rutkowski_finalproject.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ASCL - Astrophysics Source Code Library"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\"Software is the most used instrument in astronomy\"\n",
    "\n",
    "-- Alice Allen, ASCL"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Reproducibility is a vital part of the scientific method.  As computers become more and more powerful and necessary tools in producing science results, the exact methods used in coming to the results are increasingly reliant on software, in some version.  Recording that software becomes an important step to ensure software reproducibility.  The Astrophysics Source Code Library (ASCL) houses links and references to software codes used in scientific papers.  \n",
    "\n",
    "In a project to assist the recording of these codes, we will look at all of the software that is registered in the ASCL and add to the keyword metadata.  We will use Python and the Astrophysics Data System (ADS) to grab the keywords for each paper which cites that software, then use provide those keywords in order to populate the ASCL records.\n",
    "\n",
    " \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import necessary libs\n",
    "import requests\n",
    "import urllib.request, json \n",
    "import re\n",
    "import random\n",
    "import pprint\n",
    "import pandas as pd\n",
    "import math\n",
    "import matplotlib.pyplot as plt\n",
    "from ipywidgets import Image\n",
    "\n",
    "# my ADS API key (+++ do not check this into github!)\n",
    "token = \"ggg\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The ASCL very conveniently provides all of their records in a JSON record.  As of mid December 2018, there are 1,845 pieces of software registered in the ASCL.\n",
    "\n",
    "We retrieve the records here."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of ASCL entries:  1845\n"
     ]
    }
   ],
   "source": [
    "with urllib.request.urlopen(\"http://ascl.net/code/json\") as url:\n",
    "    ascl_data = json.loads(url.read().decode())\n",
    "    #print(data)\n",
    "\n",
    "print(\"Number of ASCL entries: \",len(ascl_data))\n",
    "\n",
    "# let's use the ascl_id as the dict keys\n",
    "ascl_data = {ascl_data[k]['ascl_id']: ascl_data[k] for k in ascl_data.keys()}\n",
    "\n",
    "# +++ for testing, just grab a sample\n",
    "#ascl_data_sample_keys = random.sample(list(ascl_data), 25)\n",
    "#ascl_data = {k: ascl_data[k] for k in ascl_data_sample_keys}\n",
    "\n",
    "#print (ascl_data.keys())\n",
    "#ascl_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Astrophysics Data System (ADS)\n",
    "\n",
    "The Astrophysics Data System (ADS) archives abstracts from a wide range of papers in physics and astronomy.  \n",
    "https://ui.adsabs.harvard.edu/  It identifies each record with a unique \"bibcode\".\n",
    "\n",
    "The bibcode is a 19 digit code in the form of:  <br />\n",
    "YYYYJJJJJVVVVMPPPPA <br />\n",
    "where: <br />\n",
    "YYYY is the year <br />\n",
    "JJJJJ is the journal <br />\n",
    "VVVV is the volume number <br />\n",
    "M is meant to disambiguate a record, if needed <br />\n",
    "PPPP is the page number <br />\n",
    "A is the first letter of the first author's last name <br />\n",
    "(http://simbad.u-strasbg.fr/guide/refcode/refcode-paper.html)\n",
    "\n",
    "The UI for this service has recently been updated.  It provides an easy search form to find a paper, and provides a results page with the title, authors, abstract, publication date, keywords, and other metadata.\n",
    "\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"https://raw.githubusercontent.com/krutkow/cmsc641/master/ADS_search_page.png\">"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![Image of ADS Results Page](https://raw.githubusercontent.com/krutkow/cmsc641/master/ADS_results_page.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Getting the keywords\n",
    "\n",
    "We are using the API given by the Astrophysics Data System, ADS, described at https://github.com/adsabs/adsabs-dev-api.\n",
    "\n",
    "We loop through each ASCL entry, indexed by the ASCL ID, and grab the bibcode for each paper that cites this code.  We use that bibcode with the ADS API in order to retrieve the keyword entries.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "# the dict that will hold the number by journal by year\n",
