex+bJkyeoW7cusrM11+5v0KD8ukmuX78ew4YNww8//KC2TCaT4bPPPgMAnDlzBm3btjXa\nj8k8ZFWQnZ2NHTt24OjRo6IfbFRUlGCTn5+P33//HQcPHsSPP/6IS5cu4cKFC+jTp49B25k1axa2\nbdsGNzc3VK9eXZivHByePn2KWrVqoUqVKgCAoqIiPH/+HLVr1xZs0tPTsX79ejVf+/fvl6QVAMLD\nw/Hdd9+hdevWIi3KP4CYmBjMnj0bVapUEdmcOXNG7Thq+8Gmp6ejWbNmItukpCQ4OTmJ5t25cwf7\n9+/H0KFDkZWVhadPn4rW27t3LxYtWoSTJ0+iqKhI2OcnT55IPr4pKSmYNWsWUlNTkZ6ejpSUFKxc\nuRIRERGCbWFhIY4ePap2bL/++mtJPqQeFynHX58WKdsAgL/++gs9e/YUzVu+fDnGjx8PAEhOTsay\nZcvU/Fy9elW0jr6gKuV/pK9Nvf/++4iNjUW9evUAlPyuBg8ejLi4OMFWyn5/9913QoDPzs5GYmIi\nPD09sWfPHuhiypQpCAsLQ9++fdWWyWQybNu2TTRv9uzZ8PDwgJubm+g3CgCDBw/Gzp074ejoqPFk\nk56eLnzXd+x0xZc6depo7RWo2EZubi4AICcnR2T7T6G4EoKDg5Gfn4+RI0di6NChQrpbKiZ3BT9k\nyBDUrl0b3t7eqFatGoCSg9K/f3/BZubMmSAi7NixA+fOncOzZ8/g5uaGU6dOGbSd1q1bIzk5GTVq\n1NCqx8XFBfv27UOdOnUAlPxDevTogb///luw6dOnDzp16qTmq0OHDpK0AoCdnR2OHj0Kc3NzrVra\ntWuHnTt3okmTJlpt9P1gHR0dsW3bNlhYWAAoubKaOHEizp49K9iuXLkSv/zyC27fvo2LFy/i1q1b\n+Pjjj3HkyBHBpmPHjggLC0OnTp1gZqb5UY6+4ztw4EDMnTsXw4YNQ3JyMgCgTZs2OHfunGAzfvx4\nZGRkwMPDQ7Q/06ZNk+RD6nGRcvz1aZGyDQBwc3PD/Pnz0a1bNwDAt99+i/3792PXrl0AAA8PD4wd\nOxZeXl6hBxquAAAgAElEQVQiP8ppTW1Bdfv27cJ3Kf8jfW2qffv2am21Xbt2OH36tDAtdb+VOXv2\nLEJDQwEAsbGxGq9SZTIZ1qxZgw4dOmitw+Lp6SmajoqKwqFDh3Ds2DHUqVMHXbt2hbu7Oz766CPJ\n2gD9x05KfCktLl68iKioKMTGxsLZ2RkjR46Ej4+PtJXJxGjdurVeG2dnZyIisre3F+a1bdvW4O0M\nGjSIzp8/r9OmXbt2avPs7OxE06q+DdVKRNSzZ0+6ffu2Ti2enp708OFDnTZt27al69eva12emJhI\nHTp0oDt37tDOnTupXbt2avZdunSh/Px8nZo7depEeXl5OrXoO75ubm5E9M+xef78OXXs2FFkY2tr\nS0VFRUb7UKDvuEg5/vq0SNkGEVFWVha5uLjQwYMH6auvviI/Pz/Kz88Xlnfo0IFevHihcxtt2rSh\nJ0+e6LSR8j/S16aGDBlCx48fF6aTkpLo448/FtlI3W9l8vPzydbWlm7dukVEROnp6Ro/xnLnzh1a\nunQpWVhYUO3atYmI6MSJEzo/yug7drriy+PHj4mI6MGDBxo/yuTn59OuXbvo008/pcDAQBo5ciSN\nHDlSbZuFhYUUGxtLb7/9NtnY2JCdnR3t2rVL73EwuRSNv78/Vq9ejaFDh2rNy1pbWwujYwHg2LFj\ncHBwkLwdxe1eXl4e2rZtC2dnZ9SvXx+A+m2fi4sLduzYIaRUtm/frtYDaMiQIZg7dy6GDx8ubAco\nyelJ0QoAdevWhb29PXx8fITbYZlMhvDwcCFPZ2tri65du+LDDz8U2SjydQDQsGFDnVdSTk5OCA8P\nx/vvv49atWphz549aNSokcjmjTfeEF21XL9+XbjiV6C4Kho4cKBIi5+fn+Tj6+Pjgz/++EPwsWzZ\nMnz44YciP15eXoiPjxeudlXJysrS+z+Uclx0HX+pWqRsAyi5Et+2bRu6deuGjh07YtOmTaLb8r59\n+2LMmDEYOnSoqD05OjoK3y0tLfH06VON+7R582YAJSkSbf8jBTY2Njrb1OTJkzF06FA0bdoUQMlo\nyvXr1wMAJk2aBKCkvejbb4UtUJJiPXbsGPr164d33nkHAGBlZaXxmCqQmrYaNWoU0tLS0LhxY3Tp\n0gWbN28Wfm+fffYZZDIZCgoKcPToUVhaWkImk+HatWtwc3PD4cOHhe3oat+A7vhiSCpo9uzZyM3N\nxZ9//okpU6Zg48aN8PLyEpafOnUK0dHR2LFjB95//33s2LEDjo6OuHbtGnx9fZGWlqbzuJlMikY5\nb/Xs2TNUrVpVuO1WzRsmJSVhxowZOHPmDOzs7HDv3j2sX78eHTp0EG0vNzdX43YUt3uaCuXLZDJ4\neHgI06mpqZgwYQIyMzNBRGjUqBGWL18OW1tbwcbKykrrP1KKVgCIjo5WW18mk2HEiBEICQkRtk9K\nOTrF97lz5wrrBAcH48iRI2o/2Pj4eNG2U1NT8c4776BevXpqATE2NhabNm1CYmIiAgMDsXnzZoSE\nhIgCQ2BgoLBtZdasWaOzrKny8X348CHCwsKwZcsWFBUVYciQIfjkk0/wxhtvCLfsxcXFSEtLw7vv\nvivaH0WKQN+tu+LkeOXKFRw+fFhrINN1/BW0bt0a58+f16pF3zZUc7MFBQWoVq2aMDxd0cY9PT01\ntifl/6G/vz/i4+M1BtXAwECN7UXBmjVrhO8hISHCusr2ym0KKPnNARA9q4mOjhatp22/VY9NrVq1\n4OrqKpw0AP05bylpKwDo168fbt26hTZt2qBr167w8PBA8+bNRTb+/v4YM2aMcKLev38/Vq5ciZiY\nGMFGV/sGdMcXQ+jQoQOOHz8OOzs7nDt3Dg8fPkSPHj2QmJgo7PeoUaMwYMAA/L//9/9E665bt05v\nZwKTCfDGcOLECRQXF6s9IJTK1atX8fbbb6NWrVoASq447969q/YQEgDu3r0LmUyGxo0b/ytaNaGp\n94m2H6zySUvK8oyMDGzevBnFxcXw9/fXmffXhvID6nv37uHKlStwc3OTtK6+uhv6rvgUaDs5KlAN\nZMZokqqlNJFyQnoV0tLSYGtrixMnTmg82SjfTShTWFiIu3fvGtxe9OW8O3bsiISEBKGzgxT9u3bt\nwtKlS1FUVISbN28Ky1Sf2+Tn58PR0VH07Ke0ePDgAY4dO4b8/HxhnvKFkrOzMxITExEQEIARI0ag\nZcuW6NOnj+iZ2KtgcgH+yJEjaN++PerUqYMdO3bg9OnTGD9+vKgL0+HDh2Fvb6/TRsGZM2fw8OE/\nFemUn+x36NABR48eFa4I8vPz0aVLFyQlJWHfvn3o1q0bNm/erLGBK/+TgJK7jv3794t8DR8+XLLW\njIwMrFixAnFxccI2VG9BhwwZguXLl6N27dpwc3PDnTt3EBISgqCgIEnHVkFBQQGOHTuGrl27Ijc3\nFy9evEDdunVF+1KzZk2dgbmgoADx8fGCXsUxUu6l5OjoiMOHD+PFixdo164dbGxsYGNjg6VLlwKQ\n1tPpypUrePfdd1GzZk2kpKQgNTUVH3/8MapWLckunjp1CkuWLMHu3bvx6NEjFBcXo06dOgZfSUk5\n/goeP34sSrspeuIYsg1Ad9u8cOECdu/eLVqu6K0jlREjRiAsLEy4wn/48CGmTZsmOr7Z2dmIjY1V\n0/zee+9h1apVku4mPD09sW3bNtSoUQN2dnaoUaMGAgICMHPmTNHDU9U7ZuW7Hzc3N+zfv19rWjY0\nNBTXrl3TmbYCSlKohw4dwqFDh/Do0SO4urrC3d1d9BuZP38+UlJSMHToUBARYmJi0K5dO8yZM0ew\nkdK+Ad3/w5CQEPz2229wcHAQ3XUo30GtWrUK/fv3x9WrV/H555/j9u3bmD9/PgYNGgTA8Dalht4s\nfTljZ2dHxcXFdPXqVbKzs6PFixeTn5+fwTZbtmwhBwcHeuONN8je3p5kMhm9//77Ihvlh4hERMXF\nxcLDxK+//pqIiEaMGEGBgYFqH2VWrlxJLi4u9Oabb9JHH31E5ubmNGTIEMlaiYiGDx9Ov/76K7Vt\n25aSk5NpwoQJtHjxYpGN4oFvbGwsBQcHU15envCgUsGDBw9o+fLl1K9