INR.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "95f23ff9",
   "metadata": {},
   "source": [
    "# Ibsen Network Reader 0.1.1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1db5faad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <a href=\"https://bokeh.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"1002\">Loading BokehJS ...</span>\n",
       "    </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "(function(root) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "\n",
       "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
       "    root._bokeh_onload_callbacks = [];\n",
       "    root._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "  var JS_MIME_TYPE = 'application/javascript';\n",
       "  var HTML_MIME_TYPE = 'text/html';\n",
       "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
       "  var CLASS_NAME = 'output_bokeh rendered_html';\n",
       "\n",
       "  /**\n",
       "   * Render data to the DOM node\n",
       "   */\n",
       "  function render(props, node) {\n",
       "    var script = document.createElement(\"script\");\n",
       "    node.appendChild(script);\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when an output is cleared or removed\n",
       "   */\n",
       "  function handleClearOutput(event, handle) {\n",
       "    var cell = handle.cell;\n",
       "\n",
       "    var id = cell.output_area._bokeh_element_id;\n",
       "    var server_id = cell.output_area._bokeh_server_id;\n",
       "    // Clean up Bokeh references\n",
       "    if (id != null && id in Bokeh.index) {\n",
       "      Bokeh.index[id].model.document.clear();\n",
       "      delete Bokeh.index[id];\n",
       "    }\n",
       "\n",
       "    if (server_id !== undefined) {\n",
       "      // Clean up Bokeh references\n",
       "      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
       "      cell.notebook.kernel.execute(cmd, {\n",
       "        iopub: {\n",
       "          output: function(msg) {\n",
       "            var id = msg.content.text.trim();\n",
       "            if (id in Bokeh.index) {\n",
       "              Bokeh.index[id].model.document.clear();\n",
       "              delete Bokeh.index[id];\n",
       "            }\n",
       "          }\n",
       "        }\n",
       "      });\n",
       "      // Destroy server and session\n",
       "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
       "      cell.notebook.kernel.execute(cmd);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when a new output is added\n",
       "   */\n",
       "  function handleAddOutput(event, handle) {\n",
       "    var output_area = handle.output_area;\n",
       "    var output = handle.output;\n",
       "\n",
       "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
       "    if ((output.output_type != \"display_data\") || (!Object.prototype.hasOwnProperty.call(output.data, EXEC_MIME_TYPE))) {\n",
       "      return\n",
       "    }\n",
       "\n",
       "    var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
       "\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
       "      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
       "      // store reference to embed id on output_area\n",
       "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
       "    }\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
       "      var bk_div = document.createElement(\"div\");\n",
       "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
       "      var script_attrs = bk_div.children[0].attributes;\n",
       "      for (var i = 0; i < script_attrs.length; i++) {\n",
       "        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
       "        toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n",
       "      }\n",
       "      // store reference to server id on output_area\n",
       "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
       "    }\n",
       "  }\n",
       "\n",
       "  function register_renderer(events, OutputArea) {\n",
       "\n",
       "    function append_mime(data, metadata, element) {\n",
       "      // create a DOM node to render to\n",
       "      var toinsert = this.create_output_subarea(\n",
       "        metadata,\n",
       "        CLASS_NAME,\n",
       "        EXEC_MIME_TYPE\n",
       "      );\n",
       "      this.keyboard_manager.register_events(toinsert);\n",
       "      // Render to node\n",
       "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
       "      render(props, toinsert[toinsert.length - 1]);\n",
       "      element.append(toinsert);\n",
       "      return toinsert\n",
       "    }\n",
       "\n",
       "    /* Handle when an output is cleared or removed */\n",
       "    events.on('clear_output.CodeCell', handleClearOutput);\n",
       "    events.on('delete.Cell', handleClearOutput);\n",
       "\n",
       "    /* Handle when a new output is added */\n",
       "    events.on('output_added.OutputArea', handleAddOutput);\n",
       "\n",
       "    /**\n",
       "     * Register the mime type and append_mime function with output_area\n",
       "     */\n",
       "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
       "      /* Is output safe? */\n",
       "      safe: true,\n",
       "      /* Index of renderer in `output_area.display_order` */\n",
       "      index: 0\n",
       "    });\n",
       "  }\n",
       "\n",
       "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
       "  if (root.Jupyter !== undefined) {\n",
       "    var events = require('base/js/events');\n",
       "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
       "\n",
       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
       "      register_renderer(events, OutputArea);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  \n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    var el = document.getElementById(\"1002\");\n",
       "    if (el != null) {\n",
       "      el.textContent = \"BokehJS is loading...\";\n",
       "    }\n",
       "    if (root.Bokeh !== undefined) {\n",
       "      if (el != null) {\n",
       "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
       "      }\n",
       "    } else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(display_loaded, 100)\n",
       "    }\n",
       "  }\n",
       "\n",
       "\n",
       "  function run_callbacks() {\n",
       "    try {\n",
       "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
       "        if (callback != null)\n",
       "          callback();\n",
       "      });\n",
       "    } finally {\n",
       "      delete root._bokeh_onload_callbacks\n",
       "    }\n",
       "    console.debug(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(css_urls, js_urls, callback) {\n",
       "    if (css_urls == null) css_urls = [];\n",
       "    if (js_urls == null) js_urls = [];\n",
       "\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
       "\n",
       "    function on_load() {\n",
       "      root._bokeh_is_loading--;\n",
       "      if (root._bokeh_is_loading === 0) {\n",
       "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
       "        run_callbacks()\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function on_error(url) {\n",
       "      console.error(\"failed to load \" + url);\n",
       "    }\n",
       "\n",
       "    for (let i = 0; i < css_urls.length; i++) {\n",
       "      const url = css_urls[i];\n",
       "      const element = document.createElement(\"link\");\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error.bind(null, url);\n",
       "      element.rel = \"stylesheet\";\n",
       "      element.type = \"text/css\";\n",
       "      element.href = url;\n",
       "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
       "      document.body.appendChild(element);\n",
       "    }\n",
       "\n",
       "    const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.3.2.min.js\": \"XypntL49z55iwGVUW4qsEu83zKL3XEcz0MjuGOQ9SlaaQ68X/g+k1FcioZi7oQAc\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.3.2.min.js\": \"bEsM86IHGDTLCS0Zod8a8WM6Y4+lafAL/eSiyQcuPzinmWNgNO2/olUF0Z2Dkn5i\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.3.2.min.js\": \"TX0gSQTdXTTeScqxj6PVQxTiRW8DOoGVwinyi1D3kxv7wuxQ02XkOxv0xwiypcAH\"};\n",
       "\n",
       "    for (let i = 0; i < js_urls.length; i++) {\n",
       "      const url = js_urls[i];\n",
       "      const element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error.bind(null, url);\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      if (url in hashes) {\n",
       "        element.crossOrigin = \"anonymous\";\n",
       "        element.integrity = \"sha384-\" + hashes[url];\n",
       "      }\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "  };\n",
       "\n",
       "  function inject_raw_css(css) {\n",
       "    const element = document.createElement(\"style\");\n",
       "    element.appendChild(document.createTextNode(css));\n",
       "    document.body.appendChild(element);\n",
       "  }\n",
       "\n",
       "  \n",
