analyzing-headlines-with-spacy.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Analyzing news headlines with spaCy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For many machine learning tasks, we must collect specific training data, labeling the data, and invest substantial time in developing a custom model for our purpose. However, there are some tasks that are sufficiently universal that pre-trained models can provide at least a proof of concept, and perhaps a production solution.\n",
    "\n",
    "One area where this is common is natural language processing. Language use varies between sources&mdash;a quarterly financial report will differ substantially from comic book dialogue&mdash;but most of the essential rules of a given language (we'll stick with English for this notebook) do not change between sources. This means that language models trained for certain tasks are widely applicable. Even if a better result would be possible with a model that is fine tuned to a dataset, the feasibility of a product can often be evaluated with pre-trained solutions.\n",
    "\n",
    "The [spaCy](https://spacy.io/) library from [explosion.ai](https://explosion.ai/) is designed to provide production ready solutions to NLP tasks. The emphasis is on exposing mature capabilities for real-world use, as opposed to providing a comprehensive list of subtly-different models.\n",
    "\n",
    "In this notebook, we'll use spaCy for named entity recognition (NER). In NER, the task is to identify so-called named entities in a body of text, and classify their entity type. By default, spaCy recognises [18 distinct categories](https://spacy.io/api/annotation#named-entities) of named entity, encompassing people, geopolitical entities, dates, works of arts, monetary figures and more.\n",
    "\n",
    "Our use case is to investigate the appearance of organisations in Reuters news headlines. Tracking organisational appearances is interesting in itself, and could form part of a pipeline for competitive analysis, national statistical reporting or sector-specific analysis (for instance, in banking)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup notebook dependencies\n",
    "\n",
    "First we must install a couple of dependencies, import them, and enable inline plotting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture\n",
    "# ^ hiding large cell output. disable for logs.\n",
    "!pip3 install spacy==2.3.4 pandas==1.1.4 numpy==1.19.4 matplotlib==3.3.3 seaborn==0.11.0\n",
    "!python3 -m spacy download en_core_web_sm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "Bad key backend.qt4 in file /etc/matplotlib/matplotlibrc, line 43 ('backend.qt4 : PyQt4        # PyQt4 | PySide')\n",
      "You probably need to get an updated matplotlibrc file from\n",
      "https://github.com/matplotlib/matplotlib/blob/v3.3.3/matplotlibrc.template\n",
      "or from the matplotlib source distribution\n"
     ]
    }
   ],
   "source": [
    "import spacy\n",
    "import en_core_web_sm\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We'l use a public domain dataset of Reuters news headlines spanning March 2018 through July 2020 (from [Kaggle](https://www.kaggle.com/notlucasp/financial-news-headlines)). The data contains more than 32,000 headlines, with associated dates, and a short article description (which we ignore). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Headlines</th>\n",
       "      <th>Time</th>\n",
       "      <th>Description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>TikTok considers London and other locations fo...</td>\n",
       "      <td>2020-07-18</td>\n",
       "      <td>TikTok has been in discussions with the UK gov...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Disney cuts ad spending on Facebook amid growi...</td>\n",
       "      <td>2020-07-18</td>\n",
       "      <td>Walt Disney  has become the latest company to ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Trail of missing Wirecard executive leads to B...</td>\n",
       "      <td>2020-07-18</td>\n",
       "      <td>Former Wirecard  chief operating officer Jan M...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Twitter says attackers downloaded data from up...</td>\n",
       "      <td>2020-07-18</td>\n",
       "      <td>Twitter Inc said on Saturday that hackers were...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>U.S. Republicans seek liability protections as...</td>\n",
       "      <td>2020-07-17</td>\n",
       "      <td>A battle in the U.S. Congress over a new coron...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                           Headlines       Time  \\\n",
       "0  TikTok considers London and other locations fo... 2020-07-18   \n",
       "1  Disney cuts ad spending on Facebook amid growi... 2020-07-18   \n",
       "2  Trail of missing Wirecard executive leads to B... 2020-07-18   \n",
       "3  Twitter says attackers downloaded data from up... 2020-07-18   \n",
       "4  U.S. Republicans seek liability protections as... 2020-07-17   \n",
       "\n",
       "                                         Description  \n",
       "0  TikTok has been in discussions with the UK gov...  \n",
       "1  Walt Disney  has become the latest company to ...  \n",
       "2  Former Wirecard  chief operating officer Jan M...  \n",
       "3  Twitter Inc said on Saturday that hackers were...  \n",
       "4  A battle in the U.S. Congress over a new coron...  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reuters_headline_df = pd.read_csv('reuters_headlines.csv', parse_dates=[1])\n",
