diff --git a/_delphi_utils_python/delphi_utils/geomap.py b/_delphi_utils_python/delphi_utils/geomap.py
index 960068943..646743319 100644
--- a/_delphi_utils_python/delphi_utils/geomap.py
+++ b/_delphi_utils_python/delphi_utils/geomap.py
@@ -392,16 +392,17 @@ def replace_geocode(
         df = df.groupby([date_col, new_col]).sum().reset_index()
         return df
 
-    def add_population_column(self, data, geocode_type, geocode_col=None):
+    def add_population_column(self, geocode_type, data=None, geocode_col=None):
         """
-        Appends a population column to a dateframe, based on the FIPS or ZIP code.
+        Appends a population column to a dataframe, based on the FIPS or ZIP code. If no
+        dataframe is provided, the full crosswalk from geocode to population is returned.
 
         Parameters
         ---------
-        data: pd.DataFrame
-            The dataframe with a FIPS code column.
         geocode_type: {"fips", "zip"}
             The type of the geocode contained in geocode_col.
+        data: pd.DataFrame
+            The dataframe with a FIPS code column.
         geocode_col: str, default None
             The name of the column containing the geocodes. If None, uses the geocode_type
             as the name.
@@ -419,11 +420,14 @@ def add_population_column(self, data, geocode_type, geocode_col=None):
                 For other codes, aggregate those."
             )
 
+        pop_df = self._load_crosswalk(from_code=geocode_type, to_code="pop")
+
+        if data is None:
+            return pop_df.rename(columns={"pop": "population"})
+
         if not is_string_dtype(data[geocode_col]):
             data[geocode_col] = data[geocode_col].astype(str).str.zfill(5)
 
-        pop_df = self._load_crosswalk(from_code=geocode_type, to_code="pop")
-
         data_with_pop = (
             data.copy()
             .merge(pop_df, left_on=geocode_col, right_on=geocode_type, how="inner")
diff --git a/_delphi_utils_python/tests/test_geomap.py b/_delphi_utils_python/tests/test_geomap.py
index fca26b8ea..b756d1618 100644
--- a/_delphi_utils_python/tests/test_geomap.py
+++ b/_delphi_utils_python/tests/test_geomap.py
@@ -277,12 +277,14 @@ def test_zip_to_state_id(self):
 
     def test_add_population_column(self):
         gmpr = GeoMapper()
-        new_data = gmpr.add_population_column(self.fips_data_3, "fips")
+        new_data = gmpr.add_population_column("fips", self.fips_data_3)
         assert new_data["population"].sum() == 274963
-        new_data = gmpr.add_population_column(self.zip_data, "zip")
+        new_data = gmpr.add_population_column("zip", self.zip_data)
         assert new_data["population"].sum() == 274902
         with pytest.raises(ValueError):
-            new_data = gmpr.add_population_column(self.zip_data, "hrr")
+            new_data = gmpr.add_population_column("hrr", self.zip_data)
+        pop_df = gmpr.add_population_column("fips")
+        assert pop_df.shape == (3274, 2)
 
     def test_add_geocode(self):
         gmpr = GeoMapper()
diff --git a/jhu/delphi_jhu/pull.py b/jhu/delphi_jhu/pull.py
index ae72a780a..e567c1af9 100644
--- a/jhu/delphi_jhu/pull.py
+++ b/jhu/delphi_jhu/pull.py
@@ -69,12 +69,7 @@ def pull_jhu_data(base_url: str, metric: str, pop_df: pd.DataFrame) -> pd.DataFr
 
     gmpr = GeoMapper()
     df = gmpr.replace_geocode(df, "jhu_uid", "fips", from_col="UID", date_col="timestamp")
-
-    # Merge in population LOWERCASE, consistent across confirmed and deaths
-    # Set population as NAN for fake fips
-    pop_df.rename(columns={'FIPS':'fips'}, inplace=True)
-    pop_df['fips'] = pop_df['fips'].astype(int).\
-        astype(str).str.zfill(5)
+    # Merge in population, set population as NAN for fake fips
     df = pd.merge(df, pop_df, on="fips", how='left')
 
     # Add a dummy first row here on day before first day
diff --git a/jhu/delphi_jhu/run.py b/jhu/delphi_jhu/run.py
index d355fb090..8a2287792 100644
--- a/jhu/delphi_jhu/run.py
+++ b/jhu/delphi_jhu/run.py
@@ -17,6 +17,7 @@
     S3ArchiveDiffer,
 )
 
+from delphi_utils import GeoMapper
 from .geo import geo_map
 from .pull import pull_jhu_data
 from .smooth import (
@@ -84,10 +85,7 @@ def run_module():
     else:
         arch_diff = None
 
-    pop_df = pd.read_csv(
-        join(static_file_dir, "fips_population.csv"),
-        dtype={"fips": float, "population": float},
-    )
+    pop_df = GeoMapper().add_population_column("fips")
 
     dfs = {metric: pull_jhu_data(base_url, metric, pop_df) for metric in METRICS}
     for metric, geo_res, sensor, smoother in product(
diff --git a/jhu/static/fips_population.csv b/jhu/static/fips_population.csv
deleted file mode 100644
index 7421a53a2..000000000
--- a/jhu/static/fips_population.csv
+++ /dev/null
@@ -1,3197 +0,0 @@
-fips,population
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diff --git a/jhu/tests/test_pull.py b/jhu/tests/test_pull.py
index de0a7e7cf..e1052d6aa 100644
--- a/jhu/tests/test_pull.py
+++ b/jhu/tests/test_pull.py
@@ -4,12 +4,9 @@
 
 import pandas as pd
 from delphi_jhu.pull import pull_jhu_data, detect_date_col
+from delphi_utils import GeoMapper
 
-pop_df = pd.read_csv(
-    join("..", "static", "fips_population.csv"),
-    dtype={"fips": float, "population": float}
-).rename({"fips": "FIPS"}, axis=1)
-
+pop_df = GeoMapper().add_population_column("fips")
 
 class TestPullJHU:
     test_date_cols = ['2/29/20', '3/1/20', '3/2/20', '3/3/20', '3/4/20', '3/5/20', '3/6/20',
diff --git a/testing_utils/indicator_validation.ipynb b/testing_utils/indicator_validation.template.ipynb
similarity index 97%
rename from testing_utils/indicator_validation.ipynb
rename to testing_utils/indicator_validation.template.ipynb
index d616d10a8..3c4f0c0bc 100644
--- a/testing_utils/indicator_validation.ipynb
+++ b/testing_utils/indicator_validation.template.ipynb
@@ -14,8 +14,8 @@
   },
   "orig_nbformat": 2,
   "kernelspec": {
-   "name": "Python 3.8.5 64-bit ('delphi')",
-   "display_name": "Python 3.8.5 64-bit ('delphi')",
+   "name": "Python 3.8.5 64-bit ('delphi': venv)",
+   "display_name": "Python 3.8.5 64-bit ('delphi': venv)",
    "metadata": {
     "interpreter": {
      "hash": "caf87e55c8359f697bd94fe1aac5633662441bd3172cf56261450c8476d2e897"
@@ -39,7 +39,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 143,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -172,7 +172,7 @@
   },
   {
    "source": [
-    "## Qualitative Comparisons\n"
+    "## Qualitative Comparisons: Confirmed Incidence Num\n"
    ],
    "cell_type": "markdown",
    "metadata": {}
@@ -187,12 +187,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 191,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
     "os.chdir(join(ROOT_DIR, \"jhu\"))\n",
-    "geocode = \"fips\"\n",
+    "geocode = \"county\"\n",
     "signal_type = \"confirmed_incidence_num\"\n",
     "start_date = date(2020, 3, 1)\n",
     "end_date = date(2020, 10, 1)\n",
@@ -223,7 +223,7 @@
     "if not isfile(remote_data_filename):\n",
     "    remote_data = covidcast.signal(\"jhu-csse\", \"confirmed_incidence_num\",\n",
     "                            start_date, end_date,\n",
-    "                            \"county\")\n",
+    "                            geocode)\n",
     "    remote_data.to_csv(remote_data_filename)\n",
     "else:\n",
     "    remote_data = pd.read_csv(remote_data_filename)\n",
@@ -241,7 +241,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 192,
+   "execution_count": 5,
    "metadata": {
     "tags": []
    },
@@ -249,13 +249,15 @@
     {
      "output_type": "stream",
      "name": "stdout",
-     "text": "Total difference:  0.0\n"
+     "text": [
+      "Total difference:  0.0\n"
+     ]
     },
     {
      "output_type": "display_data",
      "data": {
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      },
      "metadata": {
@@ -274,6 +276,41 @@
     "print(\"Total difference: \", rd.sub(ld).sum())"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "output_type": "stream",
+     "name": "stdout",
+     "text": [
+      "Total difference:  0.0\n"
+     ]
+    },
+    {
+     "output_type": "display_data",
+     "data": {
+      "text/plain": "<Figure size 1152x432 with 1 Axes>",
+      "image/svg+xml": "<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n<!-- Created with matplotlib (https://matplotlib.org/) -->\n<svg height=\"357.238125pt\" version=\"1.1\" viewBox=\"0 0 939.65 357.238125\" width=\"939.65pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n <metadata>\n  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n   <cc:Work>\n    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n    <dc:date>2020-10-08T14:49:56.219346</dc:date>\n    <dc:format>image/svg+xml</dc:format>\n    <dc:creator>\n     <cc:Agent>\n      <dc:title>Matplotlib v3.3.2, https://matplotlib.org/</dc:title>\n     </cc:Agent>\n    </dc:creator>\n   </cc:Work>\n  </rdf:RDF>\n </metadata>\n <defs>\n  <style 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\n"
+     },
+     "metadata": {
+      "needs_background": "light"
+     }
+    }
+   ],
+   "source": [
+    "fips_code = \"36081\" # Queens County, New York FIPS\n",
+    "rd = remote_data[remote_data[\"geo_value\"] == fips_code].set_index(\"time_value\").sort_index()[\"value\"]\n",
+    "ld = local_data[local_data[\"geo_id\"] == fips_code].set_index(\"date\").sort_index()[\"val\"]\n",
+    "plt.figure(figsize=(16, 6))\n",
+    "plt.plot(rd, label=\"remote\")\n",
+    "plt.plot(ld, label=\"local\")\n",
+    "plt.legend()\n",
+    "print(\"Total difference: \", rd.sub(ld).sum())"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 193,