test.ipynb

1-introducing-datasets.ipynb

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   "source": [
    "# The Datasets API: Features Overview\n",
    "\n",
    "This tutorial provides an overview of the [Datasets data source](https://docs.dimensions.ai/dsl/datasource-datasets.html) available via the [Dimensions Analytics API](https://docs.dimensions.ai/dsl/). \n",
    "\n",
    "The topics covered in this notebook are:\n",
    "\n",
    "* How to retrieve datasets metadata using the [search fields](https://docs.dimensions.ai/dsl/datasource-datasets.html) available\n",
    "* How to use the [schema API](https://docs.dimensions.ai/dsl/data-sources.html#metadata-api) to obtain some statistics about the Datasets data available (a standalone version of the charts generated in this section is also available online: [dataset fields overview ](http://api-sample-data.dimensions.ai/dataviz-exports/1-introducing-datasets/dataset-fields-overview.html) | [distribution of dataset fields per years](http://api-sample-data.dimensions.ai/dataviz-exports/1-introducing-datasets/dataset-fields-by-year-count.html) )."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "Collapsed": "false",
    "colab_type": "text",
    "id": "hMaQlB7DG8Vw"
   },
   "source": [
    "## Prerequisites\n",
    "\n",
    "This notebook assumes you have installed the [Dimcli](https://pypi.org/project/dimcli/) library and are familiar with the *Getting Started* tutorial.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
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     "data": {
      "text/html": [
       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "==\n",
      "Logging in..\n",
      "\u001b[2mDimcli - Dimensions API Client (v0.7.4.2)\u001b[0m\n",
      "\u001b[2mConnected to: https://app.dimensions.ai - DSL v1.27\u001b[0m\n",
      "\u001b[2mMethod: dsl.ini file\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "!pip install dimcli plotly tqdm -U --quiet \n",
    "\n",
    "import dimcli\n",
    "from dimcli.shortcuts import *\n",
    "import os, sys, time, json\n",
    "from tqdm.notebook import tqdm as progress\n",
    "import pandas as pd\n",
    "import plotly.express as px\n",
    "from plotly.offline import plot\n",
    "if not 'google.colab' in sys.modules:\n",
    "  # make js dependecies local / needed by html exports\n",
    "  from plotly.offline import init_notebook_mode\n",
    "  init_notebook_mode(connected=True)\n",
    "\n",
    "print(\"==\\nLogging in..\")\n",
    "# https://github.com/digital-science/dimcli#authentication\n",
    "ENDPOINT = \"https://app.dimensions.ai\"\n",
    "if 'google.colab' in sys.modules:\n",
    "  import getpass\n",
    "  USERNAME = getpass.getpass(prompt='Username: ')\n",
    "  PASSWORD = getpass.getpass(prompt='Password: ')    \n",
    "  dimcli.login(USERNAME, PASSWORD, ENDPOINT)\n",
    "else:\n",
    "  USERNAME, PASSWORD  = \"\", \"\"\n",
    "  dimcli.login(USERNAME, PASSWORD, ENDPOINT)\n",
    "dsl = dimcli.Dsl()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "Collapsed": "false",
    "colab_type": "text",
    "id": "Ie80RSRpLpUz"
   },
   "source": [
    "## 1. Sample Dataset Queries\n",
    "\n",
    "For the following queries, we will restrict our search using the keyword 'graphene'. You can of course change that, so to explore other topics too."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "Collapsed": "false",
    "colab": {},
    "colab_type": "code",
    "id": "guL7N-ieLf9H"
   },
   "outputs": [],
   "source": [
    "TOPIC = \"graphene\" #@param {type: \"string\"}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "Collapsed": "false",
    "colab_type": "text",
    "id": "nJU1GHK4LpU0"
   },
   "source": [
    "### Searching datasets by keyword\n",
    "\n",
    "We can easily discover datasets mentioning the keyword `graphene` and sorting them by most recent first. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "Collapsed": "false",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "tj-vWKW2LpU1",
    "outputId": "91e43a4c-3895-4645-83e2-a140bc9fa4b3"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Returned Datasets: 100 (total = 832)\n",
      "\u001b[2mTime: 0.62s\u001b[0m\n",
      "WARNINGS [1]\n",
      "Field 'license' is deprecated in favor of license_name. Please refer to https://docs.dimensions.ai/dsl/releasenotes.html for more details\n"
     ]
    }
   ],
   "source": [
    "df = dsl.query(f\"\"\"\n",
    "search datasets \n",
    "    in full_data for \"{TOPIC}\" \n",
    "return datasets[basics+license] \n",
    "    sort by date_created limit 100\n",
    "\"\"\").as_dataframe()"
   ]
  },
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   "execution_count": 4,
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    "colab_type": "code",
    "id": "IIk3--fUcATf",
    "outputId": "996f60fa-073d-41a0-a022-8bf1fc863f41"
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   "outputs": [
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       "         id                                           keywords  \\\n",
       "0  12900395  [wound dressing, biopolymer, pyocyanin, Pseudo...   \n",
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       "\n",
       "                                    license.url license.name  license.value  \\\n",
       "0  https://creativecommons.org/licenses/by/4.0/    CC BY 4.0              1   \n",
       "1  https://creativecommons.org/licenses/by/4.0/    CC BY 4.0              1   \n",
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    "df.head(3)"
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      "text/html": [
       "<div>\n",
       "        \n",
       "        \n",
       "            <div id=\"e6ba3620-d0b0-4d96-b3ee-6409e69cc239\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>\n",
       "            <script type=\"text/javascript\">\n",
       "                require([\"plotly\"], function(Plotly) {\n",
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     "metadata": {},
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   ],
   "source": [
    "px.pie(df, \n",
    "       names=\"license.name\", \n",
    "       title=f\"Share of different license of the 100 most recent datasets about '{TOPIC}'\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "Collapsed": "false",
    "colab_type": "text",
    "id": "mPFb8jyzLpU4"
   },
   "source": [
    "### Returning associated grants and publication data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "Collapsed": "false",
    "colab_type": "text",
    "id": "13MuQ3YKLpU5"
   },
   "source": [
    "Whenever the information about the publication associated to a dataset is available, it can be retrieved via the `associated_publication_id` field. Similarly, links between datasets and grants are exposed via the `associated_grant_ids` field. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
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     "height": 34
    },
    "colab_type": "code",
    "id": "4laaMLN7LpU6",
    "outputId": "429719c5-5ce6-42fe-cd9b-4ba872672220"
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Returned Datasets: 50 (total = 218)\n",
      "\u001b[2mTime: 0.63s\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "dfPubsAndGrants = dsl.query(f\"\"\"\n",
    "search datasets \n",
    "    in full_data for \"{TOPIC}\" \n",
    "    where associated_grant_ids is not empty\n",
    "    and  associated_publication_id is not empty\n",
    "return datasets[basics+associated_publication_id+associated_grant_ids+category_for] \n",
    "    sort by date_created desc limit 50\n",
    "\"\"\").as_dataframe()"
   ]
  },
  {
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       "      <td>Density Functional Theory Study of Single-Atom...</td>\n",
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       "      <td>Density Functional Theory Study of Single-Atom...</td>\n",
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       "             associated_grant_ids  \\\n",
       "0  [grant.2761799, grant.8158983]   \n",
       "1  [grant.7019622, grant.8145503]   \n",
