rough version of imported that uses CSV config for imports

This should enable add simple imports by adding rows to the CSV rather
than writing a new script

conf/imports.csv

@@ -0,0 +1,2 @@
+name,label,description,data_type,category,subcategory,release_date,source_label,source,source_type,data_url,table,default_value,exclude_countries,unit_type,unit_distribution,fill_blanks,is_public,is_filterable,is_shadeable,data_file,uses_gss,constituency_col,data_col,file_type,area_type
+import_test,"Berkshire, Buckinghamshire and Oxfordshire  Wildlife Trust members",,integer,movement,places_and_spaces,August 2024,"Data from Berkshire, Buckinghamshire and Oxfordshire Wildlife Trusts",,xlsl,,areadata,10,"Scotland, Northern Ireland",raw,people_in_area,FALSE,FALSE,FALSE,FALSE,berks_bucks_oxon_wildlife_trust_member_counts.xlsx,FALSE,Constituency,Total_Members,excel,WMC23

hub/management/commands/import_from_comfig.py

@@ -0,0 +1,86 @@
+from django.conf import settings
+
+import pandas as pd
+
+from .base_importers import BaseImportFromDataFrameCommand
+
+
+class Command(BaseImportFromDataFrameCommand):
+    help = "Import based on config"
+
+    config_file = settings.BASE_DIR / "conf" / "imports.csv"
+
+    defaults_cols = [
+        "label",
+        "data_type",
+        "category",
+        "subcategory",
+        "release_date",
+        "source_label",
+        "source",
+        "source_type",
+        "data_url",
+        "table",
+        "default_value",
+        "exclude_countries",
+        # "comparators",
+        "unit_type",
+        "unit_distribution",
+        "fill_blanks",
+    ]
+
+    def add_arguments(self, parser):
+        super().add_arguments(parser)
+
+        parser.add_argument(
+            "--import_name", action="store", required=True, help="Name of import to run"
+        )
+
+    def setup(self, import_name):
+        df = pd.read_csv(self.config_file)
+
+        df.loc[df["name"] == import_name]
+        row = df.iloc[0]
+
+        self.message = f"Importing {row['label']}"
+        self.cons_row = row["constituency_col"]
+        self.cons_col = row["constituency_col"]
+        self.data_file = settings.BASE_DIR / "data" / row["data_file"]
+        self.file_type = row["file_type"]
+        self.area_type = row["area_type"]
+
+        if row["uses_gss"] == "TRUE":
+            self.uses_gss = True
+        else:
+            self.uses_gss = False
+
+        defaults = {}
+
+        for col in self.defaults_cols:
+            defaults[col] = row[col]
+
+        self.data_sets = {import_name: {"defaults": defaults, "col": row["data_col"]}}
+
+    def get_dataframe(self):
+        if self.file_type == "csv":
+            df = pd.read_csv(self.data_file)
+        elif self.file_type == "excel":
+            df = pd.read_excel(self.data_file)
+        else:
+            self.stderr.write(f"Unknown file type: {self.file_type}")
+            return None
+
+        df = df.astype({self.get_cons_col(): "str"})
+        return df
+
+    def handle(
+        self,
+        quiet=False,
+        skip_new_areatype_conversion=False,
+        import_name=None,
+        *args,
+        **options,
+    ):
+        self.setup(import_name)
+
+        super().handle(quiet, skip_new_areatype_conversion, *args, **options)