fP/L09CRPT0/y8vISlm/e\nvJkcHByoefPmRER04cIF8vb2Fm3DwcGBnj17Ro8fP6amTZtSjx49aMqUKSKb6dOn08SJE6lZs2a0\ndOlScnFxoZkzZ4ps2rdvT0REy5Yto9DQUCIicnJyEpYPHjyYRo8eTb/88gvFxsZSbGwsbdq0SW2f\nCwsL6d69e9SiRQsaN24cDRs2TFjev39/OnbsGNnb29P9+/dp8eLFgi9lunfvLnqY+ODBA/Lx8THo\n+MvlcvL09KTatWtTw4YNSSaTUZs2bQzaBpH+trlw4ULq27cvvfvuuzR16lRq1qwZTZw4UbSN9PR0\nmjlzJjk4OJCVlRVZWVlRs2bNNB5/1eOpTHBwMC1ZsoSsra1p69at9NFHH1FISIjaerpQbHPNmjU0\nffp0Ki4uJhcXF0Fneno6zZ07l4KCgig+Pp7i4+Np1KhRIj9ffPEF9ejRg3766SfatGkTbdq0iTZv\n3iws9/DwENqz8keVCRMmUExMjPDwVhP5+fm0efNmGj16NI0ZM4a2bNkieshNpL99S4kvrVu3Vtuu\noUhtU9owuQCvCLpz5syhiIgIIiJydHQ02MbLy4seP34s9Hg5fPgwDRgwQGTz2Wef0Y8//kgFBQWU\nn59P//vf/2jq1KkGa+7UqRPl5+cLT9YvXLgg/LOlaFW2a9euHRUUFFBBQYHaj9HV1ZWePXtGH3zw\nAR05coSI1Hu36PvBduvWjZ4+fSo6uan2CtIXmBX7UFxcLOxzdna2mo23tzft3buXOnbsSFeuXFHz\nJaWnk0LLN998Q9999x0RkainjYODAxGV9DzJy8uj4uJiUdBVoKk3lPKxk3L8e/bsSdeuXaN27dpR\nUVER/fzzzxQcHGzQNoj0t82OHTvSixcvhONz8+ZN6ty5s2gbUn74H3zwAV28eFGYvnDhAvXq1Utk\no9BsZ2dHRUVF9OzZM3J0dBQCrLaPMu7u7nTlyhXy9PSkU6dOqR1bopL/dUFBgTBdUFAg+j+NGDFC\n48WUMeTn59OBAweIiOjZs2d6extpQl/7lhJfxowZQ3K5XKefgoICOnDgAH3zzTcUGhpKISEhogsU\nqW1KGybXi8bKygpz5sxBbGwsEhISUFRUhIKCAoNtHj9+jLp166JRo0bIzs5G586dMXr0aJHN1KlT\nMWfOHCxZsgREBC8vLyxcuFBk8+jRI6xevVroo9yzZ0+MGjVKNOCgsLAQ1atXh5WVFW7duoX33nsP\nN27ckKwVKHnwVFRUBA8PDyxatAjNmjUT+t4rmDRpEhwdHdGxY0e4ubkhIyNDbeDD0aNHERERgfXr\n1+ODDz6Aj48P3N3dhVyzTCYTPazJyspCw4YNRdto2LAh9u3bh7Vr1+LXX38FUPJ8QpkqVapAJpPB\nwcEBe/bsQcuWLYXBGwp++OEHLF26FKNHj0bz5s1x5coVUQ8BKT2m3n77baxevRobNmwQBsUoa6lT\npw7y8/PRrVs3TJw4EU2bNhV6ZihjZ2eHEydOCA+3jx8/LnpQLuX43717F5aWlqhduzaePXuGIUOG\niEpeS9kGoL9tymQyVKlSBTY2Njh79iysrKzURl+ePn0aa9euxcKFC9GmTRssXboUHTt2xMyZMwWb\nCRMmoGfPnujevTuICHv37kVkZKRoO4o8tKurK6Kjo9GiRQsQEbZv3w6ZTIZHjx5h165dcHFxgUwm\nw7Fjx9CzZ09RinLOnDkICgpCly5d0K5dO1y5cgUtW7YU+bGxscHvv/+OAQMGAAD++OMPWFtbC8s1\nPVNQRUraasuWLViwYAEeP36MK1eu4ObNmwgODsa+ffsEGyk9cvS1bynxJTg4GF27dkW9evU0PpQH\nSn7TirEVqgOzAOltSiuSTwXlxNOnTykqKopOnjxJRETXrl2j6OhovTZr164V2Xz00UeUnZ1NERER\n1LZtW/L29tbYv5SIhDOjJqZMmUKTJk2ipKQkSkpKosmTJ6ulK8aPH0/Z2dn066+/UrNmzahVq1b0\n5ZdfStZKRJSQkEBPnjyhe/fu0dy5c2n06NHC1ZA2iouLqbCwUDRPcWs8evRoWr16NR04cEC4yiUq\nSSd99tln1KpVK4qOjiZvb2/66aefRNtITk6mESNG0PLly4mI6PLlyzRp0iSRzcqVK+nBgweUlJRE\nHh4e1LJlS4qJidGpV5XatWuTTCajatWqUZ06dahOnTpkbm4usrl+/Tp9/fXXtGPHDiIiunLliuhK\nNT09nXJzcyk3N5fWrFlDCxYsoBs3bqj5OnbsGFlbW5OPjw/5+PhQq1atKCEhQVgu5fh369aNnjx5\nQvPnzycfHx8aOXIk9evXz6BtEBF9+OGHOttmaGgoZWdn0+7du8na2preeecdCg8PF22jU6dO9OLF\nC5o0aRKFhITQ2rVr1dJ1RCVXsL/99hv99ttv9OzZM7Xl27Zto4cPH9LFixdpxIgR1L17d9q/f7+w\n3MfHh86dOydMp6amilJbUjl//ryQdnr33Xfpgw8+oAsXLgjL9fUHl5K2IpJ2h9q1a1fasGED3bp1\ni7KysoSPMvrat5T4oviNXbhwQWvffn1jK4yJC8qY3ENWqeh7UKjM1atXcefOHXTu3Fk0X3noufJw\nb+WrAhsbG5w7d05UqqBNmzai8sfK5OTk4OHDh6JaHoZo1YRy3QpND6qU+8Fv374d7u7uyMrKwsKF\nC3Hr1i189dVXwpUzEeHAgQNCD5khQ4aoHRcFeXl5Qg8jQzB0eHl5oqm7n1SUewXJ5XLcunULH330\nkcYrL6lcvXoVt2/fRpcuXTQuJyLk5+er3eEkJibC1tYWeXl5iIiIwK1btzBp0iS0a9dOsBk2bJjQ\nZ13XPF20a9cOhw8fFtrrkydP0KVLF5w+fRpLlizBjBkzMGnSJI3tUtEPvqioCOHh4fj000+F3iSq\nI4+/+OILjf3BFy9eDKDk/3Xs2DG0a9cO586dw61btzBo0CBR33WgpLTC7t274ejoiOTkZGRlZWHg\nwIGi7rSG9sjRh7b/obOzMw4fPix6wKrKxIkT4efnp3VsxatiMimazp0748iRIxrrOKj2L5VyGwaI\n66mYm5ur1WHRd3sEAP3790d4eLjQ/Wz9+vXCcGRFV7KTJ0+qrXf//n04Ojrq1SolGEqtWwH8M4ir\nXr16WrvSeXp6wtLSUq1/sAJdNWI0FUlS/LgVJxtF31zFEH5V/8okJCQgPj4eM2fOxPXr13H37l04\nOztj4MCBOoewW1tbIzY2FnZ2dhrbi/JtsC5fP//8s+STkfKtsfIQeUNPaJMmTcLgwYPh5uaG5s2b\nC/8HQ3puOTs7AwDMzc2FrrGqqHa1y83NRWpqKgCIgrMmzYrgPGbMGPj6+mLAgAEgImzduhVjx44F\nUNLdECjpjaYpwCuoUqUKfv75Z0ycOFFrSYl9+/bh+PHjiI+Px5QpUzB8+HD06NFDtD19aSsA+Pjj\nj/H5558jNzcXa9euxbp16zBs2DCRja6BZPra9+jRo9UKlilSMNnZ2aLecYqBZgMGDBBSqYrBUm3a\ntIGZmRmKi4sRGRmpNrZCeYyAKoZcJJlMgFfUOXn69Kle24iICBw6dEg4Y7Zq1QqZmZkiG+V6KkOH\nDkVBQQECAgJE9VQOHjyIs2fPaux3qzrw6vPPPwdQElRr166NhQsX4r///S9WrVoljJBTJT4+Xq9W\nRePTFAwVjBs3DgC0/pCVuXnzJn799VfhrgQQNwi5XI4ZM2bg3r17yMjIQHJyMubOnStqMAsXLsSS\nJUsEbfb29jhw4AAASDrZKPLc5ubmagO6duzYIXxftGgRzpw5g5SUFMycORN16tTBhAkTcPz4cYSF\nhQEQ11ZRRnFVtHPnTklvA9Pma8WKFQB0H399xaMUXQY///xzjQN+VOnQoQMWLFiA8+fPw8/PD/7+\n/ujYsSMOHjyIbt26CflvVfz8/CSdTBYtWoTFixcjLy9PNNL1zTffFAK61OA8adIkdO7cGX/99Rdk\nMhmWLVsmjAxVaFAMCtKFj48PAgMDMWTIELzzzjtCe1F0c9SX8+7bty8ePnyI8ePHY8CAAcjJyRE9\nb1AwevRoHDhwAAUFBUhMTMS8efPU7lDj4+Mhk8mwYMECtfn62rcho1Tv37+PRo0a4dChQyIbPz8/\n3L59GykpKVrbrjHvX9WI5GROOXPv3j26du2a8FGme/fuVFxcLOTZMjMzycPDQ2QjpZ7KhAkTaO/e\nvWWzAwZo1ccnn3yi9aOaG/f19aWQkBDavXu30CVN+Ul+r1696O7du6LjotrrREqNGCk4ODjQ6dOn\nhelffvlF1BPB1dWVioqK9Nbp0UZhYaFaF09tvKovKVoUXWOlcv/+fVq5ciV5eXnRe++9J2kdRV0Y\nxf9W+aPaY2PGjBkG6TGWq1evUmhoKPn6+mrsmktEGrs4KndzNPSZjqY6MYWFhWRra1t6O1aGqHbR\nLitM5gpegZSSuFJuw6TUU4mPj9d4e6Tp9l7XgIbY2Fj06NEDdevWRUREBFJSUvDFF1+gRYsWerXq\nqvWs0KK4ygI0DwlXJisrC3PmzNFaPfDp06ei0bg5OTlqzwOk1IiRMkhp06ZNGDBgAH755RccOnQI\n69atE5WHtbCwEPUoSktLQ6tWrQDov2p+8uQJqlatCplMhoyMDL2jSXX5AqTXOgE0D3SqWrUqMjIy\nkJWVhTfffFOnFgWXL1/G+fPnce3aNeGKGgDCwsIwcuRI1K1bFzNmzEBycjLmzZsHV1dX4Y4oJSUF\nU6dOFW1v6dKlohHJPXv2xMGDB9X8KrddXaWuAWklhydNmoROnTrh66+/FlVWBP4pFaGo5SSTyWBv\nbw8PDw9RDnzMmDEASuo3aSs/oaj7rzwqVHmoftWqVWFra4vk5GSN9Z5Un2UpIKX0ogJ97Xvr1q3w\n8vIS4sajR48gl8tFVSt1DZbKysrCf//7X41X8MpaXnWgk8kF+EWLFiE+Pl7nUGcpt2EjRozA0KFD\n8ejRI4SGhgr1VJT5888/9erZunUr5s+fj6tXr6JZs2Y4deoUunfvjt27dws28+bNw8CBA3HmzBms\nW7cOU6ZMwdSpU7Fjxw69WrWlIJRRvQUuLCwEAOHHpMysWbPw6aefimquAP+M+Pvwww8RHh6OFy9e\n4ODBg1ixYoUwak7B5MmTERYWhqKiIvTs2VOoEaPMJ598orFcqjLNmzfHxo0b8dFHH6Fp06aIi4sT\nddEcN24c+vbti8zMTIwcORKHDh3CqlWrAPyTqlu0aBGeP38ujESMjo4W5XHr168PR0dHeHt74+23\n3xZ0qBb40uULKOkyO3bsWCxYsEDrQ7EDBw4gJCQESUlJqFmzJrKzs9G6dWsh192mTRu4u7ujT58+\nIi3KgQMoeaC4detWNG/eHP7+/pgzZ47of7V69WpMmTIFf//9N1JSUhAaGoo5c+aITo5r165VC/Cq\n86TUYNcVnIGS0tz6Sg5fv35dlHpTRlOqY/ny5Zg4cSL+97//4fbt2xpz3gpsbW3h4eGBhQsXSqr7\nn52djY4dO8Le3l7oLmvMsyx97TskJAT9+vUTpuvVq4eQkBBRgNdVSKyoqAg5OTkaj5kyc+fORe/e\nvbFz505s3boVq1atMqgMhMn1ovHy8sLWrVtFDd5QiAg3btxAcXGx3noq+l5s4e3tjd9//x2dO3fG\nmTNncOTIESxduhSxsbGCjaOjI06ePIlp06ahffv2GD58uDCvNLly5Qq++uorHD16FEDJ8O5FixaJ\nHpZ+8803WLJkiVqdcEWe+Pnz54iJiRH1ohkwYIDeeuqqqNZtV0b1riQzMxP16tVD9erV1e6QcnNz\n8ddff6G4uBh9+/ZV6y1iY2ODtLQ04cdVXFwsFP0CDKvJosuXlJ4VvXr1wvLly9G3b18kJycjJiYG\nhw8fFl5QonwBofxgTrXezfLlyzFgwACtr63s0KEDTpw4gfHjx+P9999H//794eDggOTkZGzcuFG4\nI3J3dxfWycrKQosWLbBhwwat+hU12JXbrmptd1X0lRAAStpcXl6exmqq2rh48SK+/PJL+Pj4YNy4\ncaKaQcrcuHEDmZmZuHz5sqS6/8pX/8r/A9VaS/rQ1b6Bkiqz8fHxwgVLbm4u3N3dceLECbx48QJV\nq1bVWUhM8f/Uh8Kuffv2OH78OICStqpao18bJhfgtVVDVL4K0lQMTPm2hYjQrl07jW86UkbKiy0U\nP7Zu3bohNjYWDRo0gK2trahM58iRI/HixQskJiYKB97FxQWnTp2SfOsvpabKqFGj4O3tLVxxx8bG\nYu/evVi9erVg06JFC6SkpGgcDPHixQv06NFDrbeRKlLSL/Pnz8c777yjcZCS4gGR6sM7BYp0inJv\nEm2MGjUKNjY2CAoKAhFh7dq1SE1NFe2zFIKCgjBp0iTRrXtISIgQlKXUOlGctN3c3BAXFwdzc3O1\ntiCVtLQ0bNu2DTKZDB988AFsbGyEZTNnzsTff/+N7OxsnDp1Cs+ePYOXlxdOnDiBa9euIT09HTNn\nzhQG6AFA06ZNNf4ulCkoKIC9vb3QkwbQH5xnzJiBU6dO6Sw5bKWjmqoupAa5WbNm4cqVKwgNDRUN\njtJGcXExjh49CplMBldXV+HOQ7nHkK5unYDu9g0A33//Pc6cOYPg4GDhrsTOzg7Tp08X2omuQmJS\n993NzQ2HDh3Cp59+ioYNG6JZs2ZYsWKFKEbpwuQCvJTypffv3xe+Z2dnIzo6Gubm5vjyyy+F+WPH\njkXv3r3VcsfKuLu7Y9++fXBxcREOtuoVzUcffYQ1a9YgJiYGkZGRePPNN9G0aVNRsCMiyOVy2Nra\n4q233sKdO3dw5swZ+Pj4SC5zOmDAAEyfPh3jx4/H3r17sWrVKhQUFIj65Nvb2+PkyZNCgy0qKkKH\nDh2QkpIi2PTv3x/ffvst3nvvPY373L17d/z00086c9ZS3lajr1yqosCYcjBRJTo6Gr/99ptabxJl\nbt++jW+++UZ4RZyvry9mzpwppECk5ijfffddNGzYENOmTROu7pV/ZFKKanXv3h1bt25FWFgYDh06\nhHfffRePHj3Cli1bAGgv3KXIZyv46aefsGrVKlHXw1GjRolGQl69ehUWFhaoXr06Hjx4gFu3bon6\nuEtBUw32vn37ikZr6wvO+srmGkNhYSE2btyIkydP4u2339bZXVOhIy8vDwcPHtRb93/Xrl0YN24c\n2rZtC5lMhjNnzmDFihXo0aOHUN6YiDB37lzMmzdPCPKqd3362ndubi5+++03bNq0CUSEAQMGwN/f\nH7Vq1RLa1U8//YT+/fvjypUrmD59Om7duiUUEnvw4IHaCHJNSBnvoAuTC/DGUFxcjPbt24uu2G1t\nbXHhwgU0bNgQb731FgD1B6h9+vTB77//DicnJyQnJ+P69esYP3681ty8tgENuioeSh1UoTjrd+zY\nEYcPH0aNGjXQtm1bUV/mOXPm4PHjxwgMDAQRYf369TA3NxcNl+/WrRsOHz4MZ2dn0RWX4ocwcOBA\n7Nu3D15eXqIcpfLVi77bU6n0798fs2fP1vjAS5kHDx5gy5Yt2LhxI65fv47Lly9L9jFixAj07t0b\nCxYswLp164QcpWoXOgcHB8jlcgwdOhSWlpYICwuDs7OzpKsoBcpVNjUNdJowYQKsrKwQFRWFb775\nBmvXroW9vb1aiqZz587YsWOHEKgePnyI3r17i14DqW18gAIpd3zKAU1TDfbS5ObNmzhy5IjaA1DV\ndB0R4dGjR/Dy8sK8efNw9uxZ9O3bV6RVgXJ/cE13g5pSL87Ozti4caNwgXP16lX4+/sL9dUVSL2C\nNgYLCwt89tlneh+glgcm95BVylWQco3q58+f48CBA2oN96+//hK+a0sV6HsQq3oVqjwoRRk/Pz+c\nOBUroe0AAB3nSURBVHECmZmZGDhwILp164Zdu3Zh3bp1kt7OA0irqTJ9+nRER0cLdyp9+vRRyzV/\n/fXXOnva9O7dG71799baQwWQViNGga7eRboeeCmjrTcJUHIl+e233+LYsWNITk7G6dOnsW3bNsye\nPRuAtJosCt544w1s374dISEh8PLyEvWEycnJwYYNGwRtH374IQICAkSprnnz5mHJkiUA/hnoNGPG\nDGGevjpACurVq4cHDx4I7SE7O1v0zGnRokU4e/YskpOT1cYHKJg/fz6mT5+OtLQ0XLhwQbjjUyYw\nMBA5OTkwMzNTG8gndVCVlLK5ul58rtqJQCaTwcLCQrjgUaSV9PWl/+KLL/Dtt9+qzVMN8FWrVhX1\n/Tc3N3+lEauq7Xvz5s16xyFIfYCqi759+2qNWxVyoJOC2bNnw8rKCqmpqaKrIGWmTZsmNLSaNWui