       "2  [grant.7019622, grant.8145503]   \n",
       "\n",
       "                                               title  \\\n",
       "0  Supplementary information files for Probing th...   \n",
       "1  Density Functional Theory Study of Single-Atom...   \n",
       "2  Density Functional Theory Study of Single-Atom...   \n",
       "\n",
       "                                             authors  \\\n",
       "0  [{'name': 'Ya-Wei Zhou', 'orcid': ''}, {'name'...   \n",
       "1  [{'name': 'Chunjin Ren', 'orcid': ''}, {'name'...   \n",
       "2  [{'name': 'Chunjin Ren', 'orcid': ''}, {'name'...   \n",
       "\n",
       "  associated_publication_id  \\\n",
       "0            pub.1129903102   \n",
       "1            pub.1127742907   \n",
       "2            pub.1127742907   \n",
       "\n",
       "                                        category_for  year  \\\n",
       "0  [{'id': '2203', 'name': '03 Chemical Sciences'...  2020   \n",
       "1  [{'id': '2210', 'name': '10 Technology'}, {'id...  2020   \n",
       "2  [{'id': '2210', 'name': '10 Technology'}, {'id...  2020   \n",
       "\n",
       "                                            keywords        id    journal.id  \\\n",
       "0  [DFT calculations, spectroelectrochemistry, re...  12789110  jour.1039901   \n",
       "1  [SAC, N 2 H adsorption, g-C 3 N 4 nanosheet, N...  12326369  jour.1298581   \n",
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       "                       journal.title  \n",
       "0  Applied Catalysis B Environmental  \n",
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\"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"title\": {\"text\": \"Overiew of journals linked to the most recent 100 datasets about 'graphene'\"}, \"xaxis\": {\"anchor\": \"y\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"journal.title\"}}, \"yaxis\": {\"anchor\": \"x\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"count\"}}},\n",
       "                        {\"responsive\": true}\n",
       "                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('1e4bdda3-af71-49be-8740-704aa38c64b3');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })\n",
       "                };\n",
       "                });\n",
       "            </script>\n",
       "        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = px.histogram(dfPubsAndGrants.sort_values('journal.title'), \n",
    "                   x=\"journal.title\", \n",
    "                   barmode=\"group\", \n",
    "                   title=f\"Overiew of journals linked to the most recent 100 datasets about '{TOPIC}'\")\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "Collapsed": "false",
    "colab_type": "text",
    "id": "7YMh3PbMLpU9"
   },
   "source": [
    "### Searching using fielded search\n",
    "\n",
    "We can search for Datasets by using one or more [field filters](https://docs.dimensions.ai/dsl/datasource-datasets.html#datasets-fields). \n",
    "\n",
    "For example, we can filter by `journal`, using the most frequent journal from the dataframe created above. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "Collapsed": "false",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 907
    },
    "colab_type": "code",
    "id": "imsvTijHLpU9",
    "outputId": "685814a8-99e0-48e6-c209-7fdd12c96f02"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Returned Datasets: 10 (total = 35)\n",
      "\u001b[2mTime: 0.59s\u001b[0m\n"
     ]
    },
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>authors</th>\n",
       "      <th>title</th>\n",
       "      <th>doi</th>\n",
       "      <th>year</th>\n",
       "      <th>id</th>\n",
       "      <th>keywords</th>\n",
       "      <th>journal.id</th>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>[{'name': 'Xuan Zheng', 'orcid': ''}, {'name':...</td>\n",
       "      <td>Data_Sheet_1_Liquid Phase Exfoliated Hexagonal...</td>\n",
       "      <td>10.3389/fchem.2019.00544.s001</td>\n",
       "      <td>2019</td>\n",
       "      <td>9211262</td>\n",
       "      <td>[heterostructure, h-BN, graphene, asymmetric s...</td>\n",
       "      <td>jour.1049812</td>\n",
       "      <td>Frontiers in Chemistry</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>[{'name': 'Kaihe Lv', 'orcid': ''}, {'name': '...</td>\n",
       "      <td>Data_Sheet_1_Study of Janus Amphiphilic Graphe...</td>\n",
       "      <td>10.3389/fchem.2020.00201.s001</td>\n",
       "      <td>2020</td>\n",
       "      <td>12128463</td>\n",
       "      <td>[graphene oxide, Janus amphiphilic nano-sheets...</td>\n",
       "      <td>jour.1049812</td>\n",
       "      <td>Frontiers in Chemistry</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>[{'name': 'Hui Li', 'orcid': ''}, {'name': 'Ba...</td>\n",
       "      <td>Data_Sheet_1_Heterostructured SnO2-SnS2@C Embe...</td>\n",
       "      <td>10.3389/fchem.2019.00339.s001</td>\n",
       "      <td>2019</td>\n",
       "      <td>8121764</td>\n",
       "      <td>[SnO2-SnS2, heterostructure, nitrogen-doped gr...</td>\n",
       "      <td>jour.1049812</td>\n",
       "      <td>Frontiers in Chemistry</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>[{'name': 'Qunpeng Duan', 'orcid': ''}, {'name...</td>\n",
       "      <td>Data_Sheet_1_Facile One-Step Electrodeposition...</td>\n",
       "      <td>10.3389/fchem.2020.00430.s001</td>\n",
       "      <td>2020</td>\n",
       "      <td>12423572</td>\n",
       "      <td>[electrodeposition, pillar[6]arene, host-guest...</td>\n",
       "      <td>jour.1049812</td>\n",
       "      <td>Frontiers in Chemistry</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>[{'name': 'Jingjing Chen', 'orcid': ''}, {'nam...</td>\n",
       "      <td>Data_Sheet_1_Vitrimer Chemistry Assisted Fabri...</td>\n",
       "      <td>10.3389/fchem.2019.00632.s001</td>\n",
       "      <td>2019</td>\n",
       "      <td>9822770</td>\n",
       "      <td>[graphene nanoplate, vitrimer, composite, alig...</td>\n",
       "      <td>jour.1049812</td>\n",
       "      <td>Frontiers in Chemistry</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>[{'name': 'Hongwei Mi', 'orcid': ''}, {'name':...</td>\n",
       "      <td>Table_1_Carbothermal Synthesis of Nitrogen-Dop...</td>\n",
       "      <td>10.3389/fchem.2018.00501.s001</td>\n",
       "      <td>2018</td>\n",
       "      <td>7234382</td>\n",
       "      <td>[liquid-polyacrylonitrile (LPAN), carbothermal...</td>\n",
       "      <td>jour.1049812</td>\n",
       "      <td>Frontiers in Chemistry</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>[{'name': 'Wei Zhang', 'orcid': ''}, {'name': ...</td>\n",
       "      <td>Table_1_Pyrite-Type CoS2 Nanoparticles Support...</td>\n",
       "      <td>10.3389/fchem.2018.00569.s001</td>\n",
       "      <td>2018</td>\n",
       "      <td>7368707</td>\n",
       "      <td>[water splitting, cobalt sulfide, nanoparticle...</td>\n",
       "      <td>jour.1049812</td>\n",
       "      <td>Frontiers in Chemistry</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>[{'name': 'Dan-Dan Zhang', 'orcid': ''}, {'nam...</td>\n",
       "      <td>Data_Sheet_1_Perovskite-WS2 Nanosheet Composit...</td>\n",
       "      <td>10.3389/fchem.2019.00257.s001</td>\n",
       "      <td>2019</td>\n",
       "      <td>8094617</td>\n",
       "      <td>[reduced graphene oxide, perovskite, WS2, bulk...</td>\n",
       "      <td>jour.1049812</td>\n",
       "      <td>Frontiers in Chemistry</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>[{'name': 'Xiaoyu Song', 'orcid': ''}, {'name'...</td>\n",
       "      <td>Table_1_Deep Eutectic Solvent Micro-Functional...</td>\n",
       "      <td>10.3389/fchem.2019.00594.s001</td>\n",
       "      <td>2019</td>\n",
       "      <td>9725681</td>\n",
       "      <td>[deep eutectic solvent, graphene, dispersive m...</td>\n",
       "      <td>jour.1049812</td>\n",
       "      <td>Frontiers in Chemistry</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>[{'name': 'Emilie Bordes', 'orcid': ''}, {'nam...</td>\n",
       "      <td>Data_Sheet_1_Dispersion and Stabilization of E...</td>\n",