    "code_by_journal_year = {}\n",
    "\n",
    "# some ASCL entries don't have any refs.  Let's track those.\n",
    "entries_no_refs = []\n",
    "\n",
    "# +++ some refs need to be looked at later and cleaned\n",
    "clean_refs_later = []\n",
    "\n",
    "# create a dict data structure to hold the keywords\n",
    "ascl_keywords_dict = {}\n",
    "\n",
    "# now loop through all the entries, to grab the keywords\n",
    "for key, val in ascl_data.items():\n",
    "#for x in '0':\n",
    "    # +++\n",
    "    #key = '1403.002'\n",
    "    #val = ascl_data[key]\n",
    "    \n",
    "    # initialize the empty keyword list so we can extend it later\n",
    "    ascl_keywords_dict[key] = list()\n",
    "    \n",
    "    #print('-------------------------------')\n",
    "    curr_ascl_record = val\n",
    "    #print('ascl_id: ',curr_ascl_record['ascl_id'])\n",
    "    list_refs = curr_ascl_record['ref_list']\n",
    "        \n",
    "    # some entries don't have any refs\n",
    "    if not list_refs:\n",
    "        entries_no_refs.append(key)\n",
    "        continue\n",
    "    \n",
    "    # grab the year from the ASCL ID\n",
    "    curr_year = key[:2]\n",
    "    # we'll hard code in the 2 digit prefix, using 2050 as a safe future comparison\n",
    "    if int(curr_year) > 50:\n",
    "        curr_year = '19'+str(curr_year)\n",
    "    else:\n",
    "        curr_year = '20'+str(curr_year)\n",
    "        \n",
    "    for ref in list_refs:\n",
    "        #print(' ref: ',ref)\n",
    "        \n",
    "        # ### CLEAN THE REF AND BIBCODE\n",
    "        # +++ it would be convenient if the bibcode was an entry in the JSON, rather than the ref\n",
    "        \n",
    "        # some refs had the URL replacement for an ampersand \n",
    "        ref = ref.replace('%26','&')\n",
    "        \n",
    "        # if the last character is a slash, remove it\n",
    "        if ref.endswith('/'):\n",
    "            ref = ref[:-1]\n",
    "            \n",
    "        # just get the last part of the html, to get the bibcode\n",
    "        last_slash_idx = ref.rfind('/')\n",
    "        curr_bibcode = ref[last_slash_idx+1:last_slash_idx+1+19]\n",
    "            \n",
    "        # check that URL actually does end with the bibcode\n",
    "        if 'abstract' in curr_bibcode:\n",
    "            last_slash_idx = ref.rfind('/',0,last_slash_idx)\n",
    "            curr_bibcode = ref[last_slash_idx+1:last_slash_idx+1+19]\n",
    "        \n",
    "        if '?' in curr_bibcode:\n",
    "            last_slash_idx = ref.rfind('?')\n",
    "            curr_bibcode = ref[last_slash_idx+1:last_slash_idx+1+19]\n",
    "        \n",
    "        # some refs had the URL replacement for an ampersand \n",
    "        curr_bibcode = curr_bibcode.replace('%26','&')\n",
    "        \n",
    "        # some entries need to be cleaned better later\n",
    "        # flag the refs that aren't to URLs that we know already we can \n",
    "        # safely grab the bibcode from\n",
    "        okay_urls = ['adsabs','cdsads','cdsbib','esoads']\n",
    "        if not any(x in str.lower(ref) for x in okay_urls):\n",
    "            clean_refs_later.append(key)\n",
    "            #print(' *** WARNING: UNKNOWN URL for key ',key,' *** ')\n",
    "            continue\n",
    "        \n",
    "        # get the journal from the bibcode\n",
    "        curr_journal=curr_bibcode[4:9]\n",
    "        curr_journal=curr_journal.strip('.')\n",
    "        \n",
    "        # add the year and journal to the dict from which we will plot\n",
    "        # check if the year is already in our 2D dict\n",
    "        if curr_year in code_by_journal_year:\n",
    "            if curr_journal in code_by_journal_year[curr_year]:\n",
    "                code_by_journal_year[curr_year][curr_journal] += 1\n",
    "            else:\n",
    "                code_by_journal_year[curr_year][curr_journal] = 1\n",
    "        else:\n",
    "            code_by_journal_year[curr_year]={}\n",
    "            code_by_journal_year[curr_year][curr_journal] = 1\n",
    "            \n",
    "        # get the bibcode\n",