\nU6dOWLZsmcjGysoKT548EQZo9OzZU/SPJyK4uLjAyclJeOCo+vJhfd2uFMhkMlStWhVr1qzBuHHj\n8PnnnwtD4XUNqlBm/fr1KC4uRmhoKGJiYnDr1i3hR1RYWIi4uDgcPnwYPXr0wCeffKKxR8OLFy8w\nfvx4jTnh33//HZcvXxYGbDk7OyMrKwsA1H44S5YsQW5uLoKDg7W+rUZK7yJ9L9PQ15sEKEnZDRo0\nCMeOHQNQ8gB38ODBQoDXV4zp0qVLuH37Nj744ANhP0JDQ2FmZiYM3gJKcqpZWVnCbfvatWvx3Xff\nCS+GBoDdu3cLwVzBnj17hHnaCnep8tlnn8HX11codnb+/HlhwBVQ0rPqyJEjQpfIBg0aqAXvq1ev\nwsXFBVWqVEHt2rUxY8YMtG3bVjjBh4WF4dtvv8XDhw9BRPjPf/6D6dOnY/LkyZDJZJIGVQH6XykH\nlLQFbQ9A9XVfVaDvwk6554+CvXv3Ct8VvXDatm2LLl26oGfPniAixMXFqb2YWwra2veiRYsA6B4Y\n99Zbbxn0IhlNHDt2DBYWFhg8eLDwilDldJJkyqZ7vfFoK19qKFu2bKFWrVrRhAkTKDg4mKytrWnL\nli3C8uLiYrUiRJrw9PQkMzMzcnR0pD59+lCfPn2ob9++IhtfX1/66aefyM7Oju7cuUNE6oOH9LF0\n6VKt8z7//HPq1asXff/99+Tp6Uk//PCD1u34+fkJhc2UcXFxoUuXLgnT7du3p/v379O1a9fUBqVI\nQUq5VH1ERkaqFXlSxdXVlYj+aRcvXrwQDRLRV4ypV69edPToUbXtJiYmUu/evYXp9u3biwq3FRYW\nCqWKIyIiyM7OjmrVqkV2dnbCx9LSkqZPny6so69wlzJFRUV05MgR+vvvv6m4uFi0bMCAAZSXlyfs\nZ2pqKvXv319k4+7uTs+fP6cvvviCgoKCKDQ0VChRvXr1anJ1daUtW7ZQTk4OPXnyhDZt2kRubm60\nevVqbYdaI1LKQkt98bkutJW5lnrs586dSyEhIRQSEkJz584VphV/iUqK2ymK2lWpUkX4rqnI3au0\n79IYxFRYWEh//vknDRs2jOzt7WnWrFl09uxZg7djcgFeXzVEIqLvv/+efvjhB9FH0ZgVeHl50c2b\nN4XpW7duqQWyMWPG0O+//65Tj/Iowfj4eAoNDVUbLaev4uH58+cpPDycQkNDhY8qmhqFYp6jo6NQ\n7fLhw4fUtWtXrXq1nZBUNU+YMEH4rvjBpqamEpH2t88rozjpent7C2+Kt7GxEdko/6CqVatGMplM\n7YeUmppK33zzDS1ZsoTS0tLU9ufzzz+n48ePk729PT1//pz+7//+z6ARmrpqziufhEeOHEkxMTFU\nXFxMRUVF9NtvvwnVAR89ekTp6ek0aNAgysjIEKoC5ubmStZBVDIKVfl4Hj9+XDRPwZ49e6h79+70\nzjvvUGBgIL333ntqJwpdVTQ7duxIu3btUvO/Z88e6tChg9r88+fPU1hYmMb2qWgbQ4cOpd27d1N6\nerraxYu3tzdVq1aNOnfurPUiSB/aLuy0HXtNI1mVMfR/o4q29q18klH9KEZG379//5V8q/L8+XNa\ns2YNNWzYkJYtW2bQuiaXopk1axYePXqEL774AgsXLsTGjRtFgyAA4Ny5c9izZ49Q53r//v1wcnLC\nV199hdmzZ2Po0KEAIEpjmJmZqd0uHzp0CD/99JPOB7Genp44efIkNm7ciN9++w3NmjVDcHCwaDtN\nmjQR3co3b95cyAEvWrQIx44dw8mTJzFw4ED88ccf6NWrl2Cr6Necnp4uyutlZWWhTZs2AEoeIit6\ns9SrV0/n6+g03RrKZDIEBQXhzp07Qu+TH3/8EUBJLxVFqkZKbR0FlpaWePjwIQYMGABPT0+8+eab\n6NSpk8heua5Qbm4u1q1bh7t37wrzVHuTjBw5Uq03ydSpU/H111/j7t27aN68OXr16iU61qq5SplM\nhmbNmqFXr17w8vJCXl6extGlWVlZePbsmTD95ZdfYsaMGaIU1jfffAOgJHf/xhtvCC9lVoxkVRw3\nReVQ1aqKylqsra1FqUVNKI5v9+7d4ebmJvTZj4yMVHsWokh93Lt3D76+vkL7Vejr3r272va9vLzU\n2o6+9jlmzBhkZ2dj6tSpolfKKaP8qjtj0ZbeUhz7BQsWoHHjxkJHhr///lv06kYFugrlGYK29i3l\ntYlSesdI4fnz59i5cydiYmKQkZGBKVOmiAZXSaJUTzXlRJcuXUQ1v2/evEldunShe/fukbu7OxGV\nvNbO2tqaJk2aRJ988gnZ2NhQbGwsEZFQ2yY9PV10VaBcr/n8+fM0d+5csrGxIXd3dwoPD6cmTZpo\n1GP18pVpyh/F69P0vZ0nIyOD4uPjycXFRbhLiI+Pp6tXrwo2ZmZmottJ5dtL1StiIvU32jx+/JhG\njRol1KhXUFxcTF9++SUFBQVJP/gauHLlCh0+fFiY1lZbn4hEdxJubm6UnZ0tTGdnZ1OnTp00rldY\nWEjPnz9Xmz9jxgzq1asXRUdH05o1a6h3794UHBxMH3/8Mc2bN48CAwPVXiVIRDRr1iwaMWKEaB+I\nSo6d4jVrinkK9L2yb8qUKeTo6CikBjp06ECBgYHUpUsXCgsLo4SEBLp9+7Zgv3PnTgoICKAff/yR\nnj59qqbx7t27lJGRobEe08mTJ8nFxUW4enR1daXk5GQi0p0iUF0m5e1R5YG+9JYihabt1Y0KBgwY\nQGfOnBHtp5Q3h+niypUrdOjQoVfahqEEBASQg4MDzZo1S1TPyVBMLsDfvHmTPvnkE2rVqhW1atWK\nJk2apPZ+RQcHB7p3754wnZmZKfxDlQNIdnY2/fzzz/TLL79QdnY2bd++nYjEjVzT+1GJiGQyGfXt\n21f0w7KystJoq/zSgAsXLtCXX35JixYtIqJ/bnH9/PzozJkzlJOTU6YFkbS9czU7O5v69+9PVlZW\nFBAQQAEBAWRpaUl+fn6iIKvgxo0bFBMTQ2vXrhU+qhQXF9PZs2eFdIMizaBIqSnerblp0yb6+eef\naezYsTR48GBh/V69eomeC1y+fJl69uwp8tG8eXMaMmQIRUZGasxB2tvbi15k8ezZM7K3t6fc3Fxq\n3749ZWdnU79+/ahp06bCfjdt2pT69esn3HortqNp28roe2Wfk5OTaJsPHjwgJycnevToETk5OZG9\nvb2w/NKlS9SoUSNas2YNjR8/XvQSmY0bN9J7771HrVq1EqUAlBk4cKDopHrkyBEaOHAgEalfEKhe\nHCijrX1+//33ap8ffvhB+Ev0T1E65VScrguPV0HfqxsVlFahPOVCh5qKHqakpNDgwYOpYcOGVKVK\nFY3px1dBJpNp/R8a4sckUzRt2rQRCvmvW7cOX331lWhI+rRp0+Dh4QEfHx8AJU/Yv/zySzx79gw3\nb94U6r7Xr18fQ4YMAVDSrWvBggVC0SMF2or2KPpld+3aFb6+vhg4cKDW0p7Kg5b+8//bO/OYKM43\njn8XamNtohG02gAq1ptrUUpFrFhRoApWUUGtHEqj9lCrVet9VVFpPWu80FarlkOkSDjE1giC5dAI\nrSkKRUMq8AcCcqlFjuf3B5npDHvMLDusu/7mk5CwLDs7uzPzzvs+z/P9Pn36YOfOnXBycsL69esF\nbU7FmGrpgiZ74t69eyMuLg5Pnz5FcnIyFAoFjh07plbxqq3sjeH48eMIDw+HjY2NiiUC8z1x/Um6\nd+8Od3d33vcvVE0CtIfjcnNzkZWVhdWrV6O4uBgODg5ISEgA0F5hUlRUxFY5FRcXo3fv3njjjTeg\nUCjQu3dvxMfHo7GxESkpKSqf+969eygsLERdXR3i4+PZfX/8+DGv6goQbtlnbm6O+vp6VgVaX18P\nhUKBXr16obm5Ga2trexzhw8fRmhoKEJDQ7FgwQKeP5EYP6aHDx/yrJhHjx7NnsuMKZgYNJ2f1dXV\ngtUaP//8MwBxFt9ClJeXY8+ePWwVlre3N9atW8eW1wq1bmQQY5QnhqlTp7Kf/8mTJ6ioqOD5Dokp\nU9WHtrY2aTYk2S1HIkaMGMGrKmhpaVFJ3hG12wmfO3eOzp8/T5WVlezfk5OTaciQIbx2YOHh4WRn\nZ8eGdbgzM6GMd0NDA50/f56mTZtGPXr0oKVLl1JaWhrvf