       "  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.3.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.3.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.3.2.min.js\"];\n",
       "  var css_urls = [];\n",
       "  \n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    function(Bokeh) {\n",
       "    \n",
       "    \n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if (root.Bokeh !== undefined || force === true) {\n",
       "      \n",
       "    for (var i = 0; i < inline_js.length; i++) {\n",
       "      inline_js[i].call(root, root.Bokeh);\n",
       "    }\n",
       "    if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    } else if (force !== true) {\n",
       "      var cell = $(document.getElementById(\"1002\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (root._bokeh_is_loading === 0) {\n",
       "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(css_urls, js_urls, function() {\n",
       "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(window));"
      ],
      "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(\"1002\");\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error(url) {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (let i = 0; i < css_urls.length; i++) {\n      const url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error.bind(null, url);\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.3.2.min.js\": \"XypntL49z55iwGVUW4qsEu83zKL3XEcz0MjuGOQ9SlaaQ68X/g+k1FcioZi7oQAc\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.3.2.min.js\": \"bEsM86IHGDTLCS0Zod8a8WM6Y4+lafAL/eSiyQcuPzinmWNgNO2/olUF0Z2Dkn5i\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.3.2.min.js\": \"TX0gSQTdXTTeScqxj6PVQxTiRW8DOoGVwinyi1D3kxv7wuxQ02XkOxv0xwiypcAH\"};\n\n    for (let i = 0; i < js_urls.length; i++) {\n      const url = js_urls[i];\n      const element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error.bind(null, url);\n      element.async = false;\n      element.src = url;\n      if (url in hashes) {\n        element.crossOrigin = \"anonymous\";\n        element.integrity = \"sha384-\" + hashes[url];\n      }\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  \n  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.3.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.3.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.3.2.min.js\"];\n  var css_urls = [];\n  \n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    function(Bokeh) {\n    \n    \n    }\n  ];\n\n  function run_inline_js() {\n    \n    if (root.Bokeh !== undefined || force === true) {\n      \n    for (var i = 0; i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\n    if (force === true) {\n        display_loaded();\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(\"1002\")).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd # PANDAS!\n",
    "from bokeh.plotting import figure, show, output_notebook, output_file, reset_output # bøkke\n",
    "import re # Regex\n",
    "from datetime import datetime # Jeg vet det. Ja, du må faktisk.\n",
    "output_notebook() # bøkke i notatbok"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "335d94c3",
   "metadata": {},
   "source": [
    "## Cumulative vs point data\n",
    "Set mode=\"cumulative\" for cumulative plots, and \"point\" for point plots (per-year etc)\n",
    "\n",
    "I know that it's jank, but that's how it do rn."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "16e64eb6",
   "metadata": {},
   "outputs": [],
   "source": [
    "#mode=\"cumulative\"\n",
    "mode=\"single\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "05d5487f",
   "metadata": {},
   "source": [
    "## Hent data...\n",
    "...omdøp kolonner, fiks datatypen til noen kolonner."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "fe611d18",
   "metadata": {},
   "outputs": [],
   "source": [
    "import glob\n",
    "paths = []\n",
    "outputs = []\n",
    "for path in glob.glob('csv/**/*.csv', recursive=True):\n",
    "    paths.append(path)\n",
    "#paths er liste over stier til filer i SRC\n",
    "\n",
    "for path in paths:\n",
    "    path = path.replace('csv','output')\n",
    "    outputs.append(path)\n",
    "#outputs er liste over stier til nye filer\n",
    "\n",
    "brev = pd.read_csv(paths[0])\n",
    "personer = pd.read_csv(paths[1])\n",
    "dfs = [brev,personer]\n",
    "for df in dfs:\n",
    "    df.fillna(0,inplace=True)\n",
    "personer.columns = ['xmlID', 'wikidata', 'viaf', 'nhrp', 'fornavn', 'etternavn',\n",
    "       'navn', 'birthday', 'deathday', 'type', 'instance',\n",
    "       'sex', 'nationality', 'job', 'receiveds',\n",
    "       'mentions', 'desc', 'partner', 'partnerID']\n",
    "integers = ['birthday','deathday','receiveds','mentions']\n",
    "for a in integers:\n",
    "    personer[a] = personer[a].astype(int)\n",
    "brev.columns = ['letterID', 'senderID', 'sender', 'recipientID',\n",
    "       'recipient', 'date', 'dispatch', 'dispatchabbr',\n",
    "       'geonameID', 'toponymName', 'country', 'lat', 'lon',\n",
    "       'address', 'location', 'locationabbr',\n",
    "       'tolat', 'tolon',\n",
    "       'mentionIDs', 'mentions', 'mentionORGID',\n",
    "       'mentionORG', 'mentionWorkID', 'mentionWork',\n",
    "       'textID', 'mentionWorkGenre', 'collectiveversionid',\n",
    "       'mentionPlaces', 'mentionPlacesabbr']\n",
    "integers = ['geonameID']\n",
    "for a in integers:\n",
    "    brev[a] = brev[a].astype(int)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c69aac1",
   "metadata": {},
   "source": [
    "## DATAVASK: TID OG DATO\n",
    "Kolonne for dato har rundt 5-6% tjafs. Denne modulen utøver ganske brisk & brutal vold mot irregulære datoer. Den forsøker å finne år-måned-dag, år-måned og år i den rekkefølgen, og legger til så mange 01'er som trengs for å få fullstendige datoer. Noen datoer forklares i tekst (typ \"30 november 18XY\"), noen er tidsspenn, og andre er bare *???* - disse er per nå alt for irregulære og bare mørbankes til de kun er årstall for å bygges opp igjen."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "02bf6bc3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Registered 2409 out of 2409 entries.\n",
      "Good dates: 94.73% (2282)\n",
      "Bad dates: 5.27% (127)\n",
      "\n",
      "Fixing...\n",
      "\n",
      "Done! Good dates: 100.0% (2409/2409)\n",
      "Added column datetimes to df-brev.\n"
     ]
    }
   ],
   "source": [
    "r = re.compile('^.{4}-.{2}-.{2}$') # Formatet XXXX-XX-XX\n",
    "\n",
    "good = 0\n",
    "bad = 0\n",
    "for x in brev['date']:\n",
    "    if r.match(x):\n",
    "        good +=1\n",
    "    else:\n",
    "        bad += 1\n",
    "percA = round((good/len(brev)*100),2)\n",
    "percB = round((bad/len(brev)*100),2)\n",
    "print(\"Registered\",good+bad,\"out of\",len(brev),\"entries.\\nGood dates:\",str(percA)+\"% (\"+str(good)+\")\\nBad dates:\",\n",
    "      str(percB)+\"% (\"+str(bad)+\")\\n\")\n",
    "\n",
    "i = 0\n",
    "strings = []\n",
    "for ting in brev['date']:\n",
    "    x = ting\n",
    "    y = re.sub(\"[^0-9-]\", \"\", x) # Fjern alt som ikke er tall eller bindestrek\n",
    "    if y == \"\": # Om dato er TOMT (må fikses med én gang)\n",
    "        y = \"1905-01-01\" # da er den fra THE D I S T A N T  F U T U R E  OF  1 9 9 X ! #neida det blir 1905\n",
    "    if y[0] == \"-\": # Sjekk at det ikke nå er en bindestrek foran året\n",
    "        y = y[1:] # Slett den om den finnes\n",
    "    y = y[:10] # Om resultatet har mer enn 10 karakterer: HØGG\n",
    "    \n",
    "    if r.match(y):\n",
    "        pass\n",
    "    \n",
    "        #print(\"ye:)\")\n",
    "    else:\n",
    "        if y[0] != \"1\": # Special case for [1426]. Datoen blir \"3041\", som jo er litt etter Ibsens tid.\n",
    "            y = y[3:] # sleng de tre første karakterer ligeledes i søppelet\n",
    "        #print(i,y)\n",
    "        if len(y) == 7: # Om det er 7 karakterer (YYYY-MM),\n",
    "            y+=\"-01\" # Legg til \"-01\" som dag.\n",
    "        elif len(y) == 4: # (YYYY)\n",
    "            y+=\"-01-01\" # Nå er det 1. januar det året\n",
    "        else: # Om det er hverken 4 eller 7 karakterer og heller ikke 10:\n",
    "            y = y[:4] # Slett alt som ikke er år\n",
    "            y+=\"-01-01\" # Nå er det 1. januar det året, ferdig snakka.\n",
    "        #print(y)\n",
    "    i += 1\n",
    "    strings.append(y) # OK\n",
    "\n",
    "print(\"Fixing...\\n\")    \n",
    "    \n",
    "good = 0\n",
    "bad = 0\n",
    "for x in strings:\n",
    "    if r.match(x):\n",
    "        good +=1\n",
    "    else:\n",
    "        bad += 1\n",
    "percA = round((good/len(brev)*100),2)\n",
    "percB = round((bad/len(brev)*100),2)\n",
    "print(\"Done! Good dates:\",str(percA)+\"% (\"+str(good)+\"/\"+str(len(brev))+\")\")\n",
    "if bad > 0:\n",
    "    print(\"YOOOO we got some BAD DATES:\",\n",
    "      str(percB)+\"% (\"+str(bad)+\")\")\n",
    "    raise KeyboardInterrupt()\n",
    "else:\n",
    "    datetimes = []\n",
    "    for string in strings:\n",
    "        x = string.split(\"-\")\n",
    "        date = x[2]+\"/\"+x[1]+\"/\"+x[0] # det her var det ikke noe poeng med, nei\n",