       "      <td>10.3389/fchem.2019.00223.s001</td>\n",
       "      <td>2019</td>\n",
       "      <td>7998800</td>\n",
       "      <td>[exfoliation, graphene, graphite, ionic liquid...</td>\n",
       "      <td>jour.1049812</td>\n",
       "      <td>Frontiers in Chemistry</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             authors  \\\n",
       "0  [{'name': 'Xuan Zheng', 'orcid': ''}, {'name':...   \n",
       "1  [{'name': 'Kaihe Lv', 'orcid': ''}, {'name': '...   \n",
       "2  [{'name': 'Hui Li', 'orcid': ''}, {'name': 'Ba...   \n",
       "3  [{'name': 'Qunpeng Duan', 'orcid': ''}, {'name...   \n",
       "4  [{'name': 'Jingjing Chen', 'orcid': ''}, {'nam...   \n",
       "5  [{'name': 'Hongwei Mi', 'orcid': ''}, {'name':...   \n",
       "6  [{'name': 'Wei Zhang', 'orcid': ''}, {'name': ...   \n",
       "7  [{'name': 'Dan-Dan Zhang', 'orcid': ''}, {'nam...   \n",
       "8  [{'name': 'Xiaoyu Song', 'orcid': ''}, {'name'...   \n",
       "9  [{'name': 'Emilie Bordes', 'orcid': ''}, {'nam...   \n",
       "\n",
       "                                               title  \\\n",
       "0  Data_Sheet_1_Liquid Phase Exfoliated Hexagonal...   \n",
       "1  Data_Sheet_1_Study of Janus Amphiphilic Graphe...   \n",
       "2  Data_Sheet_1_Heterostructured SnO2-SnS2@C Embe...   \n",
       "3  Data_Sheet_1_Facile One-Step Electrodeposition...   \n",
       "4  Data_Sheet_1_Vitrimer Chemistry Assisted Fabri...   \n",
       "5  Table_1_Carbothermal Synthesis of Nitrogen-Dop...   \n",
       "6  Table_1_Pyrite-Type CoS2 Nanoparticles Support...   \n",
       "7  Data_Sheet_1_Perovskite-WS2 Nanosheet Composit...   \n",
       "8  Table_1_Deep Eutectic Solvent Micro-Functional...   \n",
       "9  Data_Sheet_1_Dispersion and Stabilization of E...   \n",
       "\n",
       "                             doi  year        id  \\\n",
       "0  10.3389/fchem.2019.00544.s001  2019   9211262   \n",
       "1  10.3389/fchem.2020.00201.s001  2020  12128463   \n",
       "2  10.3389/fchem.2019.00339.s001  2019   8121764   \n",
       "3  10.3389/fchem.2020.00430.s001  2020  12423572   \n",
       "4  10.3389/fchem.2019.00632.s001  2019   9822770   \n",
       "5  10.3389/fchem.2018.00501.s001  2018   7234382   \n",
       "6  10.3389/fchem.2018.00569.s001  2018   7368707   \n",
       "7  10.3389/fchem.2019.00257.s001  2019   8094617   \n",
       "8  10.3389/fchem.2019.00594.s001  2019   9725681   \n",
       "9  10.3389/fchem.2019.00223.s001  2019   7998800   \n",
       "\n",
       "                                            keywords    journal.id  \\\n",
       "0  [heterostructure, h-BN, graphene, asymmetric s...  jour.1049812   \n",
       "1  [graphene oxide, Janus amphiphilic nano-sheets...  jour.1049812   \n",
       "2  [SnO2-SnS2, heterostructure, nitrogen-doped gr...  jour.1049812   \n",
       "3  [electrodeposition, pillar[6]arene, host-guest...  jour.1049812   \n",
       "4  [graphene nanoplate, vitrimer, composite, alig...  jour.1049812   \n",
       "5  [liquid-polyacrylonitrile (LPAN), carbothermal...  jour.1049812   \n",
       "6  [water splitting, cobalt sulfide, nanoparticle...  jour.1049812   \n",
       "7  [reduced graphene oxide, perovskite, WS2, bulk...  jour.1049812   \n",
       "8  [deep eutectic solvent, graphene, dispersive m...  jour.1049812   \n",
       "9  [exfoliation, graphene, graphite, ionic liquid...  jour.1049812   \n",
       "\n",
       "            journal.title  \n",
       "0  Frontiers in Chemistry  \n",
       "1  Frontiers in Chemistry  \n",
       "2  Frontiers in Chemistry  \n",
       "3  Frontiers in Chemistry  \n",
       "4  Frontiers in Chemistry  \n",
       "5  Frontiers in Chemistry  \n",
       "6  Frontiers in Chemistry  \n",
       "7  Frontiers in Chemistry  \n",
       "8  Frontiers in Chemistry  \n",
       "9  Frontiers in Chemistry  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "topjournal = dfPubsAndGrants['journal.id'].value_counts().idxmax()\n",
    "\n",
    "dsl.query(f\"\"\"\n",
    "search datasets \n",
    "    in full_data for \"{TOPIC}\"\n",
    "    where journal.id=\"{topjournal}\"\n",
    "return datasets[basics+doi] limit 10\n",
    "\"\"\").as_dataframe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "Collapsed": "false",
    "colab_type": "text",
    "id": "Tdvs5VoyPl2J"
   },
   "source": [
    "### Extracting related funding via grants "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "Collapsed": "false",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "ntcYjR-ROdMJ",
    "outputId": "c7620713-5641-4ed2-cffe-2e06f1a942ec"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Returned Grants: 66 (total = 66)\n",
      "\u001b[2mTime: 0.56s\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "# get unique list of associated grant IDs\n",
    "grantids = list()\n",
    "for g in dfPubsAndGrants['associated_grant_ids'].to_list():\n",
    "  grantids += g\n",
    "grantids = list(set(grantids))\n",
    "\n",
    "# get more grants data from IDs\n",
    "dfgrants = dsl.query(f\"\"\"search grants \n",
    "                      where id in {json.dumps(grantids)} \n",
    "                   return grants[id+funding_org_name+funder_countries+funding_eur] limit 1000 \"\"\").as_dataframe()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "Collapsed": "false",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 193
    },
    "colab_type": "code",
    "id": "F9lHNPS6cAUf",
    "outputId": "2000a892-46e8-4941-9d00-548b033fe410"
   },
   "outputs": [
    {
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       "      <td>European Research Council</td>\n",
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       "      <th>1</th>\n",
       "      <td>Office of the Director</td>\n",
       "      <td>224831.0</td>\n",
       "      <td>[{'id': 'US', 'name': 'United States'}]</td>\n",
       "      <td>grant.7569828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Japan Society for the Promotion of Science</td>\n",
       "      <td>139549.0</td>\n",
       "      <td>[{'id': 'JP', 'name': 'Japan'}]</td>\n",
       "      <td>grant.7521593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>National Natural Science Foundation of China</td>\n",
       "      <td>82360.0</td>\n",
       "      <td>[{'id': 'CN', 'name': 'China'}]</td>\n",
       "      <td>grant.8133465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>National Natural Science Foundation of China</td>\n",
       "      <td>56617.0</td>\n",
       "      <td>[{'id': 'CN', 'name': 'China'}]</td>\n",
       "      <td>grant.8132071</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
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       "                               funding_org_name  funding_eur  \\\n",
       "0                     European Research Council    2000000.0   \n",
       "1                        Office of the Director     224831.0   \n",
       "2    Japan Society for the Promotion of Science     139549.0   \n",
       "3  National Natural Science Foundation of China      82360.0   \n",
       "4  National Natural Science Foundation of China      56617.0   \n",
       "\n",
       "                          funder_countries             id  \n",
       "0        [{'id': 'BE', 'name': 'Belgium'}]  grant.8104355  \n",
       "1  [{'id': 'US', 'name': 'United States'}]  grant.7569828  \n",
       "2          [{'id': 'JP', 'name': 'Japan'}]  grant.7521593  \n",
       "3          [{'id': 'CN', 'name': 'China'}]  grant.8133465  \n",
       "4          [{'id': 'CN', 'name': 'China'}]  grant.8132071  "
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    "                   barmode=\"group\", \n",
    "                   title=f\"Number of datasets (about '{TOPIC}') per funder\")\n",
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     "metadata": {},
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   ],
   "source": [
    "fig = px.bar(dfgrants, \n",
    "             x=\"funding_org_name\", y=\"funding_eur\", \n",
    "             barmode=\"group\", \n",