7iJsps3b1J4eDivQoOLUHJIX6SwJx45\ncqTacAgXOzs7XlKbi5WVFTvbUzcL5KKtmoSoPTRz8+ZN2r17N02dOpXee+89Wrx4Mft8Tk4O2dvb\nk6OjIzk6OpKDgwP9/vvv1NjYSAcOHBD8rAkJCRQSEkIWFha8Zs9bt27VuWVfamoqDRo0iPz8/Gj6\n9Olka2tLycnJ1NjYSKtXr6YJEyawq40BAwZQXl4e+1puGGHixIn05MkTrfsdERFB/v7+dOnSJYqL\ni6PZs2dTRESE4Ofl0traylsFtLW16XR+cosfNK2ExRISEkIRERFUWVlJlZWV9N133/FCaEKFDAw1\nNTW0detWcnBwoFGjRtHOnTuptrZWr30jIkpJSaGlS5eyj8U2e3/ZGJ2Sdfv27airq0NQUBCICBcu\nXEDPnj1ZKbOFhQX++ecfAKp1oUyy69q1a1i8eDEuX76MU6dOIS8vD8nJyaywxNzcnDUJ6tiWTtus\nuaamBnFxcYiOjuYJr7gyd6YuPygoCLa2tmhqakJSUhKuXLkChUIBHx8fTJs2TWdzL7FERkbi/v37\nSEpKwoYNG/DTTz9h/vz5CAsLE72NuXPnCvp+zJ49G3v37lVrifD2229j6dKlGl/r6+ur4uYH/Hcc\nuSKwHj16wMHBAatWrYKnp6dGg66ysjIoFApYWVlp/3AayM7OVkkSMzC19C4uLjwl640bN+Dv7w97\ne3v2f1taWpCTk8P6oHBFNpGRkfj+++/x1ltvoa2tjT2H/v77b4SGhrL+ImL8mJqbm5Gamork5GQA\n7d+pt7e31vZw6lAqlTyri45oE5px1aD6KkNHjhyJwsJC9hxobW2Fvb19p3x+ugIigp2dHSt6nDBh\nAn799Vds2bIFVVVVGDhwILKysng6EGPA6AZ4Td4YwH8eI9w2beqWT0B7t6aZM2fC3d0dsbGxgopM\nKSEixMbGIjAwENu3b8eff/6JefPmAQBiYmJgb2+vtxBC23tnZGQgPj4ebW1tmDdvnsaeqx1hqnjE\n+H6UlJTA1dUVdnZ2KpYIQhe7Jt8XBm61zuXLl5GZmYlbt26hW7duGDduHCZMmMCrEtEkk9eFNWvW\nYPPmzejZsycCAwNRUFCAffv2wdfXF9OmTcPmzZsxduxY3mtu3bqFHTt2aHRCZODesBhjOw8PD/Y1\nxcXFaGxsZP9PyJVSjM+PWDZv3oy+ffsiNDRUbZ/gkJAQBAYGYuPGjcjPzwcRse6IUgzwNTU1ICIc\nOXJE7cSO+cxCnkO6GImJgVu519TUhKysLNjY2LAhxNLSUvTr1w8KhQIxMTEoKytDSEiISs+Jl43R\nDPB5eXmwsbFhy/hSUlIQFRUFNzc3hISEaG1snJqaisTERDa2yrUxeP3119lyyc7EtLXx4sULXL16\nFdevX4dSqURQUBCSkpLYZh+JiYkYOXIkCgoK2Bl7U1MTlEql5DMTIaXqnDlzBLcRGRmJYcOGqeQa\nMjIyYGVlxStfdHZ2xowZM+Dm5sbOGhlvEKGLvTPH+v79+0hJScHBgwdRWVnJulxqyhd0VDYL4eTk\nhD/++ANXrlzBmTNnsH//fsyfPx/p6elavXns7e3Rp08f0TcsXdDm+y/W50cIxlTLzMyMXclyrxM3\nNzdkZ2ezx7S1tRUuLi7Iz8/v9EqYi6YJHXNTY8zGhDyHdDESEwP3ps2syt3c3JCcnKz3dWZQDBoQ\n0oLYCgN1tLW1vZRWXStXrqTp06fTvn37aPLkyeTl5UVjxozhKUkXLVrEU9D+8ssvrIBGSqRQqmpT\nffr6+vL+5uTkRK2trWq3IyT00OVY+/v70+DBg2nKlCn0zTffUHp6Ok/EIiZfIAam0mLBggWsSIip\n3LC1teXleRgqKys1VlbpQ0lJCQUEBJCNjQ3Z2NhQYGCgSsmmGIV1Z+HmQvQVmomhpaWFlwtQB5NT\ncnR0pBcvXtCLFy/I0dFR6/92BVIrwrsao6miEVthAKhfPnGbHxiK9PR05OXl4bXXXkNYWBisra1R\nXl7OW+pmZ2fjxx9/ZLuq19XVYcSIEaydqbZmC7pQX1+PIUOGsI/d3d1haWkJS0tL0VUOpaWlKmEI\nAHj33XdVvL19fX2xZMkSzJs3T6VzlJDQQ8yxZmb569evh1KpxNWrVxEVFQVLS0vW5wdot3cuLS0V\n5ROujfnz52PEiBHo168fvL29UVlZya66PDw8sH//fuzevZv3mkOHDvHMrs6ePat2NqpruCg8PBzT\np0/HhQsXALT7/u/atQunT59m8wHbtm3jrbSYVZaubNmyBTt27GAft7a2Ijg4mH1vIaGZFJibm+Pz\nzz/XmgsQ8hySGk2tDDteZ+PHj9f5OjMkRhOi8fDwQGpqKnr06IGBAwciLi6OvZA7LpE1LZ/ULWW7\nko6hCHWhCaHu6GLNmIR45513kJWVxYY9GCoqKuDu7i7YfAFoV+Dm5uaqVX26urrytiHGP10TYo61\ns7Mzrl27BgsLC5SUlMDd3R179+5FTk4OunfvjoMHDwJot0fOzMwU9AkXw7Nnz9iQw9OnT9HQ0ID+\n/fvjyZMnCAsLw507d9iJRGZmJkaPHo1Tp06xN6svvviC/U6qq6tx9epVeHl5seWEYtHm+y+UDxDT\nApJLaGgohg8fjvXr16OpqQkBAQFwdnZWaW/Z3NyMtra2LisOEMoF6OKLLoUVsK+vL9zc3FR6IgQE\nBOh9nRmUl7yCYDl58iQ5ODiQp6cnb6lTXFzMihcYYmJiVF4fGxvb5fvYEV0UprW1tWoFE1IhhVJV\nrOpTX8Qca8bXg4ho2bJltHbtWiJqL5t0dXVln2OUvx1/xLJ37172947nUMfvs6GhgWJiYig2NlZj\niSiXsrIy8vLyEr0vDJs2baJly5axArIVK1bQpk2biEi8t45YWltbae7cuRQeHk6TJ0+m/fv3855f\nt26ditp448aNOr+PEG+++SYpFApBlba214s1EhMD9/zj0pWK8K7AaAZ4onZDsOvXr/NigEVFRSpG\nV2JUh8aCkLxdKnRVqmrahhjVJxFRfX09HT16lHx8fMjHx4eOHTsmatBjEDrWYmvG9UWbJkLfc6qh\noaFTx7q2tpYOHTpEXl5e5OXlRYcPH6a6ujoiki4fwNVu5OTkkJOTE3366acqxmfq4txMbsIQLF++\nnIiIzTNwf/z8/Gjt2rUqegV9qK6upqqqKtq9ezdt2bKFSkpKqLq6mv2R4jozJEYTohFDamoqUlJS\nEBMTg7lz5/JUhw0NDWxNsDEh1KhZarhK1Q8//LBTcUqu6lPTNrZu3YrHjx9j4cKFrH96nz59JIvP\niq0Z51ZNNTU1oaWlRaWzkTa0lfrputTnmsU1NTWhsLAQa9euxfLly0VvQ4iFCxeif//+KvmATZs2\noaysTG0TcnV09HTvCBNqmzJlCs6ePcsqSsvLy7FgwYJOVwZpQ10XK3Nzc4wZM4bXTJvLo0ePcPz4\ncdE9SoXQVqYN/NfKUIrrzBCY1ADPNLHmlkExbb3c3Ny6LD6oD1I2ajYmlEolbt++zbr5tbS0wMXF\nRWuiTFfE1Ixz4TpWdowha0LKAZ47CHXv3h1KpVIn/QX3BqGuljsxMVF0PkCIjg6tCoUCSqUSHh4e\nPHFWdHQ09uzZw06ooqOjsWHDBrbxu1SEh4fj7t27KCgowL1791BTUwMvLy9eFytNJCYmsg1dpOLf\nf/9VOXbq/mbsmNQAD7QPJCEhIWyW39jx9PREQkKCxkbNpsqiRYvg7e2NgIAAEBEuXbqE1NRUXiu3\nl8WoUaNEi4C01XI/f/4cLS0tndoHbsJWLMwNIi0tDQUFBewgGhsbCycnJ96sXcwqSxsdxVlEhMLC\nQty9exdHjhyBp6cn+1xpaSkuXrwIoF3BzLTZkxI3Nze2ixVzU3V0dGSrzMQ2V5cKZmIm9Dej56UE\nhvRk3LhxauOQxkhjYyNbL56enk7nz59Xaw1rahQXF9PMmTPJ2tqarK2tyd/fn4qLiw2+H0KOlYbg\n7t27FBAQQMHBwVReXk5jx46lXr16kYuLC924cUPn7SmVSt450tjYaLAcU1FRkd6+Mp1BqItVcHAw\nxcTEkIODA+Xn59Nnn32m1otGXyoqKuj27ds0fPhwnktqamoq213MlDCaOnhdsLOzw/vvvw9fX1+2\nXMnQ3cqF0OYSuW7