    "        date_time_obj = datetime.strptime(date, '%d/%m/%Y')\n",
    "        datetimes.append(date)\n",
    "    brev['datetimes'] = datetimes\n",
    "    brev['datetimes'] = pd.to_datetime(brev['datetimes'], format='%d/%m/%Y')\n",
    "    print(\"Added column datetimes to df-brev.\")\n",
    "    #brev['datetimes'] = pd.to_datetime(brev[\"datetimes\"].dt.strftime('%d/%m/%Y'))\n",
    "    brev = brev.sort_values(\"datetimes\")\n",
    "    brev.reset_index(drop=True,inplace=True)\n",
    "    personer.reset_index(drop=True,inplace=True)\n",
    "    personer['xmlID'] = personer['xmlID'].apply(str)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c03dba54",
   "metadata": {},
   "source": [
    "Index male, female and none IDs for later use. This was previously part of the **big** cell. By preindexing we're making it *lightning fast* in comparison to what it was!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "68e8fe92",
   "metadata": {},
   "outputs": [],
   "source": [
    "males = []\n",
    "females = []\n",
    "others = []\n",
    "i = 0\n",
    "for sex in personer['sex']:\n",
    "    sex = str(sex)\n",
    "    person = str(personer.iloc[i]['xmlID'])\n",
    "    if sex == \"male\": # \"male\"\n",
    "        males.append(person)\n",
    "    elif sex == \"female\": # \"female\"\n",
    "        females.append(person)\n",
    "    else: # 0\n",
    "        others.append(person)\n",
    "    i+=1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c28bb608",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "cf67e50c",
   "metadata": {},
   "source": [
    "## Plotting 1\n",
    "Personer + brev. Produserer forskjellige grafer basert på mode var."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "c4c8b4a6",
   "metadata": {},
   "outputs": [],
   "source": [
    "mode=\"point\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "76a331f7",
   "metadata": {},
   "source": [
    "## Powercell"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "24544acd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "12 TO ER 0\n"
     ]
    }
   ],
   "source": [
    "datedletters = []\n",
    "malesaddressed = []\n",
    "femalesaddressed = []\n",
    "othersaddressed = []\n",
    "malesmentioned = []\n",
    "femalesmentioned = []\n",
    "othersmentioned = []\n",
    "anonsaddressed = []\n",
    "anonsmentioned = []\n",
    "\n",
    "tomales=0\n",
    "tofemales=0\n",
    "toother=0\n",
    "mentionmales=0\n",
    "mentionfemales=0\n",
    "mentionother=0\n",
    "mentionanons=0\n",
    "anonsto=0\n",
    "totalmentions=0\n",
    "totaladdrs=0\n",
    "for idx,row in brev.iterrows(): # For HVER rad i brev-df.\n",
    "    #print(idx)\n",
    "    if mode != \"cumulative\":\n",
    "        tomales=0\n",
    "        tofemales=0\n",
    "        toother=0\n",
    "        anonsto=0\n",
    "        mentionmales=0\n",
    "        mentionfemales=0\n",
    "        mentionother=0\n",
    "        mentionanons=0\n",
    "    sex = \"LiveLoveLag\" # Sett standardverdi for var sex.\n",
    "    mentioned = row['mentionIDs'] # GET alle mention IDs fra rad.\n",
    "    date = row['datetimes'] # GET dato fra raden.\n",
    "    to = row['recipientID'] # GET recipient ID fra raden.\n",
    "    if to == 0: # hvis TIL er 0:\n",
    "        print(idx,\"TO ER 0\")\n",
    "        pass # Gjør ingenting!\n",
    "    elif to == \"\": # hvis TIL er tomt\n",
    "        print(idx,\"TO ER TOM\")\n",
    "        pass # samme.\n",
    "    else: # Hvis TIL IKKE ER 0:\n",
    "       # print(\"Mottaker er ikke tomt\")\n",
    "        if \",\" in str(to): # Hvis det ER et komma (flere mottakere) i data for mottaker:\n",
    "           # print(\"Flere mottakere\")\n",
    "            toArray = to.split(', ') # Splitt mottakerfeltet\n",
    "            for to in toArray: # For hver innførsel i mottakerfeltet\n",
    "                totaladdrs+=1\n",
    "                if str(to) != \"0\": # Hvis det ikke er 0 her av en eller annen grunn...\n",
    "                    if to in males:\n",
    "                        tomales+=1\n",
    "                    elif to in females:\n",
    "                        tofemales+=1\n",
    "                    elif to in others:\n",
    "                        toother+=1\n",
    "                    else: # Denne aktiveres aldri\n",
    "                        anonsto+=1\n",
    "                    #sex = personer.loc[personer['xmlID'] == str(to)][\"sex\"].values # GET kjønnet til personen fra personregisteret\n",
    "                    #sex = str(sex) # stringify\n",
    "                    #if sex == \"['male']\": # Hvis MANN\n",
    "                    #    tomales+=1 # Menn pluss 1\n",
    "                    #elif sex == \"['female']\": # Hvis KVINNE\n",
    "                    #    tofemales+=1 # Kvinner pluss 1\n",
    "                    #else: # hvis ikke mann ELLER kvinne\n",
    "                    #    print(to,sex)\n",
    "                    #    toother+=1 # andre pluss 1\n",
    "        else: # Hvis det IKKE er et komma i mottakerfeltet\n",
    "         #   print(\"Mottaker er alene\")\n",
    "            totaladdrs+=1\n",
    "            if to in males:\n",
    "                tomales+=1\n",
    "            elif to in females:\n",
    "                tofemales+=1\n",
    "            elif to in others:\n",
    "                toother+=1\n",
    "            else: # Dette betyr altså at sex != male, sex != female... og at tingen ikke har blitt indeksert i other.\n",
    "                anonsto+=1\n",
    "            #sex = personer.loc[personer['xmlID'] == str(to)][\"sex\"].values # GET kjønnet til personen fra personregisteret\n",
    "            #sex = str(sex) # stringify\n",
    "            #if sex == \"['male']\":  # Hvis MANN\n",
    "            #    tomales+=1 # Menn pluss 1\n",
    "            #elif sex == \"['female']\": # Hvis KVINNE\n",
    "            #    tofemales+=1 # Kvinner pluss 1\n",
    "            #else: # ELLERS\n",
    "            #    #print(to,sex)\n",
    "            #    toother+=1 # andre pluss 1\n",
    "            \n",
    "    if mentioned == 0: # Hvis MENTIONS er 0 (N/A)\n",
    "        #print(\"Mention er 0\")\n",
    "        pass # Gjør ingenting\n",
    "    elif mentioned == \"\": # Hvis mentions er TOM (N/A)\n",
    "        #print(\"Mention er null\")\n",
    "        pass # Samme.\n",
    "    else: # Hvis det er data i feltet for MENTIONS\n",
    "       # print(\"Mention har data\")\n",
    "        if \",\" in mentioned: # HVIS det er et komma i feltet\n",
    "            mentioned = mentioned.split(', ') # Splitt det\n",
    "            for mention in mentioned: # For hver av elementene i arrayen\n",
    "                totalmentions+=1\n",
    "            #    sex = personer.loc[personer['xmlID'] == mention][\"sex\"].values # Hent kjønn\n",
    "            #    sex = str(sex) # Bla bla bla - det samme som over.\n",
    "            #    if sex == \"['male']\":\n",
    "            #        mentionmales+=1\n",
    "            #    elif sex == \"['female']\":\n",
    "            #        mentionfemales+=1\n",
    "            #    else:\n",
    "            #        mentionother+=1\n",
    "                if mention in males:\n",
    "                    mentionmales+=1\n",
    "                elif mention in females:\n",
    "                    mentionfemales+=1\n",
    "                elif mention in others:\n",
    "                    mentionother+=1\n",
    "                else:\n",
    "                    mentionanons+=1\n",
    "        else: # Hvis det er ÉN person i feltet, hent dennes verdier fra personregisteret\n",
    "            totalmentions+=1\n",
    "            if mention in males:\n",
    "                mentionmales+=1\n",
    "            elif mention in females:\n",
    "                mentionfemales+=1\n",
    "            elif mention in others:\n",
    "                mentionother+=1\n",
    "            else:\n",
    "                mentionanons+=1\n",
    "          #  sex = personer.loc[personer['xmlID'] == mention][\"sex\"].values\n",
    "          #  sex = str(sex)\n",
    "          #  if sex == \"['male']\":\n",
    "          #      mentionmales+=1\n",
    "          #  elif sex == \"['female']\":\n",
    "          #      mentionfemales+=1\n",
    "          #  else:\n",
    "          #      mentionother+=1\n",
    "    datedletters.append(date)\n",
    "    malesaddressed.append(tomales)\n",
    "    femalesaddressed.append(tofemales)\n",
    "    othersaddressed.append(toother)\n",
    "    malesmentioned.append(mentionmales)\n",
    "    femalesmentioned.append(mentionfemales)\n",
    "    othersmentioned.append(mentionother)\n",
    "    anonsaddressed.append(anonsto)\n",
    "    anonsmentioned.append(mentionanons)\n",
    "    #print(\"\\n\")\n",
    "#print(tomales,tofemales,toother,\" | \",mentionmales,mentionfemales,mentionother)\n",
    "df = pd.DataFrame(\n",
    "    {'date': datedletters,\n",
    "     'males_addressed': malesaddressed,\n",
    "     'females_addressed': femalesaddressed,\n",
    "     'others_addressed': othersaddressed,\n",
    "     'anons_addressed':anonsaddressed,\n",