    "             title=f\"Funders by funding amount and number of grants (for datasets about '{TOPIC}')\")\n",
    "fig.show()"
   ]
  },
  {
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   "execution_count": 14,
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     "base_uri": "https://localhost:8080/",
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    "colab_type": "code",
    "id": "iOsuH2DocAUz",
    "outputId": "94dc0095-b2da-4b42-9d99-a6bb9b52fdd7"
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   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>funding_org_name</th>\n",
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       "      <th>id</th>\n",
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       "      <th>61</th>\n",
       "      <td>Directorate for Engineering</td>\n",
       "      <td>35986896.0</td>\n",
       "      <td>[{'id': 'US', 'name': 'United States'}]</td>\n",
       "      <td>grant.3106944</td>\n",
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       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>National Institute of General Medical Sciences</td>\n",
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       "      <th>0</th>\n",
       "      <td>European Research Council</td>\n",
       "      <td>2000000.0</td>\n",
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       "                                  funding_org_name  funding_eur  \\\n",
       "61                     Directorate for Engineering   35986896.0   \n",
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       "0                        European Research Council    2000000.0   \n",
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       "25                       European Research Council    1499925.0   \n",
       "\n",
       "                           funder_countries             id  \n",
       "61  [{'id': 'US', 'name': 'United States'}]  grant.3106944  \n",
       "65  [{'id': 'US', 'name': 'United States'}]  grant.2439760  \n",
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       "41  [{'id': 'US', 'name': 'United States'}]  grant.6377824  \n",
       "25        [{'id': 'BE', 'name': 'Belgium'}]  grant.6447261  "
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     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfgrants.sort_values('funding_eur',ascending=False).head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "Collapsed": "false",
    "colab_type": "text",
    "id": "8pF1J2KELpVB"
   },
   "source": [
    "### Aggregating results using facets"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "Collapsed": "false",
    "colab_type": "text",
    "id": "pY2O2rynLpVB"
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   "source": [
    "Datasets results can be grouped using facets. E.g. we can see what are the top `funders`, `research organizations` or  `researchers` related to our datasets (note: the column 'count' represents the number of dataset records in each of the groups)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "Collapsed": "false",
    "colab_type": "text",
    "id": "K2o4_pZoLpVC"
   },
   "source": [
    "#### Top funders"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "Collapsed": "false",
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     "base_uri": "https://localhost:8080/",
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    "colab_type": "code",
    "id": "PlSgLGiPLpVD",
    "outputId": "c5e784d1-d757-4058-e4b0-5d7b7ea8ff75"
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Returned Funders: 100\n",
      "\u001b[2mTime: 0.50s\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "df = dsl.query(f\"\"\"\n",
    "search datasets \n",
    "    in full_data for \"{TOPIC}\" \n",
    "return funders limit 100\n",
    "\"\"\").as_dataframe()"
   ]
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   "execution_count": 16,
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    "id": "nfU-A8dXcAVM",
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       "\n",
       "                                               name   country_name  city_name  \\\n",
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       "1                               European Commission        Belgium   Brussels   \n",
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       "2   Virginia  "
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     },
     "metadata": {},
     "output_type": "display_data"
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   ],
   "source": [
    "px.scatter(df, \n",
    "           x=\"count\", y=\"name\",\n",
    "           marginal_x=\"histogram\", marginal_y=\"histogram\",\n",
    "           title=f\"Top funder referenced in datasets about '{TOPIC}', all time\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "Collapsed": "false",
    "colab_type": "text",
    "id": "Z2W07IjOLpVG"
   },
   "source": [
    "#### Top research organizations\n",
    "\n",
    "Note: research organizations are linked to datasets via the datasets' associated publication. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "Collapsed": "false",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
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    "colab_type": "code",
    "id": "YvsBY1mTLpVG",
    "outputId": "8d21fcf6-b513-4304-c0a6-7ddc516d77ee"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Returned Research_orgs: 10\n",
      "\u001b[2mTime: 0.46s\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "df = dsl.query(f\"\"\"\n",
    "search datasets \n",
    "    in full_data for \"{TOPIC}\" \n",
    "return research_orgs limit 10\n",
    "\"\"\").as_dataframe()"
   ]
  },
  {
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   "execution_count": 19,
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    "id": "gOetidugcAVj",
    "outputId": "9d9c4d1b-2040-4f57-8b70-30fd179ce76a"
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   "outputs": [
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       "      <td>grid.10347.31</td>\n",
       "      <td>24</td>\n",
       "      <td>101.656390</td>\n",
       "      <td>Kuala Lumpur</td>\n",
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       "      <td>Malaysia</td>\n",
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       "      <td>3.120833</td>\n",
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       "      <td>UM</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>grid.418028.7</td>\n",
       "      <td>16</td>\n",
       "      <td>13.283713</td>\n",
       "      <td>Berlin</td>\n",
       "      <td>[Facility]</td>\n",
       "      <td>Germany</td>\n",
       "      <td>Fritz Haber Institute of the Max Planck Society</td>\n",
       "      <td>52.448765</td>\n",
       "      <td>[http://www.fhi-berlin.mpg.de/]</td>\n",
       "      <td>FHI</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>grid.34555.32</td>\n",
       "      <td>15</td>\n",
       "      <td>30.511314</td>\n",
       "      <td>Kyiv</td>\n",
       "      <td>[Education]</td>\n",
       "      <td>Ukraine</td>\n",
       "      <td>Taras Shevchenko National University of Kyiv</td>\n",
       "      <td>50.441902</td>\n",
       "      <td>[http://www.univ.kiev.ua/en/]</td>\n",
       "      <td>KNU</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>grid.263333.4</td>\n",
       "      <td>12</td>\n",
       "      <td>127.073890</td>\n",
       "      <td>Seoul</td>\n",
       "      <td>[Education]</td>\n",
       "      <td>South Korea</td>\n",
       "      <td>Sejong University</td>\n",
       "      <td>37.550835</td>\n",
       "      <td>[http://www.sejong.ac.kr/]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>grid.264756.4</td>\n",
       "      <td>12</td>\n",
       "      <td>-96.344055</td>\n",
       "      <td>College Station</td>\n",
       "      <td>[Education]</td>\n",
       "      <td>United States</td>\n",
       "      <td>Texas A&amp;M University</td>\n",
       "      <td>30.610369</td>\n",
       "      <td>[https://www.tamu.edu/]</td>\n",
       "      <td>TAMU</td>\n",
       "      <td>Texas</td>\n",