    "        bibcode = {\"bibcode\":[curr_bibcode]}\n",
    "        pattern = re.compile(\"^(\\d{4}.{5}.{4}..{4}.)$\")\n",
    "        if not pattern.match(curr_bibcode):\n",
    "            #print(' *** ERROR: WRONG BIBCODE PATTERN for key ',key,' *** ')\n",
    "            #print(' bibcode: ',curr_bibcode)\n",
    "            clean_refs_later.append(key)\n",
    "            continue\n",
    "        \n",
    "        # +++ I reached the request limit tonight\n",
    "        continue\n",
    "        \n",
    "        r = requests.post(\"https://api.adsabs.harvard.edu/v1/export/bibtex\", \\\n",
    "                         headers={\"Authorization\": \"Bearer \" + token, \"Content-type\": \"application/json\"}, \\\n",
    "                         data=json.dumps(bibcode))\n",
    "        itsok=True\n",
    "        \n",
    "        # get the dict of this json entry\n",
    "        try:\n",
    "            curr_entry = r.json()\n",
    "        except Exception as ex:\n",
    "            clean_refs_later.append(key)\n",
    "            print(' *** ERROR: BAD JSON for key ',key,' *** ')\n",
    "            print(ex)\n",
    "            itsok=False\n",
    "            pass\n",
    "            print('passing')\n",
    "            continue\n",
    "            \n",
    "        if not itsok:\n",
    "            continue\n",
    "        \n",
    "        # make sure that our field is there\n",
    "        if \"export\" not in curr_entry:\n",
    "            clean_refs_later.append(key)\n",
    "            print(' *** ERROR: ADS did not return full entry for key ',key,' *** ')\n",
    "            print(curr_entry)\n",
    "            continue\n",
    "            \n",
    "        curr_entry_info = curr_entry[\"export\"]\n",
    "        \n",
    "        # +++ I would prefer to put all of the fields in a dict, but I couldn't get the regex exactly right yet\n",
    "        # this grabs the newline, to combine two entries in a row, which is wrong, but close\n",
    "        # see entry for 1998ApJ...509...39N for an example\n",
    "        #print(' curr_entry_info: ',curr_entry_info)\n",
    "        #re.findall(r'(\\S+) = (.*\\s*.*\\,\\s)', curr_entry_info)  \n",
    "\n",
    "        # for now, just grab the keywords\n",
    "        curr_entry_info_dict = dict(re.findall(r'(keywords) = (.*\\s*.*\\,\\s)', curr_entry_info))\n",
    "        \n",
    "        # if there were no keywords in this entry, go to the next entry\n",
    "        if not curr_entry_info_dict:\n",
    "            # +++ should we record this and look at these later?\n",
    "            continue\n",
    "            \n",
    "        # remove: any newlines in the middle, starting and ending curly braces, multiple spaces in a row\n",
    "        curr_entry_info_dict['keywords'] = curr_entry_info_dict['keywords'].replace('\\n','')\n",
    "        curr_entry_info_dict['keywords'] = curr_entry_info_dict['keywords'].replace('{','')\n",
    "        curr_entry_info_dict['keywords'] = curr_entry_info_dict['keywords'].replace('}','')\n",
    "        curr_entry_info_dict['keywords'] = re.sub(' +',' ', curr_entry_info_dict['keywords'])\n",
    "        #print('  keywords: ',curr_entry_info_dict['keywords'])\n",
    "        \n",
    "        # convert the keywords to a list\n",
    "        keyword_list = curr_entry_info_dict['keywords'].split(\",\")\n",
    "        # and strip the spaces    \n",
    "        keyword_list = [x.strip(' ') for x in keyword_list]\n",
    "        # remove the inadvertant empty fields\n",
    "        keyword_list = filter(None, keyword_list)\n",
    "        # remove any keywords that are \"astrophysics\", as that is redundant in the ASCL\n",
    "        \n",
    "        # for this ascl_id, record the keywords \n",
    "        ascl_keywords_dict[key].extend(keyword_list)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Incomplete Entries\n",
    "\n",
    "Some ASCL entries require further attention.  Some were missing refs, or the refs were not to a URL where we could reliably retrieve a bibcode.  These are listed here, to go back and fix later"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "26  entries without refs\n",