    "     'males_mentioned': malesmentioned,\n",
    "     'females_mentioned': femalesmentioned,\n",
    "     'others_mentioned': othersmentioned,\n",
    "     'anons_mentioned':anonsmentioned\n",
    "    })"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "4eee2bbe",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MODE: BY YEAR\n"
     ]
    },
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       "\n",
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       "\n",
       "\n",
       "\n",
       "\n",
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     "output_type": "display_data"
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(Organizations)\"},\"renderers\":[{\"id\":\"3828\"},{\"id\":\"3938\"}]},\"id\":\"3852\",\"type\":\"LegendItem\"},{\"attributes\":{\"axis\":{\"id\":\"3713\"},\"ticker\":null},\"id\":\"3716\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"3711\",\"type\":\"LinearScale\"},{\"attributes\":{\"source\":{\"id\":\"3701\"}},\"id\":\"3939\",\"type\":\"CDSView\"},{\"attributes\":{\"data_source\":{\"id\":\"3701\"},\"glyph\":{\"id\":\"3936\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"3937\"},\"view\":{\"id\":\"3939\"}},\"id\":\"3938\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"data\":{\"anons_addressed\":{\"__ndarray__\":\"AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACAAAAAAAAAAAAAAABAAAAAAAAAAEAAAAAAAAAAAAAAAIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAMAAAABAAAAAwAAAAEAAAACAAAAAgAAAAAAAAABAAAAAQAAAAEAAAABAAAAAAAAAAAAAAAAAAAAAAAAAAIAAAADAAAAAwAAAAQAAAAJAAAADgAAAAMAAAAFAAAACgAAAAUAAAAIAAAAAQAAAAYAAAAFAAAACgAAAAMAAAAAAAAAAQAAAAEAAAACAAAA\",\"dtype\":\"int32\",\"order\":\"little\",\"shape\":[60]},\"anons_mentioned\":{\"__ndarray__\":\"AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQAAAAAAAAAAAAAAAQAAAAAAAAAAAAAAAQAAAAAAAAAAAAAAAAAAAAEAAAAAAAAAAAAAAAQAAAABAAAAAgAAAAIAAAAEAAAAAQAAAAcAAAABAAAABAAAAAEAAAACAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAAAAAAAAAADAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA\",\"dtype\":\"int32\",\"order\":\"little\",\"shape\":[60]},\"date\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[60]},\"females_addressed\":{\"__ndarray__\":\"AQAAAAEAAAAAAAAAAAAAAAIAAAAAAAAAAAAAAAMAAAAAAAAAAAAAAAAAAAACAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEAAAABAAAAAQAAAAEAAAABAAAABQAAAAMAAAAAAAAAAwAAAAQAAAACAAAAAgAAAAkAAAADAAAABgAAAAIAAAACAAAAAwAAAAQAAAAJAAAAAwAAAAMAAAAHAAAADAAAAA0AAAAJAAAAEwAAAAgAAAAIAAAADwAAAB0AAAAFAAAABwAAABMAAAAOAAAADQAAAAIAAAAAAAAAAAAAAAAAAAAAAAAA\",\"dtype\":\"int32\",\"order\":\"little\",\"shape\":[60]},\"females_mentioned\":{\"__ndarray__\":\"AgAAAAAAAAAAAAAAAAAAAAEAAAAAAAAAAwAAAAQAAAAAAAAAAAAAAAkAAAACAAAAAAAAAAAAAAABAAAAAAAAAAAAAAACAAAAAgAAAAoAAAAVAAAACQAAAAQAAAASAAAAGQAAABUAAAAXAAAAEwAAABgAAAAXAAAAFwAAABsAAAAVAAAAIgAAABgAAAAQAAAAFQAAAAsAAABHAAAAFQAAAB4AAAAeAAAAMgAAAB4AAAArAAAAJgAAABgAAAAZAAAAGAAAAEgAAAAOAAAAHgAAABIAAAAOAAAACQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA\",\"dtype\":\"int32\",\"order\":\"little\",\"shape\":[60]},\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59],\"males_addressed\":{\"__ndarray__\":\"AQAAAAAAAAABAAAAAQAAAAMAAAABAAAAAAAAAAEAAAAAAAAAAAAAAAQAAAAEAAAABQAAAAcAAAAHAAAABAAAAAYAAAAFAAAABQAAAAsAAAAiAAAAEwAAAA4AAAAnAAAAMAAAADIAAAAsAAAAMwAAACIAAABDAAAANgAAADsAAAAoAAAAKgAAADYAAAAhAAAALAAAACEAAAAxAAAAIAAAADAAAAAwAAAAXAAAAEkAAABKAAAAYAAAAD0AAAA4AAAARAAAADIAAAAwAAAALwAAADkAAAA3AAAAOwAAAAYAAAAFAAAABAAAAAIAAAACAAAA\",\"dtype\":\"int32\",\"order\":\"little\",\"shape\":[60]},\"males_mentioned\":{\"__ndarray__\":\"BgAAAAAAAAAEAAAAAQAAAAsAAAABAAAAJwAAAAwAAAACAAAAAQAAAAwAAAATAAAABAAAAAoAAAAUAAAABwAAAAQAAAAQAAAADQAAAC0AAACEAAAASwAAAC0AAABvAAAAfgAAAJEAAAB9AAAAyQAAACgAAAB1AAAARwAAAFoAAABnAAAASAAAAEcAAAAtAAAAQwAAACYAAACaAAAALQAAAFkAAAA2AAAAYwAAAEkAAAA4AAAAXgAAACQAAAAnAAAATAAAAIwAAABAAAAATgAAABYAAABFAAAAJQAAAAMAAAAAAAAAAAAAAAEAAAAAAAAA\",\"dtype\":\"int32\",\"order\":\"little\",\"shape\":[60]},\"others_addressed\":{\"__ndarray__\":\"AAAAAAAAAAAAAAAAAAAAAAEAAAAAAAAABQAAAAQAAAACAAAAAQAAAAQAAAACAAAAAQAAAAEAAAAFAAAAAwAAAAIAAAAFAAAAAAAAAAQAAAACAAAAAAAAAAIAAAABAAAAAAAAAAQAAAAEAAAAAgAAAAQAAAACAAAAAAAAAAUAAAAEAAAABwAAAAQAAAAGAAAAAwAAAAUAAAAIAAAACAAAAAEAAAAFAAAABgAAAAYAAAAGAAAACgAAAAQAAAAAAAAABQAAAAUAAAADAAAAAwAAAAQAAAAJAAAABAAAAAMAAAACAAAAAAAAAAIAAAAAAAAA\",\"dtype\":\"int32\",\"order\":\"little\",\"shape\":[60]},\"others_mentioned\":{\"__ndarray__\":\"AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA\",\"dtype\":\"int32\",\"order\":\"little\",\"shape\":[60]},\"year\":[\"1844\",\"1845\",\"1846\",\"1849\",\"1850\",\"1851\",\"1852\",\"1853\",\"1854\",\"1855\",\"1856\",\"1857\",\"1858\",\"1859\",\"1860\",\"1861\",\"1862\",\"1863\",\"1864\",\"1865\",\"1866\",\"1867\",\"1868\",\"1869\",\"1870\",\"1871\",\"1872\",\"1873\",\"1874\",\"1875\",\"1876\",\"1877\",\"1878\",\"1879\",\"1880\",\"1881\",\"1882\",\"1883\",\"1884\",\"1885\",\"1886\",\"1887\",\"1888\",\"1889\",\"1890\",\"1891\",\"1892\",\"1893\",\"1894\",\"1895\",\"1896\",\"1897\",\"1898\",\"1899\",\"1900\",\"1901\",\"1902\",\"1903\",\"1904\",\"1905\"]},\"selected\":{\"id\":\"3793\"},\"selection_policy\":{\"id\":\"3792\"}},\"id\":\"3701\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"formatter\":{\"id\":\"3774\"},\"major_label_policy\":{\"id\":\"3775\"},\"ticker\":{\"id\":\"3714\"}},\"id\":\"3713\",\"type\":\"DatetimeAxis\"},{\"attributes\":{\"line_alpha\":0.1,\"line_color\":\"grey\",\"x\":{\"field\":\"date\"},\"y\":{\"field\":\"anons_addressed\"}},\"id\":\"3964\",\"type\":\"Line\"},{\"attributes\":{\"data_source\":{\"id\":\"3701\"},\"glyph\":{\"id\":\"3854\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"3855\"},\"view\":{\"id\":\"3857\"}},\"id\":\"3856\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.3},\"fill_color\":{\"value\":\"grey\"},\"line_alpha\":{\"value\":0.3},\"line_color\":{\"value\":\"grey\"},\"x\":{\"field\":\"date\"},\"y\":{\"field\":\"anons_addressed\"}},\"id\":\"3854\",\"type\":\"Scatter\"},{\"attributes\":{\"line_alpha\":0.3,\"line_color\":\"grey\",\"x\":{\"field\":\"date\"},\"y\":{\"field\":\"anons_addressed\"}},\"id\":\"3963\",\"type\":\"Line\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"grey\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"grey\"},\"x\":{\"field\":\"date\"},\"y\":{\"field\":\"anons_addressed\"}},\"id\":\"3855\",\"type\":\"Scatter\"},{\"attributes\":{\"source\":{\"id\":\"3701\"}},\"id\":\"3857\",\"type\":\"CDSView\"},{\"attributes\":{\"mantissas\":[1,2,5],\"max_interval\":500.0,\"num_minor_ticks\":0},\"id\":\"3780\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"source\":{\"id\":\"3701\"}},\"id\":\"3966\",\"type\":\"CDSView\"},{\"attributes\":{},\"id\":\"3998\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"label\":{\"value\":\"N/A (Unknown)\"},\"renderers\":[{\"id\":\"3856\"},{\"id\":\"3965\"}]},\"id\":\"3880\",\"type\":\"LegendItem\"},{\"attributes\":{\"data_source\":{\"id\":\"3701\"},\"glyph\":{\"id\":\"3963\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"3964\"},\"view\":{\"id\":\"3966\"}},\"id\":\"3965\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"3777\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"blue\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"blue\"},\"x\":{\"field\":\"date\"},\"y\":{\"field\":\"males_mentioned\"}},\"id\":\"3991\",\"type\":\"Scatter\"},{\"attributes\":{},\"id\":\"3778\",\"type\":\"AllLabels\"},{\"attributes\":{\"data_source\":{\"id\":\"3701\"},\"glyph\":{\"id\":\"3882\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"3883\"},\"view\":{\"id\":\"3885\"}},\"id\":\"3884\",\"type\":\"GlyphRenderer\"}],\"root_ids\":[\"4210\"]},\"title\":\"Bokeh Application\",\"version\":\"2.3.2\"}};\n",
       "  var render_items = [{\"docid\":\"99725a16-d79b-4dcf-b639-5bb447049c47\",\"root_ids\":[\"4210\"],\"roots\":{\"4210\":\"f8e467a0-ea74-4625-91c7-7b191fb97024\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "4210"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from bokeh.models import ColumnDataSource\n",
    "from bokeh.plotting import figure, show\n",
    "from bokeh.layouts import column\n",
    "from bokeh.io import export_png\n",
    "from bokeh.transform import jitter\n",
    "\n",
    "title = \"Ibsen's outgoing letters by gender\"\n",
    "if mode==\"cumulative\":\n",
    "    print(\"MODE: CUMULATIVE DATA\")\n",
    "    title += \", cumulative view\"\n",
    "    title1 = title+\" - Addressed to.\"\n",
    "    title2 = title+\" - Mentioning.\"\n",
    "    source = ColumnDataSource(df)\n",
    "\n",
    "    p = figure(width=800, height=400, x_axis_type='datetime',\n",
    "               title=title1)\n",
    "\n",
    "    #p.xaxis.formatter.days = ['%Y']\n",
    "    p.x_range.range_padding = 0\n",
    "    #p.ygrid.grid_line_color = None\n",
    "\n",
    "    d = figure(width=800, height=400, x_axis_type='datetime',\n",
    "               title=title2)\n",
    "\n",
    "\n",
    "    p.line(x='date', y='males_addressed', color='blue',  source=source, alpha=1, legend_label=\"Men\")\n",
    "    p.line(x='date', y='females_addressed', color='hotpink',  source=source, alpha=1, legend_label=\"Women\")\n",
    "    p.line(x='date', y='others_addressed', color='green',  source=source, alpha=0.5, legend_label=\"N/A (Organizations)\")\n",