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       "              id  count   longitude        city_name        types  \\\n",
       "0  grid.10347.31     24  101.656390     Kuala Lumpur  [Education]   \n",
       "1  grid.418028.7     16   13.283713           Berlin   [Facility]   \n",
       "2  grid.34555.32     15   30.511314             Kyiv  [Education]   \n",
       "3  grid.263333.4     12  127.073890            Seoul  [Education]   \n",
       "4  grid.264756.4     12  -96.344055  College Station  [Education]   \n",
       "\n",
       "    country_name                                             name   latitude  \\\n",
       "0       Malaysia                             University of Malaya   3.120833   \n",
       "1        Germany  Fritz Haber Institute of the Max Planck Society  52.448765   \n",
       "2        Ukraine     Taras Shevchenko National University of Kyiv  50.441902   \n",
       "3    South Korea                                Sejong University  37.550835   \n",
       "4  United States                             Texas A&M University  30.610369   \n",
       "\n",
       "                           linkout acronym state_name  \n",
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       "4          [https://www.tamu.edu/]    TAMU      Texas  "
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   ],
   "source": [
    "px.pie(df, \n",
    "       names=\"country_name\",\n",
    "       title=f\"Global distribution of research organisations linked to datasets about '{TOPIC}'\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "Collapsed": "false",
    "colab_type": "text",
    "id": "bRujIwMDLpVJ"
   },
   "source": [
    "#### Top contributors\n",
    "\n",
    "Note: researchers are linked to datasets via the datasets' associated publication. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
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     "base_uri": "https://localhost:8080/",
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    "outputId": "7606b624-e13c-4a73-80df-efa54f31174a"
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Returned Researchers: 10\n",
      "\u001b[2mTime: 0.58s\u001b[0m\n"
     ]
    },
    {
     "data": {
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       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>count</th>\n",
       "      <th>last_name</th>\n",
       "      <th>research_orgs</th>\n",
       "      <th>first_name</th>\n",
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       "      <th>0</th>\n",
       "      <td>ur.01046566370.94</td>\n",
       "      <td>15</td>\n",
       "      <td>Frank</td>\n",
       "      <td>[grid.418028.7, grid.6734.6]</td>\n",
       "      <td>Benjamin</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>1</th>\n",
       "      <td>ur.01333027111.96</td>\n",
       "      <td>15</td>\n",
       "      <td>Schlögl</td>\n",
       "      <td>[grid.5018.c, grid.5398.7, grid.5335.0, grid.4...</td>\n",
       "      <td>Robert</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ur.01347070166.03</td>\n",
       "      <td>15</td>\n",
       "      <td>Khavryuchenko</td>\n",
       "      <td>[grid.440789.6, grid.418028.7, grid.34555.32, ...</td>\n",
       "      <td>Oleksiy V</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ur.013720757463.40</td>\n",
       "      <td>15</td>\n",
       "      <td>Hermann</td>\n",
       "      <td>[grid.424048.e, grid.481551.c, grid.7450.6, gr...</td>\n",
       "      <td>Klaus E</td>\n",
       "      <td>[0000-0002-3861-3916]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ur.0714064131.80</td>\n",
       "      <td>15</td>\n",
       "      <td>Trunschke</td>\n",
       "      <td>[grid.418028.7, grid.4372.2, grid.440957.b, gr...</td>\n",
       "      <td>Annette</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ur.010553550461.38</td>\n",
       "      <td>12</td>\n",
       "      <td>Rezania</td>\n",
       "      <td>[grid.410877.d, grid.31501.36, grid.263333.4]</td>\n",
       "      <td>Shahabaldin</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
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       "      <td>12</td>\n",
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       "      <td>[grid.411705.6, grid.444858.1]</td>\n",
       "      <td>Seyedeh Solmaz</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>ur.012742050435.43</td>\n",
       "      <td>12</td>\n",
       "      <td>Nezhad</td>\n",
       "      <td>[grid.411583.a]</td>\n",
       "      <td>Nahid Tavakkoli</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>ur.013616637374.40</td>\n",
       "      <td>12</td>\n",
       "      <td>Ghadiri</td>\n",
       "      <td>[grid.411705.6, grid.444858.1]</td>\n",
       "      <td>Seid Kamal</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>ur.015117735007.22</td>\n",
       "      <td>12</td>\n",
       "      <td>Shams</td>\n",
       "      <td>[grid.411924.b, grid.411583.a, grid.411705.6]</td>\n",
       "      <td>Mahmoud</td>\n",
       "      <td>[0000-0002-2222-9792]</td>\n",
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      "text/plain": [
       "                   id  count      last_name  \\\n",
       "0   ur.01046566370.94     15          Frank   \n",
       "1   ur.01333027111.96     15        Schlögl   \n",
       "2   ur.01347070166.03     15  Khavryuchenko   \n",
       "3  ur.013720757463.40     15        Hermann   \n",
       "4    ur.0714064131.80     15      Trunschke   \n",
       "5  ur.010553550461.38     12        Rezania   \n",
       "6   ur.01230367167.34     12         Talebi   \n",
       "7  ur.012742050435.43     12         Nezhad   \n",
       "8  ur.013616637374.40     12        Ghadiri   \n",
       "9  ur.015117735007.22     12          Shams   \n",
       "\n",
       "                                       research_orgs       first_name  \\\n",
       "0                       [grid.418028.7, grid.6734.6]         Benjamin   \n",
       "1  [grid.5018.c, grid.5398.7, grid.5335.0, grid.4...           Robert   \n",
       "2  [grid.440789.6, grid.418028.7, grid.34555.32, ...        Oleksiy V   \n",
       "3  [grid.424048.e, grid.481551.c, grid.7450.6, gr...          Klaus E   \n",
       "4  [grid.418028.7, grid.4372.2, grid.440957.b, gr...          Annette   \n",
       "5      [grid.410877.d, grid.31501.36, grid.263333.4]      Shahabaldin   \n",
       "6                     [grid.411705.6, grid.444858.1]   Seyedeh Solmaz   \n",
       "7                                    [grid.411583.a]  Nahid Tavakkoli   \n",
       "8                     [grid.411705.6, grid.444858.1]       Seid Kamal   \n",
       "9      [grid.411924.b, grid.411583.a, grid.411705.6]          Mahmoud   \n",
       "\n",
       "                orcid_id  \n",
       "0                    NaN  \n",
       "1                    NaN  \n",
       "2                    NaN  \n",
       "3  [0000-0002-3861-3916]  \n",
       "4                    NaN  \n",
       "5  [0000-0001-8943-3045]  \n",
       "6                    NaN  \n",
       "7                    NaN  \n",
       "8                    NaN  \n",
       "9  [0000-0002-2222-9792]  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dsl.query(f\"\"\"\n",
    "search datasets \n",
    "    in full_data for \"{TOPIC}\" \n",
    "return researchers limit 10\n",
    "\"\"\").as_dataframe()"
   ]
  },
  {
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   "metadata": {
    "Collapsed": "false",
    "colab_type": "text",
    "id": "hcg2KOswd2F4"
   },
   "source": [
    "## 2. A closer look at Datasets statistics\n",
    "\n",
    "The Dimensions Search Language [exposes programmatically metadata](https://docs.dimensions.ai/dsl/data-sources.html#metadata-api), such as supported sources and entities, along with their fields, facets, fieldsets, metrics and search fields. \n"
   ]
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   },
   "outputs": [
    {
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       "      <td>datasets</td>\n",