dOowfPx4rVqxQW3duCgwdOhTx8fGsg163bt0QGxuLoUOHGnQ/uD1F1TlWGoKv\nv/4aoaGhqKqqgrOzM44ePQp/f3/cvHkTEREROms0LCws8Ndff8HV1RUAUFhYKFkTCSGGDRuGhw8f\nSu5yKsSSJUvg5+eHyspKLFy4EJmZmYiMjGSf16W5uj6kpaXh7NmzKC8v5/VdHThwoEqjE1PA5EI0\ngLBXh7Hz/Plz5OTkYNeuXbzGwaaAGHuG/zcYmwMigq2tLU/7wDynC7du3cInn3zCxuDNzc1x8uRJ\nnsCrK2hubkZUVBTu3LnD6gwMybNnz9guVn5+frx497hx45CZmYmVK1fC0tIStra2OHHihGTJ1Y5c\nunQJs2bN6pJtGxKTHOAZtHl1mALHjh1Taf9n7KxatQoPHjxgxUpmZmaorq5GZGSk3r4ouiC1uZQ+\nSJmo5aKvQ6Y2HBwceI+JCLW1tfjggw+wY8eOLomza2PRokVYtmwZ7xzatm0bO5nTReikD+fOnUNQ\nUBD27dunkqMwtiiBGExygH/w4AE2bNiA7OxsAO139/DwcAwePPgl79mrz+jRo1l7hrq6OrX2DIZA\nanMpfeiKRK0UDpna6KiwVigUsLa25lXQGBIrKytYWlriq6++Yo+dtpsjcRxbpeTEiRNYsmSJRodQ\nU4kSMJjkAB8WFoZJkyaxB/fixYv47bffcPr06Ze8Z68+Us5QpcIY9kFKpHLINCWcnZ2Rnp6Ojz/+\nGAMGDMChQ4fg6uqK3NxcowkJHjhwACtXrjTY+0mBSQ7w2rw6ZLoW7mwV4M9YuyL5JoZXbYAfNWoU\n8vPzjVLX0VUwx5CIsG3bNly7dg0VFRWYMWMGLyRobm6Oqqoqg4cEAcDGxgaPHj0y6Hvqi0lW0fj5\n+eHLL79EaGgoiAjnzp3jiURkug5d+n3KdA6pHDJNCeb6VSgU2L59O8zMzJCRkSHKsVVGMyY5g6+v\nr8eZM2d47cpCQkLkg/5/BLeMr7PNJowVKR0yTYk7d+4gKioKFy9exKBBgzBr1iz88MMPRhMSNMUZ\nvEkN8M3NzUhLS0NWVha8vb3h4eHBhmlkZF4VNPmuTJw40aD7YQiKiooQFRWFmJgY9O3bF3PmzMG3\n337L9l02dEhQW/3/s2fPTG4Fa1ID/Jo1a1BYWIhJkyYhKSkJfn5+Jle2JCMj8x9mZmbw9fXFkSNH\nMGDAAACAra2t8fmqmygmNcCPGTMGOTk56NatG2pra/HRRx8hIyPjZe+WjIwkGFo9agwkJCQgKioK\nubm58PHxwZw5cxAWFibYKEdGHCY1wBtjiZ6MjIz+NDY24vLly4iKisL169cRHByMmTNnwsvL62Xv\nmkljUgO8MZboycjISEtNTQ3i4uIQHR3N9gGQ6RwmNcDLyMjIyIhHLkGRkZGReUWRB3gZGRmZVxR5\ngJeRkZF5RZEHeBkZGZlXFHmAl5GRkXlF+R8WpZJDJGoBrgAAAABJRU5ErkJggg==\n"
      }
     ],
     "prompt_number": 95
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Number of View Counts by Language"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Conclusion?"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "tedx_df['viewCount'] = tedx_df['viewCount'].fillna(0)\n",
      "tedx_df[tedx_df.viewCount!='-'][['viewCount', 'lang']].groupby('lang').sum().sort('viewCount', ascending=0)[:10]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>viewCount</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>lang</th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>English</th>\n",
        "      <td> 58477968</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Arabic</th>\n",
        "      <td>  4213183</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Spanish</th>\n",
        "      <td>  4173229</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>French</th>\n",
        "      <td>  3571510</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Portuguese</th>\n",
        "      <td>  1516388</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Japanese</th>\n",
        "      <td>   909865</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Korean</th>\n",
        "      <td>   892479</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Polish</th>\n",
        "      <td>   827042</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Greek</th>\n",
        "      <td>   490969</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Indonesian</th>\n",
        "      <td>   478289</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "output_type": "pyout",
       "prompt_number": 96,
       "text": [
        "           viewCount\n",
        "lang                \n",
        "English     58477968\n",
        "Arabic       4213183\n",
        "Spanish      4173229\n",
        "French       3571510\n",
        "Portuguese   1516388\n",
        "Japanese      909865\n",
        "Korean        892479\n",
        "Polish        827042\n",
        "Greek         490969\n",
        "Indonesian    478289"
       ]
      }
     ],
     "prompt_number": 96
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "tmp_tedx_df = tedx_df[tedx_df.lang!='English'].copy()\n",
      "tmp_tedx_df[tmp_tedx_df.viewCount!='-'][['viewCount', 'lang']].groupby('lang').sum().sort('viewCount', ascending=0).plot(kind=\"bar\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 98,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x1976f0f0>"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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jKipKlGGMMXb1SB7DOHr0KMxmM0JCQpCXlwdfX18AgK+vL3JzcwFYT/5KpVKU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\nGlXsz5zS5bAAAAAASUVORK5CYII=\n"