    "    p.line(x='date', y='anons_addressed', color='grey',  source=source, alpha=0.5, legend_label=\"N/A (Unknown)\")\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "    d.line(x='date', y='males_mentioned', color='blue',\n",
    "              source=source, alpha=1, legend_label=\"Men\")\n",
    "    d.line(x='date', y='females_mentioned', color='hotpink', \n",
    "              source=source, alpha=1, legend_label=\"Women\")\n",
    "    d.line(x='date', y='others_mentioned', color='green',\n",
    "              source=source, alpha=0.5, legend_label=\"N/A (Organizations)\")\n",
    "    d.line(x='date', y='anons_mentioned', color='grey',\n",
    "              source=source, alpha=0.5, legend_label=\"N/A (Unknown)\")\n",
    "    #p.xaxis.formatter.days = ['%Y']\n",
    "    p.x_range.range_padding = 0\n",
    "    d.x_range.range_padding = 0\n",
    "    #p.ygrid.gridS_line_color = None\n",
    "\n",
    "    p.legend.location = \"top_left\"\n",
    "    p.legend.click_policy=\"hide\"\n",
    "\n",
    "    d.legend.location = \"top_left\"\n",
    "    d.legend.click_policy=\"hide\"\n",
    "\n",
    "    show(column(p, d))\n",
    "    if mode==\"cumulative\":\n",
    "        export_png(column(p, d), filename=\"pngs/Cumulative.png\") # CONDAFOX\n",
    "else:\n",
    "    print(\"MODE: BY YEAR\")\n",
    "    df1 = df\n",
    "    lst = []\n",
    "    lst1 = []\n",
    "    for y in df1['date']:\n",
    "        y = y.strftime(\"%Y/%m/%d\")\n",
    "        z = y[:4]\n",
    "        lst.append(z)\n",
    "        x = y[5:7]\n",
    "        lst1.append(x)\n",
    "    df1['year'] = lst\n",
    "    df1['month'] = lst1\n",
    "    #df1 = df1.sort_values('month')\n",
    "    integers = ['males_addressed',\n",
    "         'females_addressed',\n",
    "         'others_addressed',\n",
    "         'anons_addressed',\n",
    "         'males_mentioned',\n",
    "         'females_mentioned',\n",
    "         'others_mentioned',\n",
    "         'anons_mentioned']\n",
    "    for a in integers:\n",
    "        df1[a] = df1[a].astype(int)\n",
    "    #df1.groupby(['year', 'month'])['males_addressed'].agg('sum')\n",
    "    df2 = df1.groupby(['year']).sum() # what the goddamn is going on with the maths here??\n",
    "    df2 = df2.reset_index()\n",
    "\n",
    "    df2['date'] = df2['year']\n",
    "\n",
    "\n",
    "    df2['date'] = pd.to_datetime(df2['date'])\n",
    "    title = \"Ibsen's outgoing letters by year, gender\"\n",
    "    title1 = title+\" - Addressed to.\"\n",
    "    title2 = title+\" - Mentioning.\"\n",
    "    source = ColumnDataSource(df2)\n",
    "\n",
    "    p = figure(width=800, height=400, x_axis_type='datetime',\n",
    "               title=title1)\n",
    "    d = figure(width=800, height=400, x_axis_type='datetime',\n",
    "               title=title2)\n",
    "\n",
    "    p.scatter(x='date', y='males_addressed', color='blue',  source=source, alpha=0.6, legend_label=\"Men\")\n",
    "    p.scatter(x='date', y='females_addressed', color='hotpink',  source=source, alpha=0.6, legend_label=\"Women\")\n",
    "    p.scatter(x='date', y='others_addressed', color='green',  source=source, alpha=0.3, legend_label=\"N/A (Organizations)\")\n",
    "    p.scatter(x='date', y='anons_addressed', color='grey',  source=source, alpha=0.3, legend_label=\"N/A (Unknown)\")\n",
    "\n",
    "    p.line(x='date', y='males_addressed', color='blue',  source=source, alpha=0.6, legend_label=\"Men\")\n",
    "    p.line(x='date', y='females_addressed', color='hotpink',  source=source, alpha=0.6, legend_label=\"Women\")\n",
    "    p.line(x='date', y='others_addressed', color='green',  source=source, alpha=0.3, legend_label=\"N/A (Organizations)\")\n",
    "    p.line(x='date', y='anons_addressed', color='grey',  source=source, alpha=0.3, legend_label=\"N/A (Unknown)\")\n",
    "\n",
    "\n",
    "\n",
    "    d.scatter(x='date', y='males_mentioned', color='blue',\n",
    "              source=source, alpha=0.6, legend_label=\"Men\")\n",
    "    d.scatter(x='date', y='females_mentioned', color='hotpink', \n",
    "              source=source, alpha=0.6, legend_label=\"Women\")\n",
    "    d.scatter(x='date', y='others_mentioned', color='green',\n",
    "              source=source, alpha=0.3, legend_label=\"N/A (Organizations)\")\n",
    "    d.scatter(x='date', y='anons_mentioned', color='grey',\n",
    "              source=source, alpha=0.3, legend_label=\"N/A (Unknown)\")\n",
    "\n",
    "    d.line(x='date', y='males_mentioned', color='blue',\n",
    "              source=source, alpha=0.6, legend_label=\"Men\")\n",
    "    d.line(x='date', y='females_mentioned', color='hotpink', \n",
    "              source=source, alpha=0.6, legend_label=\"Women\")\n",
    "    d.line(x='date', y='others_mentioned', color='green',\n",
    "              source=source, alpha=0.3, legend_label=\"N/A (Organizations)\")\n",
    "    d.line(x='date', y='anons_mentioned', color='grey',\n",
    "              source=source, alpha=0.3, legend_label=\"N/A (Unknown)\")\n",
    "\n",
    "\n",
    "    p.x_range.range_padding = 0\n",
    "    d.x_range.range_padding = 0\n",
    "    #p.ygrid.gridS_line_color = None\n",
    "\n",
    "    p.legend.location = \"top_left\"\n",
    "    p.legend.click_policy=\"hide\"\n",
    "\n",
    "    d.legend.location = \"top_left\"\n",
    "    d.legend.click_policy=\"hide\"\n",
    "\n",
    "    show(column(p, d))\n",
    "    export_png(column(p, d), filename=\"pngs/ByYear.png\") # CONDAFOX"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f816f3c0",
   "metadata": {},
   "source": [
    "## Plotting 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "id": "6f7eb7c7",
   "metadata": {},
   "outputs": [
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       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
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       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
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       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
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person(s)\",\"text_font_size\":\"15pt\"},\"id\":\"18371\",\"type\":\"Title\"},{\"attributes\":{},\"id\":\"18409\",\"type\":\"UnionRenderers\"},{\"attributes\":{\"factors\":[\"1844\",\"1845\",\"1846\",\"1849\",\"1850\",\"1851\",\"1852\",\"1853\",\"1854\",\"1855\",\"1856\",\"1857\",\"1858\",\"1859\",\"1860\",\"1861\",\"1862\",\"1863\",\"1864\",\"1865\",\"1866\",\"1867\",\"1868\",\"1869\",\"1870\",\"1871\",\"1872\",\"1873\",\"1874\",\"1875\",\"1876\",\"1877\",\"1878\",\"1879\",\"1880\",\"1881\",\"1882\",\"1883\",\"1884\",\"1885\",\"1886\",\"1887\",\"1888\",\"1889\",\"1890\",\"1891\",\"1892\",\"1893\",\"1894\",\"1895\",\"1896\",\"1897\",\"1898\",\"1899\",\"1900\",\"1901\",\"1902\",\"1903\",\"1904\",\"1905\"]},\"id\":\"18373\",\"type\":\"FactorRange\"},{\"attributes\":{\"formatter\":{\"id\":\"18406\"},\"major_label_policy\":{\"id\":\"18407\"},\"major_label_text_font_size\":\"15pt\",\"minor_tick_line_color\":null,\"ticker\":{\"id\":\"18385\"}},\"id\":\"18384\",\"type\":\"LinearAxis\"},{\"attributes\":{\"items\":[{\"id\":\"18412\"},{\"id\":\"18427\"},{\"id\":\"18442\"},{\"id\":\"18457\"}],\"location\":\"top_left\",\"orientation\":\"horizontal\"},\"id\":\"18411\",\"type\":\"Legend\"},{\"attributes\":{},\"id\":\"18410\",\"type\":\"Selection\"},{\"attributes\":{},\"id\":\"18382\",\"type\":\"CategoricalTicker\"},{\"attributes\":{},\"id\":\"18403\",\"type\":\"CategoricalTickFormatter\"},{\"attributes\":{\"axis\":{\"id\":\"18384\"},\"dimension\":1,\"ticker\":null},\"id\":\"18387\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"18404\",\"type\":\"AllLabels\"},{\"attributes\":{},\"id\":\"18385\",\"type\":\"BasicTicker\"},{\"attributes\":{\"active_multi\":null},\"id\":\"18388\",\"type\":\"Toolbar\"},{\"attributes\":{\"bottom\":{\"expr\":{\"id\":\"18395\"}},\"fill_color\":{\"value\":\"grey\"},\"line_color\":{\"value\":\"grey\"},\"top\":{\"expr\":{\"id\":\"18396\"}},\"width\":{\"value\":0.9},\"x\":{\"field\":\"year\"}},\"id\":\"18444\",\"type\":\"VBar\"},{\"attributes\":{\"fields\":[\"males_mentioned\",\"females_mentioned\"]},\"id\":\"18392\",\"type\":\"Stack\"},{\"attributes\":{\"fields\":[\"males_mentioned\"]},\"id\":\"18390\",\"type\":\"Stack\"},{\"attributes\":{\"data\":{\"anons_mentioned\":{\"__ndarray__\":\"AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQAAAAAAAAAAAAAAAQAAAAAAAAAAAAAAAQAAAAAAAAAAAAAAAAAAAAEAAAAAAAAAAAAAAAQAAAABAAAAAgAAAAIAAAAEAAAAAQAAAAcAAAABAAAABAAAAAEAAAACAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAAAAAAAAAADAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA\",\"dtype\":\"int32\",\"order\":\"little\",\"shape\":[60]},\"females_mentioned\":{\"__ndarray__\":\"AgAAAAAAAAAAAAAAAAAAAAEAAAAAAAAAAwAAAAQAAAAAAAAAAAAAAAkAAAACAAAAAAAAAAAAAAABAAAAAAAAAAAAAAACAAAAAgAAAAoAAAAVAAAACQAAAAQAAAASAAAAGQAAABUAAAAXAAAAEwAAABgAAAAXAAAAFwAAABsAAAAVAAAAIgAAABgAAAAQAAAAFQAAAAsAAABHAAAAFQAAAB4AAAAeAAAAMgAAAB4AAAArAAAAJgAAABgAAAAZAAAAGAAAAEgAAAAOAAAAHgAAABIAAAAOAAAACQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA\",\"dtype\":\"int32\",\"order\":\"little\",\"shape\":[60]},\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