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       "      <td>`HRCS - Health Categories &lt;https://app.dimensi...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>datasets</td>\n",
       "      <td>category_hrcs_rac</td>\n",
       "      <td>categories</td>\n",
       "      <td>`HRCS – Research Activity Codes &lt;https://app.d...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>datasets</td>\n",
       "      <td>category_icrp_cso</td>\n",
       "      <td>categories</td>\n",
       "      <td>`ICRP Common Scientific Outline &lt;https://app.d...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>datasets</td>\n",
       "      <td>category_icrp_ct</td>\n",
       "      <td>categories</td>\n",
       "      <td>`ICRP Cancer Types &lt;https://app.dimensions.ai/...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>datasets</td>\n",
       "      <td>category_rcdc</td>\n",
       "      <td>categories</td>\n",
       "      <td>`Research, Condition, and Disease Categorizati...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>datasets</td>\n",
       "      <td>category_sdg</td>\n",
       "      <td>categories</td>\n",
       "      <td>SDG - Sustainable Development Goals</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>datasets</td>\n",
       "      <td>date</td>\n",
       "      <td>date</td>\n",
       "      <td>The publication date of the dataset, eg \"2018-...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>datasets</td>\n",
       "      <td>date_created</td>\n",
       "      <td>date</td>\n",
       "      <td>The creation date of the dataset.</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>datasets</td>\n",
       "      <td>date_embargo</td>\n",
       "      <td>date</td>\n",
       "      <td>The embargo date of the dataset.</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>datasets</td>\n",
       "      <td>date_inserted</td>\n",
       "      <td>date</td>\n",
       "      <td>Date when the record was inserted into Dimensi...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>datasets</td>\n",
       "      <td>date_modified</td>\n",
       "      <td>date</td>\n",
       "      <td>The last modification date of the dataset.</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>datasets</td>\n",
       "      <td>description</td>\n",
       "      <td>string</td>\n",
       "      <td>Description of the dataset.</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>datasets</td>\n",
       "      <td>dimensions_url</td>\n",
       "      <td>string</td>\n",
       "      <td>Link pointing to the Dimensions web application</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>datasets</td>\n",
       "      <td>doi</td>\n",
       "      <td>string</td>\n",
       "      <td>Dataset DOI.</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>datasets</td>\n",
       "      <td>figshare_url</td>\n",
       "      <td>string</td>\n",
       "      <td>Figshare URL for the dataset.</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>datasets</td>\n",
       "      <td>funder_countries</td>\n",
       "      <td>countries</td>\n",
       "      <td>The country linked to the organisation funding...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>datasets</td>\n",
       "      <td>funders</td>\n",
       "      <td>organizations</td>\n",
       "      <td>The GRID organisations funding the dataset.</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>datasets</td>\n",
       "      <td>id</td>\n",
       "      <td>string</td>\n",
       "      <td>Dimensions dataset ID.</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>datasets</td>\n",
       "      <td>journal</td>\n",
       "      <td>journals</td>\n",
       "      <td>The journal a data set belongs to.</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>datasets</td>\n",
       "      <td>keywords</td>\n",
       "      <td>string</td>\n",
       "      <td>Keywords used to describe the dataset (from au...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>datasets</td>\n",
       "      <td>language_desc</td>\n",
       "      <td>string</td>\n",
       "      <td>Dataset title language, as ISO 639-1 language ...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>datasets</td>\n",
       "      <td>language_title</td>\n",
       "      <td>string</td>\n",
       "      <td>Dataset title language, as ISO 639-1 language ...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>datasets</td>\n",
       "      <td>license_name</td>\n",
       "      <td>string</td>\n",
       "      <td>The dataset licence name, e.g. 'CC BY 4.0'.</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>datasets</td>\n",
       "      <td>license_url</td>\n",
       "      <td>string</td>\n",
       "      <td>The dataset licence URL, e.g. 'https://creativ...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>datasets</td>\n",
       "      <td>repository_id</td>\n",
       "      <td>string</td>\n",
       "      <td>The ID of the repository of the dataset.</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>datasets</td>\n",
       "      <td>research_org_cities</td>\n",
       "      <td>cities</td>\n",
       "      <td>City of the organisations the publication auth...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>datasets</td>\n",
       "      <td>research_org_countries</td>\n",
       "      <td>countries</td>\n",
       "      <td>Country of the organisations the publication a...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>datasets</td>\n",
       "      <td>research_org_states</td>\n",
       "      <td>states</td>\n",
       "      <td>State of the organisations the publication aut...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>datasets</td>\n",
       "      <td>research_orgs</td>\n",
       "      <td>organizations</td>\n",
       "      <td>GRID organisations linked to the publication a...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>datasets</td>\n",
       "      <td>researchers</td>\n",
       "      <td>researchers</td>\n",
       "      <td>Dimensions researchers IDs associated to the d...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>datasets</td>\n",
       "      <td>title</td>\n",
       "      <td>string</td>\n",
       "      <td>Title of the dataset.</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>datasets</td>\n",
       "      <td>year</td>\n",
       "      <td>integer</td>\n",
       "      <td>Year of publication of the dataset.</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     sources                      field               type  \\\n",
       "0   datasets       associated_grant_ids             string   \n",
       "1   datasets     associated_publication  publication_links   \n",
       "2   datasets  associated_publication_id             string   \n",
       "3   datasets                    authors               json   \n",
       "4   datasets               category_bra         categories   \n",
       "5   datasets               category_for         categories   \n",
       "6   datasets               category_hra         categories   \n",
       "7   datasets           category_hrcs_hc         categories   \n",
       "8   datasets          category_hrcs_rac         categories   \n",
       "9   datasets          category_icrp_cso         categories   \n",
       "10  datasets           category_icrp_ct         categories   \n",
       "11  datasets              category_rcdc         categories   \n",
       "12  datasets               category_sdg         categories   \n",
       "13  datasets                       date               date   \n",
       "14  datasets               date_created               date   \n",
       "15  datasets               date_embargo               date   \n",
       "16  datasets              date_inserted               date   \n",
       "17  datasets              date_modified               date   \n",
       "18  datasets                description             string   \n",
       "19  datasets             dimensions_url             string   \n",
       "20  datasets                        doi             string   \n",
