diff --git a/notebooks/process/wikidata-pop-data.ipynb b/notebooks/process/wikidata-pop-data.ipynb
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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Gather Population Data from Wikidata"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import pandas as pd\n",
+    "\n",
+    "from covid_19_dashboard import helper"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": [
+     "parameters"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "out_folder = '../../data/atlas/wikidata'\n",
+    "PAPERMILL_OUTPUT_PATH = None"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def write_population_data(iso_code, df):\n",
+    "    out_path = os.path.join(out_folder, f\"{iso_code.lower()}-population.csv\")\n",
+    "    print(f\"Writing {len(df)} rows to {out_path}\")\n",
+    "    if PAPERMILL_OUTPUT_PATH is None:\n",
+    "        return\n",
+    "    df.to_csv(out_path)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Italy"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "iso_code = \"ITA\"\n",
+    "pops = helper.get_region_populations(\n",
+    "    iso_code,\n",
+    "    additional_fields=\"?istatid\",\n",
+    "    additional_query=\"?region wdt:P635 ?istatid .\",\n",
+    ")\n",
+    "df = pd.DataFrame(pops)\n",
+    "write_population_data(iso_code, df)\n",
+    "df.head(2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Switzerland"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "iso_code = \"CHE\"\n",
+    "pops = helper.get_region_populations(iso_code)\n",
+    "df = pd.DataFrame(pops)\n",
+    "write_population_data(iso_code, df)\n",
+    "df.head(2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## United States"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "iso_code = \"USA\"\n",
+    "pops = helper.get_region_populations(iso_code)\n",
+    "df = pd.DataFrame(pops)\n",
+    "write_population_data(iso_code, df)\n",
+    "df.head(2)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": "3.7.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}