      "['9909.004', '9911.001', '1010.053', '1303.021', '1311.008', '1402.005', '1403.004', '1411.006', '1602.018', '1603.014', '1707.005', '1708.017', '1707.001', '1811.012', '1804.017', '1805.024', '1806.013', '1811.010', '1808.007', '1808.006', '1808.011', '1809.008', '1810.006', '1810.021', '1811.009', '1812.001']\n",
      "\n",
      "\n",
      "48  entries to look at later\n",
      "['1010.005', '1712.008', '1105.005', '1105.005', '1105.009', '1105.014', '1108.003', '1109.018', '1109.021', '1110.008', '1110.009', '1110.025', '1111.008', '1112.001', '1112.017', '1201.015', '1204.011', '1304.016', '1308.006', '1308.016', '1401.010', '1402.002', '1408.009', '1409.008', '1409.008', '1502.009', '1505.010', '1505.011', '1806.023', '1511.004', '1511.004', '1511.004', '1511.002', '1608.002', '1610.016', '1611.001', '1704.006', '1706.007', '1705.003', '1808.009', '1711.012', '1710.005', '1801.003', '1803.009', '1803.012', '1804.010', '1809.014', '1811.003']\n"
     ]
    }
   ],
   "source": [
    "num_wo_refs = len(entries_no_refs)\n",
    "num_refs_to_clean = len(clean_refs_later)\n",
    "\n",
    "print(num_wo_refs, \" entries without refs\")\n",
    "print(entries_no_refs)\n",
    "print('\\n')\n",
    "print(num_refs_to_clean, \" entries to look at later\")\n",
    "print(clean_refs_later)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Journal Participation\n",
    "\n",
    "We wish to track the number of ASCL code entries per year per journal.  We can see that there are a handful of journal from which most of the entries originate, and then over 100 journals with only a few entries."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       A&A  A&ARv  A&AS   A&C  AAS  AGUSM  AIPC    AJ   AN  APS  ...   ocpd  \\\n",
      "1999   4.0    NaN   1.0   NaN  NaN    NaN   NaN   1.0  NaN  NaN  ...    NaN   \n",
      "2000   1.0    NaN   NaN   NaN  NaN    NaN   NaN   NaN  NaN  NaN  ...    NaN   \n",
      "2001   1.0    NaN   NaN   NaN  NaN    NaN   NaN   NaN  NaN  NaN  ...    NaN   \n",
      "2002   NaN    NaN   NaN   NaN  NaN    NaN   NaN   NaN  NaN  NaN  ...    NaN   \n",
      "2010  10.0    NaN   2.0   NaN  NaN    NaN   1.0   3.0  1.0  NaN  ...    NaN   \n",
      "2014  37.0    NaN   1.0  16.0  5.0    1.0   1.0   9.0  NaN  NaN  ...    NaN   \n",
      "2011  31.0    NaN   3.0   1.0  3.0    NaN   1.0   7.0  4.0  NaN  ...    NaN   \n",
      "2017  47.0    2.0   NaN   6.0  NaN    NaN   NaN  15.0  NaN  NaN  ...    NaN   \n",
      "2012  35.0    NaN   1.0   2.0  4.0    NaN   1.0   6.0  NaN  NaN  ...    1.0   \n",
      "2013  27.0    NaN   2.0   8.0  1.0    NaN   1.0  10.0  2.0  2.0  ...    NaN   \n",
      "2015  41.0    NaN   1.0  25.0  1.0    NaN   NaN  12.0  NaN  NaN  ...    NaN   \n",
      "2016  35.0    NaN   NaN   9.0  NaN    NaN   NaN  10.0  NaN  NaN  ...    NaN   \n",
      "2018  25.0    NaN   NaN  11.0  1.0    NaN   NaN  17.0  NaN  NaN  ...    NaN   \n",
      "\n",
      "      phot  physi  pms  poii  sf2a  ucl  uxsa  xrrc  yCat  \n",
      "1999   NaN    NaN  NaN   NaN   NaN  NaN   NaN   NaN   NaN  \n",
      "2000   NaN    NaN  NaN   NaN   NaN  NaN   NaN   NaN   NaN  \n",
      "2001   NaN    NaN  NaN   NaN   NaN  NaN   NaN   NaN   NaN  \n",
      "2002   NaN    NaN  NaN   NaN   NaN  NaN   NaN   NaN   NaN  \n",
      "2010   NaN    NaN  NaN   NaN   NaN  NaN   NaN   NaN   NaN  \n",
      "2014   NaN    NaN  NaN   NaN   NaN  NaN   NaN   1.0   NaN  \n",
      "2011   NaN    NaN  NaN   NaN   1.0  NaN   NaN   NaN   1.0  \n",
      "2017   NaN    NaN  NaN   NaN   NaN  NaN   NaN   NaN   NaN  \n",
      "2012   NaN    NaN  1.0   1.0   2.0  NaN   NaN   NaN   NaN  \n",
      "2013   1.0    NaN  NaN   NaN   1.0  NaN   1.0   NaN   NaN  \n",
      "2015   NaN    NaN  NaN   NaN   NaN  NaN   NaN   NaN   NaN  \n",
      "2016   NaN    NaN  NaN   NaN   NaN  1.0   NaN   NaN   NaN  \n",
      "2018   NaN    1.0  NaN   NaN   NaN  NaN   NaN   NaN   1.0  \n",
      "\n",
      "[13 rows x 154 columns]\n"
     ]
    }
   ],
   "source": [
    "# let's put the 2d dict of year-journal entries into a datafram\n",
    "\n",
    "# +++ turning the 2D dict into a dataframe may be unnecessarily complicating things\n",
    "code_by_journal_year_df = pd.DataFrame(code_by_journal_year)\n",
    "code_by_journal_year_df = code_by_journal_year_df.transpose()\n",
    "\n",
    "# and let's see it\n",
