Generate realistic sample data

src/App.tsx

@@ -8,7 +8,7 @@ import Legend from "./components/Legend";
 import QRCode from "./components/QRCode";
 import { WaffleChart } from "./components/WaffleChart";
 
-import { fetchGoogleSheet } from "./lib/parser";
+import { getSampleData } from "./lib/data";
 import "./styles/App.scss";
 
 function App() {
@@ -18,9 +18,9 @@ function App() {
   });
   const responseQuery = useQuery({
     queryKey: ["responses"],
-    queryFn: fetchGoogleSheet,
+    // queryFn: fetchGoogleSheet,
-    // queryFn: getSampleData,
+    queryFn: getSampleData,
-    refetchInterval: 5 * 1000, // Refresh every 5 seconds
+    refetchInterval: 1 * 1000, // Refresh every 5 seconds
   });
 
   if (metadataQuery.isPending || responseQuery.isPending)
@@ -29,19 +29,16 @@ function App() {
     return <div>Error loading data</div>;
 
   // Sort responses by timestamp to easily find the latest response
-  const responses = responseQuery.data.sort(
+  const responses = [...responseQuery.data].sort(
     (a, b) => a.timestamp - b.timestamp
   );
   const categoryMetadata = metadataQuery.data;
 
-  if (!responses.length) return null;
-
   // Group data by question (outside the component)
   const questionGroups = Array.from(
     d3.group(responses, (d) => d.question).entries()
   );
 
-  // Create scales
   return (
     <div className="layout">
       <div className="chart-container">

src/lib/data.ts

@@ -1,29 +1,27 @@
+import { fetchCategoryMetadata } from "./metadata";
 import { ResponseData } from "./parser";
 
-export function getSampleData(): Promise<ResponseData[]> {
+function randInt(min: number, max: number): number {
-  const questions = [
+  return Math.floor(Math.random() * (max - min + 1)) + min;
-    "Service Quality",
+}
-    "Value for Money",
+
-    "Ease of Use",
+export async function getSampleData(): Promise<ResponseData[]> {
-    "Recommendation",
+  // Use the actual categories
-    "Overall Satisfaction",
+  const questions = (await fetchCategoryMetadata()).map(
-    "Customer Support",
+    (metadata) => metadata.category
-    "Product Features",
+  );
-  ];
   const sampleData: ResponseData[] = [];
-  let id = 1;
+  const numResponses = randInt(10, 20);
-  questions.forEach((question) => {
+  for (let i = 0; i < numResponses; i++) {
-    const numResponses = Math.floor(Math.random() * 50) + 30;
+    questions.forEach((question) => {
-    for (let i = 0; i < numResponses; i++) {
+      const response = randInt(0, 4); // Likert scale response (0-4)
-      const response = Math.floor(Math.random() * 5);
       sampleData.push({
-        timestamp: id++,
+        timestamp: i, // Group all responses by the same timestamp to mimic Google Forms behavior
-        position: "",
         question: question,
         response: response,
       });
-    }
+    });
-  });
+  }
   // Simulate a delay to mimic fetching actual data
   return new Promise<ResponseData[]>((resolve) => {
     setTimeout(() => resolve(sampleData), 500);

src/lib/parser.ts

@@ -22,7 +22,6 @@ const url = `https://docs.google.com/spreadsheets/d/${sheet_id}/gviz/tq?tqx=out:
 
 export interface ResponseData {
   timestamp: number;
-  position: string;
   question: string;
   response: number;
 }
@@ -40,7 +39,6 @@ export function parseCSV(csv: string): ResponseData[] {
     });
     return Object.entries(responses).flatMap(([category, response]) => ({
       timestamp: new Date(row["Timestamp"]).getTime(),
-      position: row["Position"],
       question: category,
       response: response,
     }));