      }
     ],
     "prompt_number": 98
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Number of Events by Language"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Conclusion?"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "tedx_df.groupby('lang').event.nunique().order(ascending=False)[:10]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 99,
       "text": [
        "lang\n",
        "English       1035\n",
        "Spanish        101\n",
        "Portuguese      63\n",
        "French          54\n",
        "Korean          48\n",
        "Arabic          35\n",
        "Russian         26\n",
        "Italian         19\n",
        "Japanese        15\n",
        "Chinese         14"
       ]
      }
     ],
     "prompt_number": 99
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "tmp_tedx_df = tedx_df[tedx_df.lang!='English'].copy()\n",
      "tmp_tedx_df.groupby('lang').event.nunique().order(ascending=False).plot(kind=\"bar\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 100,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x17887670>"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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PHj2iPXv2kKOjo8b2MLSNDO0rSgzt38+ePSNXV1c6evQoTZ48mXx8fCgzM1Py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\nYII=\n"
      }
     ],
     "prompt_number": 100
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<span id=\"stat2\"></span>\n",
      "<a href=\"#outline\">Go to Top</a>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Statistics by Country"
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Number of Videos by Country"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "tedx_df['country'].value_counts()[:10]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 51,
       "text": [
        "United States     5634\n",
        "Canada            1249\n",
        "India              815\n",
        "Brazil             726\n",
        "Netherlands        710\n",
        "South Korea        685\n",
        "Spain              674\n",
        "Australia          605\n",
        "United Kingdom     591\n",
        "Japan              474"
       ]
      }
     ],
     "prompt_number": 51
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Number of View Counts by Country"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "tedx_df[tedx_df.viewCount!='-'][['viewCount', 'country']].groupby('country').sum().sort('viewCount', ascending=0)[:10]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>viewCount</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>country</th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>United States</th>\n",
        "      <td> 18189465</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Canada</th>\n",
        "      <td>  4572056</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>France</th>\n",
        "      <td>  3065666</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>United Kingdom</th>\n",
        "      <td>  2226657</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Argentina</th>\n",
        "      <td>  2171808</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Netherlands</th>\n",
        "      <td>  1947574</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Japan</th>\n",
        "      <td>  1734785</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>India</th>\n",
        "      <td>  1510407</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Yemen</th>\n",
        "      <td>  1308153</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Spain</th>\n",
        "      <td>  1196308</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "output_type": "pyout",
       "prompt_number": 104,
       "text": [
        "               viewCount\n",
        "country                 \n",
        "United States   18189465\n",
        "Canada           4572056\n",
        "France           3065666\n",
        "United Kingdom   2226657\n",
        "Argentina        2171808\n",
        "Netherlands      1947574\n",
        "Japan            1734785\n",
        "India            1510407\n",
        "Yemen            1308153\n",
        "Spain            1196308"
       ]
      }
     ],
