feat: add loading page for when dataset is loading

Originally there was a simple "Loading" text, however this looked bad and might lead a user to think that the page had frozen.

There is now a more comprehensive loading animation which users might be happy to sit on for a few minutes.

frontend/src/components/AppLayout.tsx

@@ -82,7 +82,7 @@ const AppLayout = () => {
         <div style={{ ...styles.card, ...styles.headerBar }}>
           <div style={styles.appHeaderBrandRow}>
             <span style={styles.appTitle}>
-              Ethnograph View
+              CrossPost Analysis Engine
             </span>
             <span
               style={{

frontend/src/index.css

@@ -42,3 +42,24 @@ textarea:focus {
   box-shadow: 0 0 0 3px var(--focus-ring);
   outline: none;
 }
+
+@keyframes stats-spin {
+  from {
+    transform: rotate(0deg);
+  }
+
+  to {
+    transform: rotate(360deg);
+  }
+}
+
+@keyframes stats-pulse {
+  0%,
+  100% {
+    opacity: 0.5;
+  }
+
+  50% {
+    opacity: 1;
+  }
+}

frontend/src/pages/Stats.tsx

@@ -136,7 +136,27 @@ const StatPage = () => {
     getStats();
   }, [datasetId])
 
-  if (loading) return <p style={{...styles.page, minWidth: "100vh", minHeight: "100vh"}}>Loading insights…</p>;
+  if (loading) {
+    return (
+      <div style={styles.loadingPage}>
+        <div style={styles.loadingCard}>
+          <div style={styles.loadingHeader}>
+            <div style={styles.loadingSpinner} />
+            <div>
+              <h2 style={styles.loadingTitle}>Loading analytics</h2>
+              <p style={styles.loadingSubtitle}>Fetching summary, timeline, user, and content insights.</p>
+            </div>
+          </div>
+
+          <div style={styles.loadingSkeleton}>
+            <div style={{ ...styles.loadingSkeletonLine, ...styles.loadingSkeletonLineLong }} />
+            <div style={{ ...styles.loadingSkeletonLine, ...styles.loadingSkeletonLineMed }} />
+            <div style={{ ...styles.loadingSkeletonLine, ...styles.loadingSkeletonLineShort }} />
+          </div>
+        </div>
+      </div>
+    );
+  }
   if (error) return <p style={{...styles.page}}>{error}</p>;
 
 return (

frontend/src/styles/stats/feedback.ts

@@ -2,6 +2,78 @@ import { palette } from "./palette";
 import type { StyleMap } from "./types";
 
 export const feedbackStyles: StyleMap = {
+  loadingPage: {
+    width: "100%",
+    minHeight: "100vh",
+    padding: 20,
+    display: "flex",
+    alignItems: "center",
+    justifyContent: "center",
+  },
+
+  loadingCard: {
+    width: "min(560px, 92vw)",
+    background: palette.surface,
+    border: `1px solid ${palette.borderDefault}`,
+    borderRadius: 8,
+    boxShadow: `0 1px 0 ${palette.shadowSubtle}`,
+    padding: 20,
+  },
+
+  loadingHeader: {
+    display: "flex",
+    alignItems: "center",
+    gap: 12,
+  },
+
+  loadingSpinner: {
+    width: 18,
+    height: 18,
+    borderRadius: "50%",
+    border: `2px solid ${palette.borderDefault}`,
+    borderTopColor: palette.brandGreen,
+    animation: "stats-spin 0.9s linear infinite",
+    flexShrink: 0,
+  },
+
+  loadingTitle: {
+    margin: 0,
+    fontSize: 16,
+    fontWeight: 600,
+    color: palette.textPrimary,
+  },
+
+  loadingSubtitle: {
+    margin: "6px 0 0",
+    fontSize: 13,
+    color: palette.textSecondary,
+  },
+
+  loadingSkeleton: {
+    marginTop: 16,
+    display: "grid",
+    gap: 8,
+  },
+
+  loadingSkeletonLine: {
+    height: 9,
+    borderRadius: 999,
+    background: palette.canvas,
+    animation: "stats-pulse 1.25s ease-in-out infinite",
+  },
+
+  loadingSkeletonLineLong: {
+    width: "100%",
+  },
+
+  loadingSkeletonLineMed: {
+    width: "78%",
+  },
+
+  loadingSkeletonLineShort: {
+    width: "62%",
+  },
+
   alertCardError: {
     borderColor: palette.alertErrorBorder,
     background: palette.alertErrorBg,

frontend/src/types/ApiTypes.ts

@@ -55,16 +55,24 @@ type TimeAnalysisResponse = {
 }
 
 // Content Analysis
+type Emotion = {
+  emotion_anger: number;
+  emotion_disgust: number;
+  emotion_fear: number;
+  emotion_joy: number;
+  emotion_sadness: number;
+};
+
 type NGram = {
     count: number;
     ngram: string;
 }
 
-type AverageEmotionByTopic = {
-    topic: string;
+type AverageEmotionByTopic = Emotion & {
   n: number;
-    [emotion: string]: string | number;
-}
+  topic: string;
+};
+
 
 type ContentAnalysisResponse = {
     word_frequencies: FrequencyWord[];

server/analysis/stat_gen.py

@@ -96,10 +96,7 @@ class StatGen:
             "common_three_phrases": self.linguistic_analysis.ngrams(filtered_df, n=3),
             "average_emotion_by_topic": self.emotional_analysis.avg_emotion_by_topic(
                 filtered_df
-            ),
-            "reply_time_by_emotion": self.temporal_analysis.avg_reply_time_per_emotion(
-                filtered_df
-            ),
+            )
         }
 
     def get_user_analysis(self, df: pd.DataFrame, filters: dict | None = None) -> dict: