diff --git a/score/ipython/census_etl.ipynb b/score/ipython/census_etl.ipynb
new file mode 100644
index 00000000..1e43b94b
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+++ b/score/ipython/census_etl.ipynb
@@ -0,0 +1,166 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0491828b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import censusdata\n",
+    "import csv\n",
+    "from pathlib import Path\n",
+    "\n",
+    "ACS_YEAR = 2019\n",
+    "\n",
+    "DATA_PATH = Path.cwd().parent / \"data\"\n",
+    "FIPS_CSV_PATH = DATA_PATH / \"fips_states_2010.csv\"\n",
+    "\n",
+    "GEOID_FIELD_NAME = \"GEOID10\"\n",
+    "UNEMPLOYED_FIELD_NAME = \"Unemployed Civilians (fraction)\"\n",
+    "\n",
+    "# Some display settings to make pandas outputs more readable.\n",
+    "pd.set_option(\"display.expand_frame_repr\", False)\n",
+    "pd.set_option(\"display.precision\", 2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "654f25a1",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "# Following the tutorial at https://jtleider.github.io/censusdata/example1.html.\n",
+    "# Full list of fields is at https://www2.census.gov/programs-surveys/acs/summary_file/2019/documentation/user_tools/ACS2019_Table_Shells.xlsx\n",
+    "censusdata.printtable(censusdata.censustable(src=\"acs5\", year=ACS_YEAR, table=\"B23025\"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8999cea4",
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [],
+   "source": [
+    "def fips_from_censusdata_censusgeo(censusgeo: censusdata.censusgeo) -> str:\n",
+    "    \"\"\"Create a FIPS code from the proprietary censusgeo index.\"\"\"\n",
+    "    fips = \"\".join([value for (key, value) in censusgeo.params()])\n",
+    "    return fips\n",
+    "\n",
+    "\n",
+    "dfs = []\n",
+    "with open(FIPS_CSV_PATH) as csv_file:\n",
+    "    csv_reader = csv.reader(csv_file, delimiter=\",\")\n",
+    "    line_count = 0\n",
+    "\n",
+    "    for row in csv_reader:\n",
+    "        if line_count == 0:\n",
+    "            line_count += 1\n",
+    "        else:\n",
+    "            fips = row[0].strip()\n",
+    "            print(f\"Downloading data for state with FIPS code {fips}\")\n",
+    "\n",
+    "            dfs.append(\n",
+    "                censusdata.download(\n",
+    "                    src=\"acs5\",\n",
+    "                    year=ACS_YEAR,\n",
+    "                    geo=censusdata.censusgeo(\n",
+    "                        [(\"state\", fips), (\"county\", \"*\"), (\"block group\", \"*\")]\n",
+    "                    ),\n",
+    "                    var=[\"B23025_005E\", \"B23025_003E\"],\n",
+    "                )\n",
+    "            )\n",
+    "\n",
+    "df = pd.concat(dfs)\n",
+    "\n",
+    "df[GEOID_FIELD_NAME] = df.index.to_series().apply(func=fips_from_censusdata_censusgeo)\n",
+    "\n",
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "803cce31",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "# Calculate percent unemployment.\n",
+    "# TODO: remove small-sample data that should be `None` instead of a high-variance fraction.\n",
+    "df[UNEMPLOYED_FIELD_NAME] = df.B23025_005E / df.B23025_003E\n",
+    "\n",
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2a269bb1",
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [],
+   "source": [
+    "# mkdir census\n",
+    "columns_to_include = [GEOID_FIELD_NAME, UNEMPLOYED_FIELD_NAME]\n",
+    "\n",
+    "df[columns_to_include].to_csv(\n",
+    "    path_or_buf=DATA_PATH / \"tmp\" / \"census\" / \"census.csv\", index=False\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "05b93deb",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "43784bc1",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1abc16a5",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "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": "3.7.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}