     "prompt_number": 104
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Number of Events by Country"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "tedx_df.groupby('country').event.nunique().order(ascending=False)[:10]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 48,
       "text": [
        "country\n",
        "United States     359\n",
        "India              89\n",
        "Canada             80\n",
        "United Kingdom     51\n",
        "South Korea        47\n",
        "Brazil             44\n",
        "Spain              41\n",
        "Netherlands        32\n",
        "France             30\n",
        "Australia          28"
       ]
      }
     ],
     "prompt_number": 48
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<span id=\"viz1\"></span>\n",
      "<a href=\"#outline\">Go to Top</a>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Trends of TEDx over 5 years (by language)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# more information for visualization, including how to prepare data for D3.js\n",
      "# http://nbviewer.ipython.org/5501063"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import HTML\n",
      "HTML('<iframe src=\"http://96chany.com/projects/tedx_popularity\" width=\"1000\" height=\"800\"></iframe>')\n",
      "\n",
      "# you can navigate years by sliding 'year' digits"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<iframe src=\"http://96chany.com/projects/tedx_popularity\" width=\"1000\" height=\"800\"></iframe>"
       ],
       "output_type": "pyout",
       "prompt_number": 3,
       "text": [
        "<IPython.core.display.HTML at 0x637f970>"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<span id=\"viz2\"></span>\n",
      "<a href=\"#outline\">Go to Top</a>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Comparison between TED and TEDx by language"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import HTML\n",
      "HTML('<iframe src=\"http://96chany.com/projects/tedx_comparison\" width=\"1100\" height=\"750\"></iframe>')\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<iframe src=\"http://96chany.com/projects/tedx_comparison\" width=\"1100\" height=\"750\"></iframe>"
       ],
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "<IPython.core.display.HTML at 0x637fdf0>"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from pandas import read_csv\n",
      "from urllib import urlopen\n",
      "from pandas import Series, DataFrame\n",
      "\n",
      "page = urlopen(\"list of languages by number of native speaker.csv\")\n",
      "df = read_csv(page)\n",
      "df.set_index('Language',inplace=True,drop=True)\n",
      "df[:30].plot(kind=\"bar\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 1,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x6aacb90>"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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YRtmwB88wDFMMMZEOXs1ahWiV4jEqIQ7WFn2tUuLgPHiGYRhGB/bgWWtUyzCM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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x6aacbb0>"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Issues We Encountered"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Data inconsistancy :\n",
      "The video [TEDxCausewayBay - Terence Wong - 04/15/10](http://tedxtalks.ted.com/video/TEDxCausewayBay-Terence-Wong-04) appears in language [Chinese](http://tedxtalks.ted.com/browse/talks-by-language/chinese?page=6) and [Korean](http://tedxtalks.ted.com/browse/talks-by-language/korean?page=32), and in event [TEDxCAU](http://tedxtalks.ted.com/browse/talks-by-event/tedxcau?page=2) and [TEDxCausewayBay](http://tedxtalks.ted.com/browse/talks-by-event/TEDxCausewayBay)"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<span id=\"next\"></span>\n",
      "<a href=\"#outline\">Go to Top</a>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "What's Next?"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "* Video Recommendation for Translators Based on Translators' Translating History\n",
      "* Comparing the Translated Results of Human Translators and Machine Translators (Google/Bing Translate) to Improve the Translation Quality"
     ]
    }
   ],
   "metadata": {}
  }
 ]
}