From e7201b0c193d08447da5fe4649c84875513d62dc Mon Sep 17 00:00:00 2001
From: Struan Donald <struan@exo.org.uk>
Date: Thu, 19 Sep 2024 16:31:59 +0200
Subject: [PATCH] import command for bbowt member counts

Imports Berkshire, Buckinghamshire and Oxfordshire Wildlife Trust member
counts.
---
 .../commands/import_berks_wt_member_count.py  | 52 +++++++++++++++++++
 1 file changed, 52 insertions(+)
 create mode 100644 hub/management/commands/import_berks_wt_member_count.py

diff --git a/hub/management/commands/import_berks_wt_member_count.py b/hub/management/commands/import_berks_wt_member_count.py
new file mode 100644
index 000000000..21585cf58
--- /dev/null
+++ b/hub/management/commands/import_berks_wt_member_count.py
@@ -0,0 +1,52 @@
+from django.conf import settings
+
+import pandas as pd
+
+from hub.models import DataSet
+
+from .base_importers import BaseImportFromDataFrameCommand
+
+
+class Command(BaseImportFromDataFrameCommand):
+    help = "Import Berkshire, Buckinghamshire and Oxfordshire Wildlife Trust member counts for post 2024 constituencies"
+
+    message = "importing Berkshire, Buckinghamshire and Oxfordshire wildlife trust member counts"
+    cons_row = "Constituency"
+    cons_col = "Constituency"
+    data_file = (
+        settings.BASE_DIR
+        / "data"
+        / "berks_bucks_oxon_wildlife_trust_member_counts.xlsx"
+    )
+    uses_gss = False
+
+    area_type = "WMC23"
+
+    data_sets = {
+        "bbox_wt_members": {
+            "defaults": {
+                "label": "Berkshire, Buckinghamshire and Oxfordshire Wildlife Trust members",
+                "data_type": "integer",
+                "category": "movement",
+                "subcategory": "places_and_spaces",
+                "release_date": "August 2024",
+                "source_label": "Data from Berkshire, Buckinghamshire and Oxfordshire Wildlife Trust.",
+                "source": "",
+                "source_type": "xlsx",
+                "data_url": "",
+                "table": "areadata",
+                "default_value": 10,
+                "exclude_countries": ["Scotland", "Northern Ireland"],
+                "comparators": DataSet.numerical_comparators(),
+                "unit_type": "raw",
+                "unit_distribution": "people_in_area",
+                "fill_blanks": False,
+            },
+            "col": "Total_Members",
+        }
+    }
+
+    def get_dataframe(self):
+        df = pd.read_excel(self.data_file)
+        df = df.astype({self.get_cons_col(): "str"})
+        return df