       "21  datasets               figshare_url             string   \n",
       "22  datasets           funder_countries          countries   \n",
       "23  datasets                    funders      organizations   \n",
       "24  datasets                         id             string   \n",
       "25  datasets                    journal           journals   \n",
       "26  datasets                   keywords             string   \n",
       "27  datasets              language_desc             string   \n",
       "28  datasets             language_title             string   \n",
       "29  datasets               license_name             string   \n",
       "30  datasets                license_url             string   \n",
       "31  datasets              repository_id             string   \n",
       "32  datasets        research_org_cities             cities   \n",
       "33  datasets     research_org_countries          countries   \n",
       "34  datasets        research_org_states             states   \n",
       "35  datasets              research_orgs      organizations   \n",
       "36  datasets                researchers        researchers   \n",
       "37  datasets                      title             string   \n",
       "38  datasets                       year            integer   \n",
       "\n",
       "                                          description  is_filter  is_entity  \\\n",
       "0   The Dimensions IDs of the grants linked to the...       True      False   \n",
       "1   Publication linked to the dataset (single value).       True       True   \n",
       "2   The Dimensions ID of the publication linked to...       True      False   \n",
       "3   Ordered list of the dataset authors. ORCIDs ar...       True      False   \n",
       "4   `Broad Research Areas <https://app.dimensions....       True       True   \n",
       "5   `ANZSRC Fields of Research classification <htt...       True       True   \n",
       "6   `Health Research Areas <https://app.dimensions...       True       True   \n",
       "7   `HRCS - Health Categories <https://app.dimensi...       True       True   \n",
       "8   `HRCS – Research Activity Codes <https://app.d...       True       True   \n",
       "9   `ICRP Common Scientific Outline <https://app.d...       True       True   \n",
       "10  `ICRP Cancer Types <https://app.dimensions.ai/...       True       True   \n",
       "11  `Research, Condition, and Disease Categorizati...       True       True   \n",
       "12                SDG - Sustainable Development Goals       True       True   \n",
       "13  The publication date of the dataset, eg \"2018-...       True      False   \n",
       "14                  The creation date of the dataset.       True      False   \n",
       "15                   The embargo date of the dataset.       True      False   \n",
       "16  Date when the record was inserted into Dimensi...       True      False   \n",
       "17         The last modification date of the dataset.       True      False   \n",
       "18                        Description of the dataset.      False      False   \n",
       "19    Link pointing to the Dimensions web application      False      False   \n",
       "20                                       Dataset DOI.       True      False   \n",
       "21                      Figshare URL for the dataset.      False      False   \n",
       "22  The country linked to the organisation funding...       True       True   \n",
       "23        The GRID organisations funding the dataset.       True       True   \n",
       "24                             Dimensions dataset ID.       True      False   \n",
       "25                 The journal a data set belongs to.       True       True   \n",
       "26  Keywords used to describe the dataset (from au...       True      False   \n",
       "27  Dataset title language, as ISO 639-1 language ...       True      False   \n",
       "28  Dataset title language, as ISO 639-1 language ...       True      False   \n",
       "29        The dataset licence name, e.g. 'CC BY 4.0'.       True      False   \n",
       "30  The dataset licence URL, e.g. 'https://creativ...      False      False   \n",
       "31           The ID of the repository of the dataset.       True      False   \n",
       "32  City of the organisations the publication auth...       True       True   \n",
       "33  Country of the organisations the publication a...       True       True   \n",
       "34  State of the organisations the publication aut...       True       True   \n",
       "35  GRID organisations linked to the publication a...       True       True   \n",
       "36  Dimensions researchers IDs associated to the d...       True       True   \n",
       "37                              Title of the dataset.      False      False   \n",
       "38                Year of publication of the dataset.       True      False   \n",
       "\n",
       "    is_facet  \n",
       "0      False  \n",
       "1       True  \n",
       "2      False  \n",
       "3      False  \n",
       "4       True  \n",
       "5       True  \n",
       "6       True  \n",
       "7       True  \n",
       "8       True  \n",
       "9       True  \n",
       "10      True  \n",
       "11      True  \n",
       "12      True  \n",
       "13     False  \n",
       "14     False  \n",
       "15     False  \n",
       "16     False  \n",
       "17     False  \n",
       "18     False  \n",
       "19     False  \n",
       "20     False  \n",
       "21     False  \n",
       "22      True  \n",
       "23      True  \n",
       "24     False  \n",
       "25      True  \n",
       "26      True  \n",
       "27      True  \n",
       "28      True  \n",
       "29      True  \n",
       "30     False  \n",
       "31      True  \n",
       "32      True  \n",
       "33      True  \n",
       "34      True  \n",
       "35      True  \n",
       "36      True  \n",
       "37     False  \n",
       "38      True  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%dsldocs datasets"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "Collapsed": "false",
    "colab_type": "text",
    "id": "foyjbGHSLpVP"
   },
   "source": [
    "The fields list shown above can be extracted via the following DSL query:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "Collapsed": "false",
    "colab": {},
    "colab_type": "code",
    "id": "dwQmPCr1LpVQ"
   },
   "outputs": [],
   "source": [
    "data = dsl.query(\"\"\"describe source datasets\"\"\")\n",
    "fields = sorted([x for x in data.fields.keys()])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "Collapsed": "false",
    "colab_type": "text",
    "id": "PhARWrB-LpVS"
   },
   "source": [
    "### Counting records per each field\n",
    "\n",
    "By using the fields list obtained above, it is possible to draw up some general statistics re. the Datasets content type in Dimensions.\n",
    "\n",
    "In order to do this, we  use the operator `is not empty` to generate automatically queries like this `search datasets where {field_name} is not empty return datasets limit 1` and then use the `total_count` field in the JSON we get back for our statistics. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "Collapsed": "false",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 672,
     "referenced_widgets": [
      "dc17d7c6e107409c82a441a9198c324e",
      "d7626f2fe62c4ea3aea03902503cbf93",
      "1969a520465c41eaa7fe580248edb307",
      "a9f340121c9445c8bc495a1dfa9a5d0f",
      "f151ac52739f4f5f866e3f210a53f774",
      "9595785a1ad94c3290f594009266bc35",
      "2cdc7a0af63d499e96b70b0112d62560",
      "7b88f5f3f5cc4622afaaeedb31a25721"
     ]
    },
    "colab_type": "code",
    "id": "y7W9fNgjLpVT",
    "outputId": "29522e2b-a283-469a-edab-5f4316b768e5"
   },
   "outputs": [
    {
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       "model_id": "8affb158b3b64d55bb97b082dbed3468",
       "version_major": 2,
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      "text/plain": [
       "HBox(children=(FloatProgress(value=0.0, max=39.0), HTML(value='')))"
