diff --git a/hub/management/commands/import_council_data.py b/hub/management/commands/import_council_data.py
new file mode 100644
index 000000000..0d8f08b06
--- /dev/null
+++ b/hub/management/commands/import_council_data.py
@@ -0,0 +1,54 @@
+from django.conf import settings
+
+import pandas as pd
+from mysoc_dataset import get_dataset_url
+
+from hub.models import AreaData, DataSet
+
+from .base_importers import BaseImportFromDataFrameCommand
+
+
+class Command(BaseImportFromDataFrameCommand):
+    cons_row = "gss-code"
+    message = "Importing council population data"
+    uses_gss = True
+    do_not_convert = True
+
+    area_type = "STC"
+
+    defaults = {
+        "data_type": "integer",
+        "category": "place",
+        "subcategory": "",
+        "release_date": "February 2023",
+        "label": "Council population",
+        "source_label": "Data from mySociety.",
+        "source": "https://www.mysociety.org/",
+        "source_type": "csv",
+        "table": "areadata",
+        "default_value": 1000,
+        "data_url": "",
+        "comparators": DataSet.numerical_comparators(),
+        "unit_type": "raw",
+        "unit_distribution": "people_in_area",
+    }
+
+    data_sets = {
+        "council_population_count": {
+            "defaults": defaults,
+            "col": "pop-2020",
+        },
+    }
+
+    def get_dataframe(self):
+        url = get_dataset_url(
+            repo_name="uk_local_authority_names_and_codes",
+            package_name="uk_la_future",
+            version_name="1",
+            file_name="uk_local_authorities_future.csv",
+            done_survey=True,
+        )
+        df = pd.read_csv(url)
+
+        print(df.columns)
+        return df