59],\"males_mentioned\":{\"__ndarray__\":\"BgAAAAAAAAAEAAAAAQAAAAsAAAABAAAAJwAAAAwAAAACAAAAAQAAAAwAAAATAAAABAAAAAoAAAAUAAAABwAAAAQAAAAQAAAADQAAAC0AAACEAAAASwAAAC0AAABvAAAAfgAAAJEAAAB9AAAAyQAAACgAAAB1AAAARwAAAFoAAABnAAAASAAAAEcAAAAtAAAAQwAAACYAAACaAAAALQAAAFkAAAA2AAAAYwAAAEkAAAA4AAAAXgAAACQAAAAnAAAATAAAAIwAAABAAAAATgAAABYAAABFAAAAJQAAAAMAAAAAAAAAAAAAAAEAAAAAAAAA\",\"dtype\":\"int32\",\"order\":\"little\",\"shape\":[60]},\"others_mentioned\":{\"__ndarray__\":\"AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA\",\"dtype\":\"int32\",\"order\":\"little\",\"shape\":[60]},\"year\":[\"1844\",\"1845\",\"1846\",\"1849\",\"1850\",\"1851\",\"1852\",\"1853\",\"1854\",\"1855\",\"1856\",\"1857\",\"1858\",\"1859\",\"1860\",\"1861\",\"1862\",\"1863\",\"1864\",\"1865\",\"1866\",\"1867\",\"1868\",\"1869\",\"1870\",\"1871\",\"1872\",\"1873\",\"1874\",\"1875\",\"1876\",\"1877\",\"1878\",\"1879\",\"1880\",\"1881\",\"1882\",\"1883\",\"1884\",\"1885\",\"1886\",\"1887\",\"1888\",\"1889\",\"1890\",\"1891\",\"1892\",\"1893\",\"1894\",\"1895\",\"1896\",\"1897\",\"1898\",\"1899\",\"1900\",\"1901\",\"1902\",\"1903\",\"1904\",\"1905\"]},\"selected\":{\"id\":\"18410\"},\"selection_policy\":{\"id\":\"18409\"}},\"id\":\"17795\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"source\":{\"id\":\"17795\"}},\"id\":\"18447\",\"type\":\"CDSView\"},{\"attributes\":{\"data_source\":{\"id\":\"17795\"},\"glyph\":{\"id\":\"18444\"},\"hover_glyph\":null,\"muted_glyph\":null,\"name\":\"anons_mentioned\",\"nonselection_glyph\":{\"id\":\"18445\"},\"view\":{\"id\":\"18447\"}},\"id\":\"18446\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"18406\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"bottom\":{\"expr\":{\"id\":\"18395\"}},\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"grey\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"grey\"},\"top\":{\"expr\":{\"id\":\"18396\"}},\"width\":{\"value\":0.9},\"x\":{\"field\":\"year\"}},\"id\":\"18445\",\"type\":\"VBar\"},{\"attributes\":{},\"id\":\"18407\",\"type\":\"AllLabels\"}],\"root_ids\":[\"18370\"]},\"title\":\"Bokeh Application\",\"version\":\"2.3.2\"}};\n",
       "  var render_items = [{\"docid\":\"44ca6785-1aba-4d37-9199-84bed4fb0b27\",\"root_ids\":[\"18370\"],\"roots\":{\"18370\":\"0d146d84-978b-4b9c-a7eb-9a0b9747043d\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "18370"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "if mode != \"cumulative\":\n",
    "    df2 = df.copy()\n",
    "    listm=df2.columns.tolist()\n",
    "    df2.drop(['month','date'],inplace=True,axis=1)\n",
    "    df2 = df2.groupby(\"year\").sum()\n",
    "    df2 = df2.reset_index()\n",
    "\n",
    "    years = df2['year'].tolist()\n",
    "    headers1 = ['males_addressed',\"females_addressed\",\"others_addressed\",\"anons_addressed\"]\n",
    "    headers2 = ['males_mentioned','females_mentioned',\"others_mentioned\",\"anons_mentioned\"]\n",
    "\n",
    "    dfAddr = df2.copy()\n",
    "    dfMent = df2.copy()\n",
    "    colors = [\n",
    "        \"lightblue\",\n",
    "        \"hotpink\",\n",
    "        \"green\",\n",
    "        \"grey\"\n",
    "    ]\n",
    "    #dfAddr = dfAddr.set_index(\"year\")\n",
    "    #dfAddr = dfAddr.T\n",
    "    #collist = dfAddr.columns.tolist()\n",
    "    dfAddr.drop(['males_mentioned','females_mentioned','others_mentioned','anons_mentioned'],inplace=True,axis=1)\n",
    "    dfMent.drop(['males_addressed','females_addressed','others_addressed','anons_addressed'],inplace=True,axis=1)\n",
    "    plotheaders = ['Males','Females','Organizations','Anonymous/Unknown']\n",
    "    source = ColumnDataSource(dfAddr)\n",
    "    source2 = ColumnDataSource(dfMent)\n",
    "    p = figure(x_range=years, height=500,width=1000, title=\"Ibsen's letters by year, gender of recipient(s)\",\n",
    "               toolbar_location=None, tools=\"\")\n",
    "\n",
    "    p.vbar_stack(headers1, x='year', width=0.9,\n",
    "                 source=source,legend_label=plotheaders,color=colors)\n",
    "\n",
    "    p.y_range.start = 0\n",
    "    p.x_range.range_padding = 0\n",
    "    p.xgrid.grid_line_color = None\n",
    "    p.axis.minor_tick_line_color = None\n",
    "    p.outline_line_color = None\n",
    "    p.legend.location = \"top_left\"\n",
    "    p.legend.orientation = \"horizontal\"\n",
    "    p.xaxis.major_label_orientation = 3.14/4\n",
    "    #p.xaxis.major_label_text_font_size = \"10pt\"\n",
    "    p.yaxis.major_label_text_font_size = \"8pt\"\n",
    "    p.title.text_font_size = '15pt'\n",
    "    show(p)\n",
    "\n",
    "    d = figure(x_range=years, height=500,width=1000, title=\"Ibsen's letters by year, gender of mentioned person(s)\",\n",
    "               toolbar_location=None, tools=\"\")\n",
    "\n",
    "    d.vbar_stack(headers2, x='year', width=0.9,\n",
    "                 source=source2,legend_label=plotheaders,color=colors)\n",
    "\n",
    "    d.y_range.start = 0\n",
    "    d.x_range.range_padding = 0\n",
    "    d.xgrid.grid_line_color = None\n",
    "    d.axis.minor_tick_line_color = None\n",
    "    d.outline_line_color = None\n",
    "    #d.xaxis.major_label_text_font_size = \"10pt\"\n",
    "    d.yaxis.major_label_text_font_size = \"15pt\"\n",
    "    d.title.text_font_size = '15pt'\n",
    "    d.legend.location = \"top_left\"\n",
    "    d.legend.orientation = \"horizontal\"\n",
    "    d.xaxis.major_label_orientation = 3.14/4\n",
    "    show(d)\n",
    "    export_png(p, filename=\"pngs/RecipsByYear.png\") # CONDAFOX\n",
    "    export_png(d, filename=\"pngs/MentionsByYear.png\") # CONDAFOX"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "id": "f5346bac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <div class=\"bk-root\" id=\"627caf08-b131-4940-bfce-7027a8da110e\" data-root-id=\"17193\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
       "  var docs_json = {\"3d801d0c-12c8-45b2-99e1-1a6c32717785\":{\"defs\":[],\"roots\":{\"references\":[{\"attributes\":{\"below\":[{\"id\":\"17204\"}],\"center\":[{\"id\":\"17207\"},{\"id\":\"17210\"}],\"height\":550,\"left\":[{\"id\":\"17208\"}],\"renderers\":[{\"id\":\"17215\"}],\"title\":{\"id\":\"17194\"},\"toolbar\":{\"id\":\"17211\"},\"toolbar_location\":null,\"width\":1200,\"x_range\":{\"id\":\"17196\"},\"x_scale\":{\"id\":\"17200\"},\"y_range\":{\"id\":\"17198\"},\"y_scale\":{\"id\":\"17202\"}},\"id\":\"17193\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"data_source\":{\"id\":\"17192\"},\"glyph\":{\"id\":\"17213\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"17214\"},\"view\":{\"id\":\"17216\"}},\"id\":\"17215\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"17642\",\"type\":\"AllLabels\"},{\"attributes\":{\"data\":{\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13],\"job\":[\"publisher, bookseller\",\"bookseller\",\"author\",\"publisher\",\"author, critic\",\"actor, theatre manager\",\"art historian, historian, litt\\u00e9rateur\",\"actor\",\"teacher\",\"painter\",\"translator\",\"civil servant\",\"journalist\",\"actor, theatre director\"],\"mentions\":{\"__ndarray__\":\"ggAAAKsAAAB1AQAAiAAAAG0AAABGAAAACAAAABcBAAAqAAAAnQAAADYAAAAlAAAADwAAAC8AAAA=\",\"dtype\":\"int32\",\"order\":\"little\",\"shape\":[14]},\"receiveds\":{\"__ndarray__\":\"IwEAALEAAACSAAAAXQAAAEIAAABCAAAAOAAAADUAAAAuAAAAJAAAABwAAAAaAAAAGgAAABgAAAA=\",\"dtype\":\"int32\",\"order\":\"little\",\"shape\":[14]}},\"selected\":{\"id\":\"17648\"},\"selection_policy\":{\"id\":\"17647\"}},\"id\":\"17192\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"17648\",\"type\":\"Selection\"},{\"attributes\":{\"formatter\":{\"id\":\"17644\"},\"major_label_policy\":{\"id\":\"17645\"},\"major_label_text_font_size\":\"15pt\",\"ticker\":{\"id\":\"17209\"}},\"id\":\"17208\",\"type\":\"CategoricalAxis\"},{\"attributes\":{},\"id\":\"17647\",\"type\":\"UnionRenderers\"},{\"attributes\":{},\"id\":\"17196\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"17200\",\"type\":\"LinearScale\"},{\"attributes\":{\"formatter\":{\"id\":\"17641\"},\"major_label_orientation\":0.785,\"major_label_policy\":{\"id\":\"17642\"},\"major_label_text_font_size\":\"10pt\",\"ticker\":{\"id\":\"17205\"}},\"id\":\"17204\",\"type\":\"LinearAxis\"},{\"attributes\":{\"factors\":[\"publisher, bookseller\",\"bookseller\",\"author\",\"publisher\",\"author, critic\",\"actor, theatre manager\",\"art historian, historian, litt\\u00e9rateur\",\"actor\",\"teacher\",\"painter\",\"translator\",\"civil servant\",\"journalist\",\"actor, theatre director\"]},\"id\":\"17198\",\"type\":\"FactorRange\"},{\"attributes\":{\"fill_color\":{\"value\":\"black\"},\"height\":{\"value\":0.5},\"line_width\":{\"value\":0.9},\"right\":{\"field\":\"receiveds\"},\"y\":{\"field\":\"job\"}},\"id\":\"17213\",\"type\":\"HBar\"},{\"attributes\":{\"axis\":{\"id\":\"17208\"},\"dimension\":1,\"ticker\":null},\"id\":\"17210\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"17202\",\"type\":\"CategoricalScale\"},{\"attributes\":{\"text\":\"Ibsen's letters, sorted by recipient's professions, excl. organizations, top 14\",\"text_font_size\":\"15pt\"},\"id\":\"17194\",\"type\":\"Title\"},{\"attributes\":{},\"id\":\"17205\",\"type\":\"BasicTicker\"},{\"attributes\":{\"active_multi\":null},\"id\":\"17211\",\"type\":\"Toolbar\"},{\"attributes\":{},\"id\":\"17641\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"17209\",\"type\":\"CategoricalTicker\"},{\"attributes\":{\"axis\":{\"id\":\"17204\"},\"grid_line_color\":\"grey\",\"ticker\":null},\"id\":\"17207\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"17645\",\"type\":\"AllLabels\"},{\"attributes\":{\"source\":{\"id\":\"17192\"}},\"id\":\"17216\",\"type\":\"CDSView\"},{\"attributes\":{},\"id\":\"17644\",\"type\":\"CategoricalTickFormatter\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"black\"},\"height\":{\"value\":0.5},\"line_alpha\":{\"value\":0.1},\"line_width\":{\"value\":0.9},\"right\":{\"field\":\"receiveds\"},\"y\":{\"field\":\"job\"}},\"id\":\"17214\",\"type\":\"HBar\"}],\"root_ids\":[\"17193\"]},\"title\":\"Bokeh Application\",\"version\":\"2.3.2\"}};\n",
