added a file computing statistics about the measurements

experimental/measurement_stats.ipynb

@@ -0,0 +1,128 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e8c267a9-b96c-441a-8cfc-3976060ff078",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from datas import metadata\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f31f2eaa-08f9-42d3-a87c-5b09c007e7eb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "info = metadata.speakers_info;"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9b1a2b56-1731-45f1-b6d3-68d9def21cc0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import plotly.express as px"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bc56e6c2-79d1-4ffa-b626-1f9e850fffd6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "brands = []\n",
+    "reviewers = []\n",
+    "for speaker, data in info.items():\n",
+    "    brands.append(data['brand'])\n",
+    "    measurements = data['measurements']\n",
+    "    for k, m in measurements.items():\n",
+    "        origin = m['origin'].replace('Vendors-', '')\n",
+    "        if origin == 'Misc':\n",
+    "            origin = k.replace('misc-', '').capitalize()\n",
+    "        reviewers.append(origin)\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fa51df24-f9be-439b-98c4-0ea6dd3c3d69",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df_brands = pd.DataFrame({'brands': brands}).groupby('brands').size().sort_values(ascending=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d0101e67-1880-4c4f-be6c-90fec24af52d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df_reviewers = pd.DataFrame({'reviewer': reviewers}).groupby('reviewer').size().sort_values(ascending=False)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d30ade40-9547-41cb-9c7c-e5eae298615e",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "px.bar(df_brands[:30])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "75dc8cf5-ccdd-4e49-ae56-699ba4981b9c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "px.bar(\n",
+    "    df_reviewers[:30]\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f0e86ca9-1cae-4264-91c3-aa2847325d36",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}