index.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "library(readr)\n",
    "library(dplyr, warn.conflicts = FALSE)\n",
    "library(ggplot2)\n",
    "library(lubridate, warn.conflicts = FALSE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "download.file(url='http://dvn-vm1.hmdc.harvard.edu/data/mysql/irclog/irclog.tsv', destfile='data/irclog.tsv', method='curl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Parsed with column specification:\n",
      "cols(\n",
      "  id = col_double(),\n",
      "  channel = col_character(),\n",
      "  day = col_date(format = \"\"),\n",
      "  nick = col_character(),\n",
      "  timestamp = col_double(),\n",
      "  line = col_character(),\n",
      "  spam = col_double(),\n",
      "  in_summary = col_double()\n",
      ")\n",
      "Warning message:\n",
      "“1954 parsing failures.\n",
      "row  col           expected actual              file\n",
      "223 line delimiter or quote        'data/irclog.tsv'\n",
      "223 line delimiter or quote      W 'data/irclog.tsv'\n",
      "223 line delimiter or quote        'data/irclog.tsv'\n",
      "223 line delimiter or quote      T 'data/irclog.tsv'\n",
      "258 line delimiter or quote        'data/irclog.tsv'\n",
      "... .... .................. ...... .................\n",
      "See problems(...) for more details.\n",
      "”"
     ]
    }
   ],
   "source": [
    "df <- read_tsv('data/irclog.tsv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "options(dplyr.print_max = 1e9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "out <- df %>%\n",
    "    filter(!is.na(nick)) %>%\n",
    "    group_by(month=floor_date(as.Date(day), \"month\")) %>%\n",
    "    count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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GIBSVF1IGmL2yqQFAGpTSVDGn900w4g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\nSUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "out %>% ggplot(aes(x = month, y = n)) + geom_col() +\n",
    "ylab(\"messages\") +\n",
    "xlab(\"month\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# A tibble: 78 x 2\n",
      "# Groups:   month [78]\n",
      "   month          n\n",
      "   <date>     <int>\n",
      " 1 2012-12-01   188\n",
      " 2 2013-01-01   129\n",
      " 3 2013-02-01   550\n",
      " 4 2013-03-01    85\n",
      " 5 2013-04-01    55\n",
      " 6 2013-05-01   244\n",
      " 7 2013-06-01     5\n",
      " 8 2013-07-01   494\n",
      " 9 2013-08-01   411\n",
      "10 2013-09-01    87\n",
      "11 2013-10-01   217\n",
      "12 2013-11-01    97\n",
      "13 2013-12-01    30\n",
      "14 2014-01-01   946\n",
      "15 2014-02-01   196\n",
      "16 2014-03-01   607\n",
      "17 2014-04-01   460\n",
      "18 2014-05-01   561\n",
      "19 2014-06-01   237\n",
      "20 2014-07-01   867\n",
      "21 2014-08-01   122\n",
      "22 2014-09-01   443\n",
      "23 2014-10-01   327\n",
      "24 2014-11-01   103\n",
      "25 2014-12-01   221\n",
      "26 2015-01-01   246\n",
      "27 2015-02-01   370\n",
      "28 2015-03-01   516\n",
      "29 2015-04-01   967\n",
      "30 2015-05-01   522\n",
      "31 2015-06-01   391\n",
      "32 2015-07-01   926\n",
      "33 2015-08-01   330\n",
      "34 2015-09-01   498\n",
      "35 2015-10-01   654\n",
      "36 2015-11-01   464\n",
      "37 2015-12-01   989\n",
      "38 2016-01-01   585\n",
      "39 2016-02-01   668\n",
      "40 2016-03-01   592\n",
      "41 2016-04-01   232\n",
      "42 2016-05-01   464\n",
      "43 2016-06-01   949\n",
      "44 2016-07-01   588\n",
      "45 2016-08-01   719\n",
      "46 2016-09-01  1054\n",
      "47 2016-10-01   799\n",
      "48 2016-11-01   483\n",
      "49 2016-12-01   174\n",
      "50 2017-01-01   699\n",
      "51 2017-02-01   580\n",
      "52 2017-03-01   407\n",
      "53 2017-04-01   439\n",
      "54 2017-05-01   305\n",
      "55 2017-06-01   384\n",
      "56 2017-07-01   513\n",
      "57 2017-08-01   513\n",
      "58 2017-09-01  1230\n",
      "59 2017-10-01   655\n",
      "60 2017-11-01   683\n",
      "61 2017-12-01   794\n",
      "62 2018-01-01   632\n",
      "63 2018-02-01   609\n",
      "64 2018-03-01   899\n",
      "65 2018-04-01  1068\n",
      "66 2018-05-01  1058\n",
      "67 2018-06-01   801\n",
      "68 2018-07-01   639\n",
      "69 2018-08-01   473\n",
      "70 2018-09-01  1376\n",
      "71 2018-10-01  2603\n",
      "72 2018-11-01  2656\n",
      "73 2018-12-01  1797\n",
      "74 2019-01-01  2061\n",
      "75 2019-02-01   866\n",
      "76 2019-03-01  1654\n",
      "77 2019-04-01  1553\n",
      "78 2019-05-01  1152\n"
     ]
    }
   ],
   "source": [
    "out %>% print(n=80)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "ggsave(\"irclog.png\", width = 7, height = 3)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "3.4.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}