12 natalie analysis

notebooks/2024_12_MS_cybersecurity/config.yaml

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+---
+search_recipe:
+  scope_statements:
+    - "Child online safety and privacy"
+    - "Protecting children in the digital age"
+    - "Protecing children from online threats"
+    - "Ensuring children's safety online"
+    - "Ensuring children's privacy online"
+    - "Helping parents protect their children online"
+    - "Helping parents inform their children about online safety"
+    - "Helping parents monitor their children's online activity"
+
+  keyword_sets:
+    - set_name: "Domain keywords"
+      keywords:
+        - "child"
+        - "children"
+        - "infant"
+        - "baby"
+        - "babies"
+        - "toddler"
+        - "toddlers"
+        - "pregnancy"
+        - "parent"
+        - "mother"
+        - "father"
+        - "family"
+        - "pupil"
+        - "teenager"
+        - "teen"
+
+    - set_name: "Tech keywords"
+      keywords:
+        - "cybersecurity"
+        - "online safety"
+        - "data protection"
+        - "encryption"
+        - "malware"
+        - "phishing"
+        - "firewall"
+        - "identity theft"
+        - "cyber threats"
+        - "cyberattack"
+        - "cyber attack"
+        - "data breach"
+        - "social engineering"
+        - "threat intelligence"
+        - "penetration testing"
+        - "cyber defence"
+        - "cyber defense"
+        - "cyber forensics"
+        - "ransomware"
+        - "zero day exploit"
+        - "cloud security"

notebooks/2024_12_MS_cybersecurity/natalie_cybersec_analysis.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Examples of using analysis functionalities\n",
+    "\n",
+    "Using discovery_utils analyses functionalities for investments data\n",
+    "\n",
+    "Here, we'll find companies using their categories, but you can also use search results from the process shown in cybersec_search.ipynb"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from discovery_utils.utils import (\n",
+    "    analysis_crunchbase,\n",
+    "    analysis,\n",
+    "    charts\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from discovery_utils.getters import crunchbase\n",
+    "CB = crunchbase.CrunchbaseGetter()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let's find categories to use for selecting companies"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Categories for cybersec\n",
+    "CB.find_similar_categories(\"cyber security\", category_type=\"broad\", n_results=10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Categories for family and kids\n",
+    "CB.find_similar_categories(\"family\", category_type=\"narrow\", n_results=15)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now get both types of companies and take the intersection to find those that match both categories\n",
+    "\n",
+    "This might take a minute for the first time, as it downloads the data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cybersec_df = CB.get_companies_in_categories([\"Privacy and Security\"], category_type=\"broad\")\n",
+    "family_df = CB.get_companies_in_categories([\"Family\", \"Parenting\", \"Children\", \"Teenagers\"], category_type=\"narrow\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "matching_ids = set(cybersec_df.id) & set(family_df.id)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "len(matching_ids)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can check these companies by querying the ids"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "matchings_orgs_df = CB.organisations_enriched.query(\"id in @matching_ids\")\n",
+    "matchings_orgs_df[['name', 'homepage_url', 'short_description']]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now get the funding rounds for the matching companies - you can specify what type of funding rounds you need"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Check what type of funding rounds there are\n",
+    "CB.unique_funding_round_types"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "funding_rounds_df = (\n",
+    "    CB.select_funding_rounds(org_ids=matching_ids, funding_round_types=[\"angel\", \"pre_seed\", \"seed\", \"series_a\"])\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now let's generate some basic time series"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ts_df = analysis_crunchbase.get_timeseries(matchings_orgs_df, funding_rounds_df, period='year', min_year=2014, max_year=2024)\n",
+    "ts_df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fig = charts.ts_bar(\n",
+    "    ts_df,\n",
+    "    variable='raised_amount_gbp_total',\n",
+    "    variable_title=\"Raised amount, £ millions\",\n",
+    "    category_column=\"_category\",\n",
+    ")\n",
+    "charts.configure_plots(fig, chart_title=\"\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let's look into breakdown of deal types"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "deals_df, deal_counts_df = analysis_crunchbase.get_funding_by_year_and_range(funding_rounds_df, 2014, 2024)\n",
+    "aggregated_funding_types_df = analysis_crunchbase.aggregate_by_funding_round_types(funding_rounds_df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "deals_df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "analysis_crunchbase.chart_investment_types(aggregated_funding_types_df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "analysis_crunchbase.chart_deal_sizes(deals_df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "analysis_crunchbase.chart_deal_sizes_counts(deal_counts_df)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "discovery-mission-radar-prototyping-ejbE0IFh-py3.11",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}