    "print(code_by_journal_year_df)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting the participation by journal\n",
    "\n",
    "Using the metadata we collected when gathering the keywords, we can track the participation by year by journal. The plots show, by paper publication year, the number of entries from each journal which have a software code registered in the ASCL.\n",
    "There is a bar for each journal which has an entry for that year. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# sort the dataframe by year\n",
    "code_by_journal_year_df = code_by_journal_year_df.sort_index()\n",
    "\n",
    "\n",
    "#print(type(code_by_journal_year_df.loc['2017']))\n",
    "\n",
    "#print(code_by_journal_year_df[code_by_journal_year_df > 5])\n",
    "\n",
    "\n",
    "# Plot each year in a separate graph\n",
    "for year, outerrow in code_by_journal_year_df.iterrows():\n",
    "    plt.title(year)\n",
    "    plt.xlabel('Journal')\n",
    "    plt.ylabel('Number of entries')\n",
    "    \n",
    "    series_to_plot = outerrow[outerrow.notna()]\n",
    "    series_to_plot.plot.bar()\n",
    "    plt.show()\n",
    "    \n",
    "# +++ this could be more interesting with a pie chart to show percentages\n",
    "# also, the y axis should all be integers here\n",
    "# also, the x axis has too many journal entries.  I know that most of them are negligible, I should enforce\n",
    "#       a minimum threshold"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Saving the keywords\n",
    "\n",
    "Now that we have all the keywords, save them to a text file.  This will be provided to the ASCL in order to update their records of the each code."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# save the keywords to a file\n",
    "f = open(\"ascl_keywords.txt\",\"w\")\n",
    "\n",
    "# write them in the format:\n",
    "# ascl_id: ['keyword1','keyword2','keyword3']\n",
    "for key, val in ascl_keywords_dict.items():\n",
    "    f.write(key)\n",
    "    f.write(':')\n",
    "    f.write(str(val))\n",
    "    f.write(\"\\n\")\n",
    "    \n",
    "f.close()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The keywords\n",
    "\n",
    "Here we display a small sample of the keywords found."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{   '1011.009': [   '25.75.-q',\n",
      "                    '25.75.Dw',\n",
      "                    '25.75.Gz',\n",
      "                    '25.75.Ld',\n",
      "                    '25.75.Nq',\n",
      "                    'Relativistic heavy-ion collisions',\n",
      "                    'Particle and resonance production'],\n",
      "    '1112.018': [],\n",
      "    '1208.016': [   'Methods: data analysis',\n",
      "                    'Methods: statistical',\n",
      "                    'Time',\n",
      "                    'Techniques: photometric',\n",
      "                    'binaries: eclipsing',\n",
      "                    'open clusters and associations: individual: M37',\n",
      "                    'stars: fundamental parameters',\n",
      "                    'stars: rotation'],\n",
      "    '1406.006': [],\n",
      "    '1708.030': []}\n"
     ]
    }
   ],
   "source": [
    "ascl_data_sample_keys = random.sample(list(ascl_keywords_dict), 5)\n",
    "ascl_keywords_dict = {k: ascl_keywords_dict[k] for k in ascl_data_sample_keys}\n",
    "\n",
    "pp = pprint.PrettyPrinter(indent=4)\n",
    "pp.pprint(ascl_keywords_dict)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusion\n",
    "\n",
    "This work does a large portion of the work necessary in order to fill in the keywords, which will enable better searching and recording of the software in the ASCL.\n",
    "\n",
    "There is still work to be done to finish gathering all the keywords.  Some of the references need to be manually analyzed.  The keywords may need to be cleaned.  For example, we may want to remove the keyword \"astrophysics\" as that is redundant in the context of the ASCL (\"Astrophysics Source Code Library\").  \n",
    "\n",
    "Further investigation could be done on the usage statistics, to see the journals which publish papers which cite software, or to see how software registration and citation changes with time.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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