compute sar in time evolution

author: Adam Janovsky 2022-09-13 16:44:51 +0200
committer: Adam Janovsky 2022-09-13 16:44:51 +0200
commit: b91c4d18ea86552eab22421debd02baaaa79869b (patch)
tree: a4f5af64c51b1ab4599a0c3857d1ed38d570c5ba
parent: e663600dc1da9f0fc35534b072603bb23b0bfe14 (diff)
download: sec-certs-b91c4d18ea86552eab22421debd02baaaa79869b.tar.gz
sec-certs-b91c4d18ea86552eab22421debd02baaaa79869b.tar.zst
sec-certs-b91c4d18ea86552eab22421debd02baaaa79869b.zip
1 files changed, 63 insertions, 2 deletions
diff --git a/notebooks/cc/temporal_trends.ipynb b/notebooks/cc/temporal_trends.ipynb
index d2f0257c..5914cd88 100644
--- a/notebooks/cc/temporal_trends.ipynb
+++ b/notebooks/cc/temporal_trends.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 56,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -16,10 +16,13 @@
     "import numpy as np\n",
     "import tqdm\n",
     "import matplotlib.ticker as mtick\n",
+    "import warnings\n",
     "\n",
     "plt.style.use(\"seaborn-whitegrid\")\n",
     "sns.set_palette(\"deep\")\n",
-    "sns.set_context(\"notebook\") # Set to \"paper\" for use in paper :)"
+    "sns.set_context(\"notebook\") # Set to \"paper\" for use in paper :)\n",
+    "\n",
+    "warnings.simplefilter(action='ignore', category=pd.errors.PerformanceWarning)"
    ]
   },
   {
@@ -239,6 +242,64 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+    "## Average SAR levels\n",
+    "\n",
+    "Somewhat fragile code, sensible results only for the most popular SARs. Computes their average values over time"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 140/140 [00:07<00:00, 18.45it/s]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 720x288 with 10 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from sec_certs.utils.pandas import discover_sar_families, get_sar_level_from_set\n",
+    "\n",
+    "df_sar = df.loc[:, [\"eal\", \"extracted_sars\"]]\n",
+    "families = discover_sar_families(df_sar.extracted_sars)\n",
+    "df_sar.eal = df_sar.eal.cat.codes\n",
+    "\n",
+    "supports = [df_sar.loc[~df_sar[\"eal\"].isnull()].shape[0]]\n",
+    "\n",
+    "for family in tqdm.tqdm(families):\n",
+    "    df_sar[family] = df_sar.extracted_sars.map(lambda x: get_sar_level_from_set(x, family))\n",
+    "\n",
+    "most_popular_sars = list(df_sar.isna().sum().sort_values().head(12).index)[2:]\n",
+    "df_sar = df_sar.loc[:, most_popular_sars].join(df.year_from.to_frame())\n",
+    "melted_sars = df_sar.groupby(\"year_from\").mean().reset_index().melt(id_vars=\"year_from\", var_name=\"SAR\", value_name=\"avg_val\")\n",
+    "\n",
+    "g = sns.FacetGrid(melted_sars, col=\"SAR\", hue=\"SAR\", col_wrap=5, height=2)\n",
+    "g.map(sns.lineplot, \"year_from\", \"avg_val\")\n",
+    "g.set(xlabel=\"Year of cert.\", ylabel=\"Avg. value\")\n",
+    "g.set_titles(\"{col_name}\")\n",
+    "g.fig.subplots_adjust(top=0.87)\n",
+    "g.fig.suptitle('Category prevalence in time')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
     "## Average certificate lifetime\n",
     "\n",
     "Examine average certificate lifetime. Note that approx. 1k certificates expired on a single day, at 2019-09-01.\n",
author	Adam Janovsky	2022-09-13 16:44:51 +0200
committer	Adam Janovsky	2022-09-13 16:44:51 +0200
commit	b91c4d18ea86552eab22421debd02baaaa79869b (patch)
tree	a4f5af64c51b1ab4599a0c3857d1ed38d570c5ba
parent	e663600dc1da9f0fc35534b072603bb23b0bfe14 (diff)
download	sec-certs-b91c4d18ea86552eab22421debd02baaaa79869b.tar.gz sec-certs-b91c4d18ea86552eab22421debd02baaaa79869b.tar.zst sec-certs-b91c4d18ea86552eab22421debd02baaaa79869b.zip