Including all schools in England

backend/app.py

@@ -15,12 +15,7 @@ from typing import Optional
 import os
 import re
 
-# Local Authority codes for Wandsworth and Merton
+# No longer filtering by specific LA codes - load all available schools
-LA_CODES = {
-    212: "Wandsworth",
-    315: "Merton"
-}
-ALLOWED_LA_CODES = list(LA_CODES.keys())
 
 app = FastAPI(
     title="SchoolCompare API",
@@ -128,21 +123,22 @@ def load_school_data() -> pd.DataFrame:
                         print(f"Loading data from {ks2_file}")
                         df = pd.read_csv(ks2_file, low_memory=False)
                         
-                        # Filter to Wandsworth (212) and Merton (315)
                         # Handle both string and integer columns
-                        if df['LEA'].dtype == 'object':
+                        if 'LEA' in df.columns and df['LEA'].dtype == 'object':
                             df['LEA'] = pd.to_numeric(df['LEA'], errors='coerce')
-                        if df['URN'].dtype == 'object':
+                        if 'URN' in df.columns and df['URN'].dtype == 'object':
                             df['URN'] = pd.to_numeric(df['URN'], errors='coerce')
-                        df = df[df['LEA'].isin(ALLOWED_LA_CODES)]
                         
                         # Filter to schools only (RECTYPE == 1 means school level data)
                         if 'RECTYPE' in df.columns:
                             df = df[df['RECTYPE'] == 1]
                         
-                        # Add year and local authority name
+                        # Add year and local authority name from LANAME column
                         df['year'] = year
-                        df['local_authority'] = df['LEA'].map(LA_CODES)
+                        if 'LANAME' in df.columns:
+                            df['local_authority'] = df['LANAME']
+                        elif 'LEA' in df.columns:
+                            df['local_authority'] = df['LEA'].astype(str)
                         
                         # Standardize column names for our API
                         df = df.rename(columns={
@@ -380,7 +376,7 @@ async def get_filter_options():
     
     if df.empty:
         return {
-            "local_authorities": ["Wandsworth", "Merton"],
+            "local_authorities": [],
             "school_types": [],
             "years": [],
         }

frontend/app.js

@@ -78,6 +78,14 @@ async function loadFilters() {
     const data = await fetchAPI('/api/filters');
     if (!data) return;
 
+    // Populate local authority filter
+    data.local_authorities.forEach(la => {
+        const option = document.createElement('option');
+        option.value = la;
+        option.textContent = la;
+        elements.localAuthorityFilter.appendChild(option);
+    });
+
     // Populate school type filter
     data.school_types.forEach(type => {
         const option = document.createElement('option');

frontend/index.html

@@ -41,7 +41,7 @@
         <section id="dashboard-view" class="view active">
             <div class="hero">
                 <h1 class="hero-title">Compare Primary School Performance</h1>
-                <p class="hero-subtitle">Explore and compare KS2 results across Wandsworth & Merton primary schools</p>
+                <p class="hero-subtitle">Explore and compare KS2 results across England's primary schools</p>
             </div>
 
             <div class="search-section">
@@ -57,8 +57,6 @@
                 <div class="filter-row">
                     <select id="local-authority-filter" class="filter-select">
                         <option value="">All Areas</option>
-                        <option value="Wandsworth">Wandsworth</option>
-                        <option value="Merton">Merton</option>
                     </select>
                     <select id="type-filter" class="filter-select">
                         <option value="">All School Types</option>
@@ -252,7 +250,7 @@
 
     <footer class="footer">
         <p>Data source: <a href="https://www.compare-school-performance.service.gov.uk/download-data" target="_blank">UK Government - Compare School Performance</a></p>
-        <p class="footer-note">Primary school (KS2) data for Wandsworth and Merton. Data from 2019-2020, 2020-2021, 2021-2022 unavailable due to COVID-19 disruption.</p>
+        <p class="footer-note">Primary school (KS2) data for England. Data from 2019-2020, 2020-2021, 2021-2022 unavailable due to COVID-19 disruption.</p>
     </footer>
 
     <script src="/static/app.js"></script>