diff --git a/hub/management/commands/import_council_imd_data.py b/hub/management/commands/import_council_imd_data.py
new file mode 100644
index 000000000..b2dcc4170
--- /dev/null
+++ b/hub/management/commands/import_council_imd_data.py
@@ -0,0 +1,68 @@
+import pandas as pd
+from mysoc_dataset import get_dataset_url
+
+from hub.import_utils import add_gss_codes, filter_authority_type
+from hub.models import DataSet
+
+from .base_importers import BaseImportFromDataFrameCommand, MultipleAreaTypesMixin
+
+
+class Command(MultipleAreaTypesMixin, BaseImportFromDataFrameCommand):
+    help = "Import Council IMD data"
+
+    message = "Importing council IMD data"
+    cons_row = "gss_code"
+    area_types = ["STC", "DIS"]
+    uses_gss = True
+    do_not_convert = True
+
+    data_sets = {
+        "council_imd": {
+            "defaults": {
+                "source": "https://mysociety.github.io/composite_uk_imd/",
+                "source_label": "Data from ONS (England and Wales), NRS (Scotland), and NISRA (Northern Ireland), collated and standardised by mySociety.",
+                "name": "council_imd",
+                "description": "Deciles of deprivation, from 1 (most deprived) to 10 (least deprived). This uses a composite measure of deprivation (including income, employment, education, skills, health, crime, and housing) standardised across the countries of the UK.",
+                "label": "Index of Multiple Deprivation (IMD)",
+                "data_type": "integer",
+                "category": "place",
+                "source_type": "csv",
+                "table": "areadata",
+                "comparators": DataSet.numerical_comparators()[::-1],
+                "default_value": 5,
+                "unit_type": "percentage",
+                "unit_distribution": "people_in_area",
+                "is_public": True,
+            },
+            "col": "la-imd-pop-quintile",
+        }
+    }
+    package = {
+        "repo_name": "composite_uk_imd",
+        "package_name": "uk_index",
+        "version_name": "3.3.0",
+        "file_name": "la_imd.csv",
+    }
+
+    def __init__(self):
+        super().__init__()
+
+        url = get_dataset_url(
+            repo_name=self.package["repo_name"],
+            package_name=self.package["package_name"],
+            version_name=self.package["version_name"],
+            file_name=self.package["file_name"],
+            done_survey=True,
+        )
+
+        self.data_sets["council_imd"]["defaults"]["data_url"] = url
+
+    def get_dataframe(self):
+        df = pd.read_csv(self.data_sets["council_imd"]["defaults"]["data_url"])
+
+        df = add_gss_codes(df, "local-authority-code")
+        df = filter_authority_type(df, self.area_type, self.cons_row)
+        return df
+
+    def update_averages(self):
+        pass