       "  var render_items = [{\"docid\":\"3d801d0c-12c8-45b2-99e1-1a6c32717785\",\"root_ids\":[\"17193\"],\"roots\":{\"17193\":\"627caf08-b131-4940-bfce-7027a8da110e\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "17193"
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "'C:\\\\Users\\\\lokes\\\\OneDrive - Universitetet i Oslo\\\\Desktop\\\\Notebooks\\\\INR\\\\pngs\\\\recipients-professions.png'"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jobs = personer.copy()\n",
    "jobs.drop(['birthday','deathday'],inplace=True,axis=1)\n",
    "for idx,row in jobs.iterrows():\n",
    "    if row['job'] == 0:\n",
    "        jobs.drop(idx,inplace=True,axis=0)\n",
    "    if row['job'] == 'married to':\n",
    "        jobs.drop(idx,inplace=True,axis=0)\n",
    "    if row['job'] == 'organization':\n",
    "        jobs.drop(idx,inplace=True,axis=0)\n",
    "jobs = jobs.reset_index(drop=True)\n",
    "jobs = jobs.groupby(['job']).sum().sort_values(['receiveds','mentions'],ascending=False).head(14)\n",
    "jobs = jobs.reset_index()\n",
    "        \n",
    "jobs\n",
    "\n",
    "job = jobs['job']\n",
    "\n",
    "source=ColumnDataSource(jobs)\n",
    "\n",
    "p = figure(y_range=job, height=550, width=1200, title=\"Ibsen's letters, sorted by recipient's professions, excl. organizations, top 14\",\n",
    "           toolbar_location=None, tools=\"\")\n",
    "\n",
    "p.hbar(y=\"job\", right=\"receiveds\", height=0.5, width=0.9,color=\"black\",source=source)\n",
    "\n",
    "p.xaxis.major_label_text_font_size = \"10pt\"\n",
    "p.yaxis.major_label_text_font_size = \"15pt\"\n",
    "p.title.text_font_size = '15pt'\n",
    "\n",
    "p.xgrid.grid_line_color = \"grey\"\n",
    "#p.y_range.start = 0\n",
    "p.xaxis.major_label_orientation = 3.14/4\n",
    "show(p)\n",
    "export_png(p, filename=\"pngs/recipients-professions.png\") # CONDAFOX"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e15ada37",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "4fefe556",
   "metadata": {},
   "source": [
    "## Works\n",
    "With the brev df:\n",
    "1. DROP all letters that do not mention at least 1 work.\n",
    "2. GET all works?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "id": "965d2d88",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "df2 = brev.copy()\n",
    "dfX = df2.copy()\n",
    "times = []\n",
    "works = []\n",
    "verksliste = []\n",
    "amounts = []\n",
    "#dfX = dfX.set_index('datetimes',drop=False)\n",
    "\n",
    "#raise KeyboardInterrupt\n",
    "i=0\n",
    "for work in dfX['mentionWorkID']:\n",
    "    if work == 0: # hvis work er null, dropp raden\n",
    "        dfX.drop(i,axis=0,inplace=True)\n",
    "    else: # hvis ikke, splitt raden for å opprette verksliste\n",
    "        x = work.split(\", \")\n",
    "        for item in x: # lag \n",
    "            if item not in verksliste:\n",
    "                verksliste.append(item)\n",
    "    i+=1\n",
    "for verk in verksliste:\n",
    "    dfX[verk] = 0 # You'll get a column of all 5s\n",
    "dfX.drop(['senderID', 'sender', 'mentionIDs', 'mentions', 'mentionORGID', 'mentionORG', 'recipientID', 'recipient', 'date',\n",
    "       'dispatch', 'dispatchabbr', 'geonameID', 'toponymName','country', 'lat', 'lon', 'address', 'location',\n",
    "       'locationabbr', 'tolat', 'tolon', 'mentionPlaces', 'mentionPlacesabbr','collectiveversionid'],axis=1,inplace=True)\n",
    "\n",
    "i=0\n",
    "for work in dfX['mentionWorkID']:\n",
    "    x = work.split(\", \")\n",
    "    for item in x:\n",
    "        dfX.iloc[i, dfX.columns.get_loc(item)] = 1\n",
    "    i+=1\n",
    "dfX.drop(['letterID', 'mentionWorkID', 'mentionWork', 'textID',\n",
    "       'mentionWorkGenre'],axis=1,inplace=True)\n",
    "#dfX = dfX.set_index('datetimes',drop=True)\n",
    "dfX.drop('datetimes',axis=1,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 249,
   "id": "b406a729",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "58"
      ]
     },
     "execution_count": 249,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "errors = []\n",
    "dupes = []\n",
    "for col in dfX.columns:\n",
    "    if \"[\" in col:\n",
    "        dupes.append(col)\n",
    "        what = col.strip(\"[]\")\n",
    "        errors.append(what)\n",
    "dfT = dfX.copy()\n",
    "i = 0\n",
    "columns = dfX.columns\n",
    "for col in columns:\n",
    "    if col in errors:\n",
    "        newname = \"NEW \"+col\n",
    "        #print(newname)\n",
    "        dfX[newname] = dfX[col]+dfX[dupes[i]]\n",
    "        dfX.drop([col,dupes[i]],inplace=True,axis=1)\n",
    "        \n",
    "        i+=1\n",
    "#dfT.columns.tolist()\n",
    "columns = dfX.columns\n",
    "newcols = []\n",
    "for col in columns:\n",
    "    newcol = col.strip(\"NEW []\")\n",
    "    newcol = newcol.strip(\"wo\")\n",
    "    newcols.append(newcol)\n",
    "dfX.columns = newcols\n",
    "dfX.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "id": "eac3160e",
   "metadata": {},
   "outputs": [
    {
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       "<p>853 rows × 58 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Balm  FpA  DiMaane  Di  DiAur  DiRose  DiTilRH  OmKj  OL1  DiTilCJ  ...  \\\n",
       "4        0    0        0   0      0       0        0     0    0        0  ...   \n",
       "5        1    1        0   0      0       0        0     0    0        0  ...   \n",
       "7        0    0        1   0      0       0        0     0    0        0  ...   \n",
       "10       0    0        0   1      0       0        0     0    0        0  ...   \n",
       "18       0    0        0   0      1       0        0     0    0        0  ...   \n",
       "...    ...  ...      ...  ..    ...     ...      ...   ...  ...      ...  ...   \n",
       "2185     0    0        0   0      0       0        0     0    0        0  ...   \n",
       "2240     0    0        0   0      0       0        0     0    0        0  ...   \n",
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       "2386     0    0        0   0      0       0        0     0    0        0  ...   \n",
       "\n",
       "      F2  C2  LB  Et_Ri  Du  Ge  F  Vi  G2  R  \n",
       "4      0   0   0      0   0   0  0   0   0  0  \n",
       "5      0   0   0      0   0   0  0   0   0  0  \n",
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       "10     0   0   0      0   0   0  0   0   0  0  \n",
       "18     0   0   0      0   0   0  0   0   0  0  \n",
       "...   ..  ..  ..    ...  ..  .. ..  ..  .. ..  \n",
       "2185   0   0   0      0   0   0  1   0   0  0  \n",
       "2240   0   0   0      0   0   0  0   1   0  0  \n",
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       "2338   0   0   0      0   0   0  0   0   0  0  \n",
       "2386   0   0   0      0   0   0  0   0   0  1  \n",
       "\n",
       "[853 rows x 58 columns]"
      ]
     },
     "execution_count": 173,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "id": "278c93ea",
   "metadata": {},
   "outputs": [
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2240</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2252</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2338</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2386</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>853 rows × 58 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Balm  FpA  DiMaane  Di  DiAur  DiRose  DiTilRH  OmKj  OL1  DiTilCJ  ...  \\\n",
       "4        0    0        0   0      0       0        0     0    0        0  ...   \n",
       "5        1    1        0   0      0       0        0     0    0        0  ...   \n",
       "7        0    0        1   0      0       0        0     0    0        0  ...   \n",
       "10       0    0        0   1      0       0        0     0    0        0  ...   \n",
       "18       0    0        0   0      1       0        0     0    0        0  ...   \n",
       "...    ...  ...      ...  ..    ...     ...      ...   ...  ...      ...  ...   \n",
       "2185     0    0        0   0      0       0        0     0    0        0  ...   \n",
       "2240     0    0        0   0      0       0        0     0    0        0  ...   \n",
       "2252     0    0        0   0      0       0        0     0    0        0  ...   \n",
       "2338     0    0        0   0      0       0        0     0    0        0  ...   \n",