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     },
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     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
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     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>filter_by</th>\n",
       "      <th>results</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>no filter (=all records)</td>\n",
       "      <td>1562963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>date</td>\n",
       "      <td>1562963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>title</td>\n",
       "      <td>1562963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>id</td>\n",
       "      <td>1562963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>figshare_url</td>\n",
       "      <td>1562963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>date_inserted</td>\n",
       "      <td>1562963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>date_created</td>\n",
       "      <td>1562963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>dimensions_url</td>\n",
       "      <td>1562963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>year</td>\n",
       "      <td>1562963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>authors</td>\n",
       "      <td>1562963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>license_name</td>\n",
       "      <td>1562962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>license_url</td>\n",
       "      <td>1562962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>description</td>\n",
       "      <td>1562951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>language_desc</td>\n",
       "      <td>1562937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>language_title</td>\n",
       "      <td>1562937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>doi</td>\n",
       "      <td>1562926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>date_modified</td>\n",
       "      <td>1562836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>repository_id</td>\n",
       "      <td>1562706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>keywords</td>\n",
       "      <td>1561236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>associated_publication</td>\n",
       "      <td>1097585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>associated_publication_id</td>\n",
       "      <td>1097585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>journal</td>\n",
       "      <td>1097427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>researchers</td>\n",
       "      <td>1095472</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>research_orgs</td>\n",
       "      <td>1071226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>research_org_countries</td>\n",
       "      <td>1047301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>research_org_states</td>\n",
       "      <td>1047301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>research_org_cities</td>\n",
       "      <td>1046630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>category_for</td>\n",
       "      <td>726625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>funders</td>\n",
       "      <td>674791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>funder_countries</td>\n",
       "      <td>674781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>associated_grant_ids</td>\n",
       "      <td>410030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>category_rcdc</td>\n",
       "      <td>345879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>category_hrcs_hc</td>\n",
       "      <td>186297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>category_hra</td>\n",
       "      <td>166770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>category_icrp_cso</td>\n",
       "      <td>165713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>category_bra</td>\n",
       "      <td>159065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>category_hrcs_rac</td>\n",
       "      <td>122630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>category_sdg</td>\n",
       "      <td>76867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>category_icrp_ct</td>\n",
       "      <td>69508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>date_embargo</td>\n",
       "      <td>8402</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
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       "                    filter_by  results\n",
       "0    no filter (=all records)  1562963\n",
       "14                       date  1562963\n",
       "38                      title  1562963\n",
       "25                         id  1562963\n",
       "22               figshare_url  1562963\n",
       "17              date_inserted  1562963\n",
       "15               date_created  1562963\n",
       "20             dimensions_url  1562963\n",
       "39                       year  1562963\n",
       "4                     authors  1562963\n",
       "30               license_name  1562962\n",
       "31                license_url  1562962\n",
       "19                description  1562951\n",
       "28              language_desc  1562937\n",
       "29             language_title  1562937\n",
       "21                        doi  1562926\n",
       "18              date_modified  1562836\n",
       "32              repository_id  1562706\n",
       "27                   keywords  1561236\n",
       "2      associated_publication  1097585\n",
       "3   associated_publication_id  1097585\n",
       "26                    journal  1097427\n",
       "37                researchers  1095472\n",
       "36              research_orgs  1071226\n",
       "34     research_org_countries  1047301\n",
       "35        research_org_states  1047301\n",
       "33        research_org_cities  1046630\n",
       "6                category_for   726625\n",
       "24                    funders   674791\n",
       "23           funder_countries   674781\n",
       "1        associated_grant_ids   410030\n",
       "12              category_rcdc   345879\n",
       "8            category_hrcs_hc   186297\n",
       "7                category_hra   166770\n",
       "10          category_icrp_cso   165713\n",
       "5                category_bra   159065\n",
       "9           category_hrcs_rac   122630\n",
       "13               category_sdg    76867\n",
       "11           category_icrp_ct    69508\n",
       "16               date_embargo     8402"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q_template = \"\"\"search datasets where {} is not empty return datasets[id] limit 1\"\"\"\n",
    "\n",
    "# seed results with total number of orgs\n",
    "total = dsl.query(\"\"\"search datasets return datasets[id] limit 1\"\"\", verbose=False).count_total\n",
    "stats = [\n",
    "    {'filter_by': 'no filter (=all records)', 'results' : total}\n",
    "]\n",
    "\n",
    "for f in progress(fields):\n",
    "    q = q_template.format(f)\n",
    "    res = dsl.query(q, verbose=False)\n",
    "    time.sleep(0.5)\n",
    "    stats.append({'filter_by': f, 'results' : res.count_total})\n",
    "\n",
    "\n",
    "df = pd.DataFrame().from_dict(stats)\n",
    "df.sort_values(\"results\", inplace=True, ascending=False)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "Collapsed": "false",
    "colab_type": "text",
    "id": "gOmpRRLMLpVW"
   },
   "source": [
    "### Creating a bar chart\n",
    "\n",
    "> NOTE: a standalone version of this chart is also [available online](http://api-sample-data.dimensions.ai/dataviz-exports/1-introducing-datasets/dataset-fields-overview.html)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
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    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 542
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    "colab_type": "code",
    "id": "XIfCjqPULpVW",
    "outputId": "3fdd59d7-bd52-4e46-a09d-8cb0ef25584e"
   },
   "outputs": [
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