    "reuters_headline_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extract entities with spaCy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To detect entities and their type (spaCy refers to this as their _label_) in text, we must use a statistical model. Here, we use spaCy's `en_core_web_sm` model. This is an English language model trained on web data, and is lightweight at 11MB. Larger versions of this model, and their performance characteristics, can be found in the [spaCy docs](https://spacy.io/models/en). spaCy also provides support for [non-English languages](https://spacy.io/usage/models#languages). Under the hood, this is a convolutional neural network, but since it is already trained and we're using it as is, we can consider it a simple function with known statistical performance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "nlp = en_core_web_sm.load()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To extract entities from a single document, we simply calling `nlp` on the document: `nlp(\"Here is some text\")`. When we do so, the text is tokenized, and several components of an NLP pipeline are run on the tokens: they're tagged for part-of-speech labels (verb, noun, etc.) and assigned dependency labels with a parser.\n",
    "\n",
    "To extract entities from many headlines, it is considerably more performant to use spaCy's built in pipeline abstraction than to `apply` the operation with pandas. Since we care only about extracting named entities from the text, we can also disable the tagger and parser to avoid unnecessary work, improving speed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "entity_pipe = nlp.pipe(reuters_headline_df.Headlines, disable=['tagger', 'parser'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# even with above performance considerations, this cell takes a minute\n",
    "reuters_headline_df['Entities'] = [x.ents for x in entity_pipe]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For convenience, we'll construct a new DataFrame with only the columns we care about: date, headline, entity and entity label. Each row in the DataFrame is a single entity that has been extracted, so headlines containing multiple entities may appear multiple times."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "entity_df = (\n",
    "    reuters_headline_df\n",
    "    .explode('Entities')\n",
    "    [['Time', 'Headlines', 'Entities']]\n",
    "    .rename(columns={'Entities': 'Entity', 'Headlines': 'Headline', 'Time': 'Date'})\n",
    "    .dropna()\n",
    "    .assign(\n",
    "        Label = lambda df: df.Entity.apply(lambda x: x.label_),\n",
    "        Entity = lambda df: df.Entity.apply(lambda x: x.text)\n",
    "    )\n",
    "    .reset_index(drop=True)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\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>Date</th>\n",
       "      <th>Headline</th>\n",
       "      <th>Entity</th>\n",
       "      <th>Label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-07-18</td>\n",
       "      <td>TikTok considers London and other locations fo...</td>\n",
       "      <td>London</td>\n",
       "      <td>GPE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-07-18</td>\n",
       "      <td>Disney cuts ad spending on Facebook amid growi...</td>\n",
       "      <td>Facebook</td>\n",
       "      <td>ORG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-07-18</td>\n",
       "      <td>Trail of missing Wirecard executive leads to B...</td>\n",
       "      <td>Wirecard</td>\n",
       "      <td>ORG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-07-18</td>\n",
       "      <td>Trail of missing Wirecard executive leads to B...</td>\n",
       "      <td>Belarus</td>\n",
       "      <td>GPE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-07-18</td>\n",
       "      <td>Trail of missing Wirecard executive leads to B...</td>\n",
       "      <td>Der Spiegel</td>\n",
       "      <td>PERSON</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date                                           Headline       Entity  \\\n",
       "0 2020-07-18  TikTok considers London and other locations fo...       London   \n",
       "1 2020-07-18  Disney cuts ad spending on Facebook amid growi...     Facebook   \n",
       "2 2020-07-18  Trail of missing Wirecard executive leads to B...     Wirecard   \n",
       "3 2020-07-18  Trail of missing Wirecard executive leads to B...      Belarus   \n",
       "4 2020-07-18  Trail of missing Wirecard executive leads to B...  Der Spiegel   \n",
       "\n",
       "    Label  \n",
       "0     GPE  \n",
       "1     ORG  \n",
       "2     ORG  \n",
       "3     GPE  \n",
       "4  PERSON  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "entity_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "SpaCy provides a nice built in visualizer for extracted entities. Let's take a look at a couple of examples:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<span class=\"tex2jax_ignore\"><div class=\"entities\" style=\"line-height: 2.5; direction: ltr\">Disney cuts ad spending on \n",
       "<mark class=\"entity\" style=\"background: #7aecec; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Facebook\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; text-transform: uppercase; vertical-align: middle; margin-left: 0.5rem\">ORG</span>\n",
       "</mark>\n",
       " amid growing boycott: WSJ</div></span>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<span class=\"tex2jax_ignore\"><div class=\"entities\" style=\"line-height: 2.5; direction: ltr\">TikTok considers \n",
       "<mark class=\"entity\" style=\"background: #feca74; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    London\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; text-transform: uppercase; vertical-align: middle; margin-left: 0.5rem\">GPE</span>\n",