       "2386     0    0        0   0      0       0        0     0    0        0  ...   \n",
       "\n",
       "      F2  C2  LB  Et_Ri  Du  Ge  F  Vi  G2  R  \n",
       "4      0   0   0      0   0   0  0   0   0  0  \n",
       "5      0   0   0      0   0   0  0   0   0  0  \n",
       "7      0   0   0      0   0   0  0   0   0  0  \n",
       "10     0   0   0      0   0   0  0   0   0  0  \n",
       "18     0   0   0      0   0   0  0   0   0  0  \n",
       "...   ..  ..  ..    ...  ..  .. ..  ..  .. ..  \n",
       "2185   0   0   0      0   0   0  1   0   0  0  \n",
       "2240   0   0   0      0   0   0  0   1   0  0  \n",
       "2252   0   0   0      0   0   0  0   0   0  0  \n",
       "2338   0   0   0      0   0   0  0   0   0  0  \n",
       "2386   0   0   0      0   0   0  0   0   0  1  \n",
       "\n",
       "[853 rows x 58 columns]"
      ]
     },
     "execution_count": 176,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gh = dfX.columns\n",
    "cols = []\n",
    "for col in gh:\n",
    "    cols.append(col)\n",
    "cols\n",
    "#dfX = dfX.reset_index(drop=False)\n",
    "dfZ = dfX.copy()\n",
    "dfZ"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 269,
   "id": "a4a2f7ac",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Standard name KK is Kjærlighedens Komedie\n",
      "Standard name KG is Kejser og Galilæer\n",
      "Standard name FH is Fruen fra havet\n",
      "Standard name HG is Hedda Gabler\n",
      "Standard name C1 is Catilina, 1. Versjon\n",
      "Standard name G1 is Gildet paa Solhoug, 1. versjon\n",
      "Standard name F1 is Fru Inger til Østeraad, 1. versjon\n",
      "ALTERNATIVE NAME HH is Hærmændene på Helgeland\n",
      "ALTERNATIVE NAME K is Kjæmpehøien\n",
      "Standard name Br is Brand\n",
      "Standard name PG is Peer Gynt\n",
      "Standard name UF is De unges Forbund\n",
      "Standard name SS is Samfundets støtter\n",
      "Standard name F2 is Fru Inger til Østråt, 2. versjon\n",
      "Standard name C2 is Catilina, 2. versjon\n",
      "Standard name Du is Et dukkehjem\n",
      "Standard name Ge is Gengangere\n",
      "ALTERNATIVE NAME F is Fru Inger til Østråt\n",
      "Standard name Vi is Vildanden\n",
      "Standard name G2 is Gildet på Solhaug, 2. versjon\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "['Di',\n",
       " 'Kjærlighedens Komedie',\n",
       " 'Kejser og Galilæer',\n",
       " 'Fruen fra havet',\n",
       " 'Hedda Gabler',\n",
       " 'Catilina, 1. Versjon',\n",
       " 'Gildet paa Solhoug, 1. versjon',\n",
       " 'Fru Inger til Østeraad, 1. versjon',\n",
       " 'Hærmændene på Helgeland',\n",
       " 'Kjæmpehøien',\n",
       " 'Brand',\n",
       " 'Peer Gynt',\n",
       " 'De unges Forbund',\n",
       " 'Samfundets støtter',\n",
       " 'Fru Inger til Østråt, 2. versjon',\n",
       " 'Catilina, 2. versjon',\n",
       " 'Et dukkehjem',\n",
       " 'Gengangere',\n",
       " 'Fru Inger til Østråt',\n",
       " 'Vildanden',\n",
       " 'Gildet på Solhaug, 2. versjon',\n",
       " 'R']"
      ]
     },
     "execution_count": 269,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cols = dfZ.columns\n",
    "#for idx, row in dfZ.iterrows():\n",
    "f = dfZ.sum()\n",
    "i=0\n",
    "verksoversikt = pd.read_excel('verk.xlsx', index_col=0)\n",
    "\n",
    "verksoversikt = verksoversikt.dropna()\n",
    "\n",
    "verksoversikt = verksoversikt.reset_index()\n",
    "xvals = [\n",
    "\n",
    "]\n",
    "yvals= []\n",
    "for fa in f:\n",
    "    if fa > 10:\n",
    "        pass\n",
    "        #print(cols[i],fa)\n",
    "        xvals.append(cols[i])\n",
    "        yvals.append(fa)\n",
    "    i+=1\n",
    "i = 0\n",
    "plainnames = {}\n",
    "for uid in verksoversikt['HISe-ID']:\n",
    "    newname = verksoversikt['Original tittel'][i]\n",
    "    #print(uid,newname)\n",
    "    plainnames[uid] = newname\n",
    "    i+=1\n",
    "i = 0\n",
    "altnames = {}\n",
    "for uid in verksoversikt['felles-ID']:\n",
    "    newname = verksoversikt['Original tittel'][i]\n",
    "    #print(uid,newname)\n",
    "    altnames[uid] = newname\n",
    "    i+=1\n",
    "#plainnames # Dict med uid : navn\n",
    "i=0\n",
    "for xval in xvals:\n",
    "    if xval in plainnames:\n",
    "        print(\"Standard name\",xval,\"is\",plainnames[xval])\n",
    "        xvals[i] = plainnames[xval]\n",
    "    elif xval in altnames:\n",
    "        altname = altnames[xval]\n",
    "        altname = altname[:-12]\n",
    "        print(\"ALTERNATIVE NAME\",xval,\"is\",altname)\n",
    "        xvals[i] = altname\n",
    "    else:\n",
    "        pass\n",
    "    i+=1\n",
    "xvals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 270,
   "id": "4eaca868",
   "metadata": {},
   "outputs": [],
   "source": [
    "import random\n",
    "colors = []\n",
    "for x in xvals:\n",
    "    color = \"#\"+''.join([random.choice('ABCDEF0123456789') for i in range(6)])\n",
    "    colors.append(color)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 273,
   "id": "df21e386",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
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         "legendgroup": "Di",
         "marker": {
          "color": "#636efa",
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         "yaxis": "y"
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         "legendgroup": "Hedda Gabler",
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         "hovertemplate": "color=Fru Inger til Østeraad, 1. versjon<br>Works mentioned=%{x}<br>Times mentioned=%{y}<extra></extra>",
         "legendgroup": "Fru Inger til Østeraad, 1. versjon",
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         "textposition": "auto",
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         "hovertemplate": "color=Hærmændene på Helgeland<br>Works mentioned=%{x}<br>Times mentioned=%{y}<extra></extra>",
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         "alignmentgroup": "True",
         "hovertemplate": "color=Brand<br>Works mentioned=%{x}<br>Times mentioned=%{y}<extra></extra>",
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   ],
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    "import plotly.express as px\n",
    "#df = px.data.iris()\n",
    "fig = px.bar(x=xvals, y=yvals, color=xvals, width=1200, height=800,\n",
    "                title=\"Ibsen's mentions of his own works through correspondence\",\n",
    "                labels=dict(x=\"Works mentioned\", y=\"Times mentioned\"))\n",
    "fig.update_xaxes(categoryorder='total ascending')\n",
    "fig.update_xaxes(tickangle=45)\n",
    "fig.update_layout(showlegend=False)\n",
    "fig.update_coloraxes(showscale=False)\n",
    "#fig.update_xaxes(categoryorder='array', categoryarray=['January', 'February', 'March', 'April', 'May', 'June', 'July', 'August', 'September', 'October', 'November', 'December'])\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "02bdc3a4",
   "metadata": {},
   "outputs": [],
   "source": [
    "source = ColumnDataSource(dfZ)\n",
    "\n",
    "p = figure(title=\"ÅÅÅÅÅÅÅÅÅÅÅÅÅÅÅ\", x_axis_label='date', y_axis_label='work')\n",
    "i = 0\n",
    "\n",
    "for val in xvals:\n",
    "    p.scatter(x=val,y=yvals[i], legend_label=val, line_width=1, source=source)\n",
    "    i+=1\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bf457b2c",
   "metadata": {},
   "outputs": [],
   "source": [
    "dfX = dfX.set_index('datetimes',drop=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "018a1800",
   "metadata": {},
   "source": [
    "# DEBUG LAND\n",
    "~~1857 257 40 | 3130 943 0?~~\n",
    "1857 257 189 | 3130 943 0?\n",
    ">:|\n",
    "\n",
    "Personfilen angir tallene over som (kumulativt) (addr.|ment.) M1852, F260, O203  |  M3562 F1073 O0. Se under...\n",
    "\n",
    "1. Oops. Liten skriveleif førte til at others_addressed ble veldig lavt. Fikset nå til 189."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9f72be98",
   "metadata": {},
   "outputs": [],
   "source": [
    "raise KeyboardInterrupt\n",
    "personer.groupby(\"sex\").sum() # teller ikke når sex == 0....."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8d20eb03",
   "metadata": {},
   "outputs": [],
   "source": [
    "totaladdrs2=0\n",
    "totalmentions2=0\n",
    "for recs in personer['receiveds']:\n",
    "    totaladdrs2+=recs\n",
    "for mens in personer['mentions']:\n",
    "    totalmentions2+=mens\n",
    "print(\"Fra script:\",totaladdrs,totalmentions) # Hvor mange mottakere og nevnte personer skriptet henter\n",
    "print(\" vs\")\n",
    "print(\"Fra personfilen:\",totaladdrs2,totalmentions2,\"... hmmmm.\") # Hvor mange mottakere og nevnte personer personregisteret hevder det er"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "303dc1bf",
   "metadata": {},
   "source": [
    "Daaaa er det nok noe som er feil et sted. Enten har brevfilen ikke alle brev, eller så har personregisteret feil, eller so har ikke brevfilen alle mentions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0910d599",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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