       "</mark>\n",
       " and other locations for headquarters</div></span>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<span class=\"tex2jax_ignore\"><div class=\"entities\" style=\"line-height: 2.5; direction: ltr\">\n",
       "<mark class=\"entity\" style=\"background: #7aecec; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    KPMG\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; text-transform: uppercase; vertical-align: middle; margin-left: 0.5rem\">ORG</span>\n",
       "</mark>\n",
       " hit by \n",
       "<mark class=\"entity\" style=\"background: #feca74; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Hong Kong High Court\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; text-transform: uppercase; vertical-align: middle; margin-left: 0.5rem\">GPE</span>\n",
       "</mark>\n",
       " in \n",
       "<mark class=\"entity\" style=\"background: #e4e7d2; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    $400 million\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; text-transform: uppercase; vertical-align: middle; margin-left: 0.5rem\">MONEY</span>\n",
       "</mark>\n",
       " \n",
       "<mark class=\"entity\" style=\"background: #7aecec; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    China Medical\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; text-transform: uppercase; vertical-align: middle; margin-left: 0.5rem\">ORG</span>\n",
       "</mark>\n",
       " fraud</div></span>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<span class=\"tex2jax_ignore\"><div class=\"entities\" style=\"line-height: 2.5; direction: ltr\">\n",
       "<mark class=\"entity\" style=\"background: #feca74; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Abu Dhabi's\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; text-transform: uppercase; vertical-align: middle; margin-left: 0.5rem\">GPE</span>\n",
       "</mark>\n",
       " \n",
       "<mark class=\"entity\" style=\"background: #7aecec; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Etihad Airways\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; text-transform: uppercase; vertical-align: middle; margin-left: 0.5rem\">ORG</span>\n",
       "</mark>\n",
       " restructures \n",
       "<mark class=\"entity\" style=\"background: #7aecec; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Airbus\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; text-transform: uppercase; vertical-align: middle; margin-left: 0.5rem\">ORG</span>\n",
       "</mark>\n",
       ", \n",
       "<mark class=\"entity\" style=\"background: #7aecec; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Boeing\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; text-transform: uppercase; vertical-align: middle; margin-left: 0.5rem\">ORG</span>\n",
       "</mark>\n",
       " jet orders</div></span>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<span class=\"tex2jax_ignore\"><div class=\"entities\" style=\"line-height: 2.5; direction: ltr\">Trail of missing \n",
       "<mark class=\"entity\" style=\"background: #7aecec; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Wirecard\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; text-transform: uppercase; vertical-align: middle; margin-left: 0.5rem\">ORG</span>\n",
       "</mark>\n",
       " executive leads to \n",
       "<mark class=\"entity\" style=\"background: #feca74; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Belarus\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; text-transform: uppercase; vertical-align: middle; margin-left: 0.5rem\">GPE</span>\n",
       "</mark>\n",
       ", \n",
       "<mark class=\"entity\" style=\"background: #aa9cfc; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Der Spiegel\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; text-transform: uppercase; vertical-align: middle; margin-left: 0.5rem\">PERSON</span>\n",
       "</mark>\n",
       " reports</div></span>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "example_headlines = [\n",
    "    \"Disney cuts ad spending on Facebook amid growing boycott: WSJ\",\n",
    "    \"TikTok considers London and other locations for headquarters\",\n",
    "    \"KPMG hit by Hong Kong High Court in $400 million China Medical fraud\",\n",
    "    \"Abu Dhabi's Etihad Airways restructures Airbus, Boeing jet orders\",\n",
    "    \"Trail of missing Wirecard executive leads to Belarus, Der Spiegel reports\"\n",
    "]\n",
    "\n",
    "for example in example_headlines:\n",
    "    spacy.displacy.render(\n",
    "        nlp(example),\n",
    "        style=\"ent\", jupyter=True\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Clearly, this is not perfect. TikTok, Disney and WSJ were not identified as organisations. Der Spiegel is a German news organisation, not a person. Without a labeled test set, we cannot verify the robustness of the entity extraction on our particular data set. Metrics for the spaCy models are reported on the corresponding [model page](https://spacy.io/models/en). For `en_core_web_sm`, F-score, precision and recall all hang around 85%. It is an unavoidable reality of statistical models of text that they are imperfect.\n",
    "\n",
    "Some of the failures we observed above do not occur if we use the larger `en_core_web_lg` language model. TikTok, Disney and WSJ are correctly identified as organisations. However, no model is perfect, and even the large model misidentifies Der Spiegel as a person.\n",
    "\n",
    "> If you'd like to try out the larger model yourself, you can! You'll need to replace the model name in the cell where it is loaded above, and also download it and import it, like we do with en_core_web_sm in the first code cells of this notebook. Be warned, the large model is 746MB.\n",
    "\n",
    "So then **why should we use a statistical model?** Why aren't we just extracting entities with regular expressions? Pattern matching will work for entities known ahead of time. For instance, if we only wanted to detect occurrences of \"Facebook\" or \"Twitter\", we could write rules to detect them. This approach is simple, and will match exactly the strings specified in the rules, regardless of context, which may be appropriate for some use cases.\n",
    "\n",
    "In contrast, statistical NER techniques do not discriminate on the particular name of an entity, but rather on its usage. Consider the entity \"White House\" (identified as an organisation by spaCy). Pattern matching will not distinguish between the White House of [whitehouse.gov](https://www.whitehouse.gov/) and the White House in the phrase \"How Many People Can Walter White House in His RV?\" One could attempt to implement some heuristic rules to isolate the desired pattern. In practice, this is not always possible, and is extremely manual and error-prone; all the more so when many entities are sought.\n",
    "\n",
    "In cases where seek to extract *entities* rather than words, especially when there is a likely naming conflict with words in common usage, we are often better served by a statistical approach."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Most mentioned organisations\n",
    "\n",
    "Having extracted entites from the Reuters headlines, we can now query them however we please. For instance, we could ask which organisations have been reported about most (by Reuters) in 2020:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "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>Entity</th>\n",
       "      <th>2020 Count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Fed</td>\n",
       "      <td>252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Boeing</td>\n",
       "      <td>210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>EU</td>\n",
       "      <td>190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Amazon</td>\n",
       "      <td>144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Huawei</td>\n",
       "      <td>125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Apple</td>\n",
       "      <td>111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Airbus</td>\n",
       "      <td>109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Facebook</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>MAX</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Lufthansa</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Entity  2020 Count\n",
       "0        Fed         252\n",
       "1     Boeing         210\n",
       "2         EU         190\n",
       "3     Amazon         144\n",
       "4     Huawei         125\n",
       "5      Apple         111\n",
       "6     Airbus         109\n",
       "7   Facebook          94\n",
       "8        MAX          93\n",
       "9  Lufthansa          93"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(\n",
    "    entity_df[\n",
    "        (entity_df.Label == \"ORG\") &                # filter to organisation entities only\n",
    "        (entity_df.Date.dt.year == 2020)            # filter to 2020 only\n",
    "    ]\n",
    "    .drop_duplicates()                              # count each headline once, even if org mentioned multiple times\n",
    "    .groupby('Entity')\n",
    "    .agg({'Headline': len})                         # count number of headlines in which each org appears\n",
    "    .sort_values(by='Headline', ascending=False)    # order from most to least appearances\n",
    "    .reset_index()\n",
    "    .rename(columns={'Headline': '2020 Count'})\n",
    "    .head(10)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The organisation appearing in the most headlines in 2020 is the \"Fed\"&mdash;the U.S. Federal Reserve Board. This is believable. Let's see some of those headlines:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Fed banks unanimously voted to keep discount rate unchanged - minutes',\n",
       "       \"Fed's money market move lifts Northern Trust fund above key threshold\",\n",
       "       'Fed officials signal rising caution on U.S. economic recovery amid virus spread',\n",
       "       'U.S. economy faces hard slog back from pandemic, Fed chief says',\n",
       "       'U.S. economy expands modestly but trade tensions weigh, Fed survey shows',\n",
       "       'Fed\\'s Bullard: \"Material reassessment\" is \"big tent language\"',\n",
       "       \"Fed's Harker says increase in coronavirus cases has direct economic impact\",\n",
       "       \"Fed's Powell beats drum for more government aid to bolster economy\",\n",
       "       'Fed studying if new facility for small business loans might be opened to non-bank lenders',\n",
       "       'Fund managers change tack as Fed reacts to virus'], dtype=object)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "entity_df[(entity_df.Date.dt.year == 2020) & (entity_df.Entity == \"Fed\")].sample(10).Headline.values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Timeline of mentions for a named entity\n",
    "\n",
    "Perhaps we are interested in tracking the appearance of an organisation in the news over time. We can view that with a simple line chart of mentions per day."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def occurence_plot(entity_name):\n",
    "    ax = (\n",
    "        entity_df[\n",
    "            (entity_df.Label == \"ORG\") &         # select only entities of type organisation\n",
    "            (entity_df.Entity == entity_name)    # select only a specific named entity\n",
    "         ]\n",
    "        .drop_duplicates()                       # count each headline once\n",
    "        .groupby('Date')\n",
    "        .agg(len)                                # count headlines containing the org on each date\n",
    "        .plot(\n",
    "            y='Entity',\n",
    "            drawstyle='steps',\n",
    "            legend=False,\n",
    "            figsize=(8,2)\n",
    "        )\n",
    "    )\n",
    "    ax.set_ylabel('Daily count')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For instance, we could look at mentions of aerospace company Boeing:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x144 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "occurence_plot('Boeing')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There's a prominent spike in articles around March-April 2019. This corresponds to the [Boeing 737 MAX groundings](https://en.wikipedia.org/wiki/Boeing_737_MAX_groundings) following two unfortunate crashes. This also explains the presence of the \"MAX\" entity (misidentified as an organisation) in the top 10 mentioned organisations in 2020 (as testing continues)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Organisation co-occurrence matrix\n",
    "\n",
    "We may be interested in investigating which organisations are frequently mentioned together. Let's do so for 2020. We can transform our list of headlines and associated entities into a co-occurrence matrix."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create a filtered dataframe for convenience\n",
    "orgs_2020_df = (\n",
    "    entity_df[\n",
    "        (entity_df.Label == \"ORG\") &        # filter to organisation entities only\n",
    "        (entity_df.Date.dt.year == 2020)    # filter to 2020 only\n",
    "    ]\n",
    "    [['Headline', 'Entity']]\n",
    "    .drop_duplicates()                      # count each headline once, even if org mentioned multiple times\n",
    ")\n",
    "\n",
    "ct = pd.crosstab(orgs_2020_df.Headline, orgs_2020_df.Entity)\n",
    "co_occurrence = ct.T.dot(ct)\n",
    "np.fill_diagonal(co_occurrence.values, 0)   # remove self-co-occurrence !!! warning: in-place operation !!!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The result is a giant DataFrame where each organisational entity appears as both a row and column, with the value of each cell representing the count of times two organisations have co-occurred in a Reuters headline in 2020. We have removed the diagonal of the matrix, since all organisations co-occur with themselves every time they're mentioned.\n",
    "\n",
    "For a given org, we can look up the other orgs it most frequently co-occurred with:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Entity\n",
       "Delta     2\n",
       "Boeing    2\n",
       "CNBC      1\n",
       "MAX       1\n",
       "United    1\n",
       "Name: American Airlines, dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "co_occurrence.loc['American Airlines'].sort_values(ascending=False).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Alternatively, we could check how often two orgs were mentioned together:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "co_occurrence.loc['HSBC'].loc['Huawei']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we might be interested in seeing the full co-occurence matrix visualized. Some organisations never co-occurred with any other org in a Reuters headline in 2020, so we'll drop those rows and columns of zero."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "no_zeros = co_occurrence.loc[(co_occurrence !=0 ).any(axis='rows'), (co_occurrence != 0).any(axis='columns')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_, ax = plt.subplots(figsize=(10,10))\n",
    "sns.heatmap(no_zeros > 0, cmap='Blues', ax=ax)\n",
    "ax.set_title(\"Co-occurrences of organisations in Reuters news headlines\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can't really indentify individual co-occurences in that chart, but we do learn that they are sparse. As expected, most organisations co-occur with only a handful of others."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## To spaCy and beyond\n",
    "\n",
    "Hopefully, this notebook has inspired your own use cases for named entity recognition. NER is but one mature NLP capability, for which spaCy provides industrial strength tooling. Even without training our own model, we were able to prototype a couple of capabilities that might be the basis of tools for use by journalists, businesses, or national statistics organisations seeking to monitor company activity.\n",
    "\n",
    "If we had been working with a more esoteric dataset, or wanted better entity recognition on our particular dataset, or desired different categories of entity, we could fine tune a model for the purpose. Doing so would require that we have data labeled with examples of the entities we want to extract. We could label that manually, employ a commercial labeling service, or use a purpose built tool like [prodi.gy](https://prodi.gy/) (from the makers of spaCy)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***If this documentation includes code, including but not limited to, code examples, Cloudera makes this available to you under the terms of the Apache License, Version 2.0, including any required notices.  A copy of the Apache License Version 2.0 can be found [here](https://opensource.org/licenses/Apache-2.0).***"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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 },
 "nbformat": 4,
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}