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example.py

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+from datasets import load_dataset
+
+
+def display_dataset_statistics(dataset):
+    """
+    Display overall statistics about the dataset.
+
+    Args:
+        dataset: A HuggingFace Dataset object.
+    """
+    print("\n" + "=" * 50)
+    print(f"{'DATASET STATISTICS':^50}")
+    print("=" * 50)
+
+    print(f"\n📊 Number of entries: {len(dataset):,}")
+
+    # Convert to pandas for easier analysis
+    df = dataset.to_pandas()
+
+    # Count presentation types
+    if "status" in df.columns:
+        print("\n" + "-" * 30)
+        print("📝 PRESENTATION TYPES")
+        print("-" * 30)
+        status_counts = df["status"].value_counts()
+        for status, count in status_counts.items():
+            print(f"  • {status}: {count:,} ({count / len(df) * 100:.1f}%)")
+
+    # Count venues
+    if "venue" in df.columns:
+        print("\n" + "-" * 30)
+        print("🏢 VENUES")
+        print("-" * 30)
+        venue_counts = df["venue"].value_counts()
+        for venue, count in venue_counts.items():
+            print(f"  • {venue}: {count:,} ({count / len(df) * 100:.1f}%)")
+
+    # Count primary research areas
+    if "primary_area" in df.columns:
+        print("\n" + "-" * 30)
+        print("🔬 TOP 10 PRIMARY RESEARCH AREAS")
+        print("-" * 30)
+        area_counts = df["primary_area"].value_counts().head(10)
+        for area, count in area_counts.items():
+            print(f"  • {area}: {count:,} ({count / len(df) * 100:.1f}%)")
+
+
+def display_sample_entries(dataset, n=3):
+    """
+    Display sample entries from the dataset.
+
+    Args:
+        dataset: A HuggingFace Dataset object.
+        n: Number of samples to display.
+    """
+    print("\n" + "=" * 50)
+    print(f"{'SAMPLE ENTRIES':^50}")
+    print("=" * 50)
+
+    for i in range(min(n, len(dataset))):
+        print(f"\n📄 SAMPLE {i + 1}")
+        print("-" * 30)
+        print(f"🎬 Video file: video/{dataset[i].get('video_file', 'N/A')}")
+        print(f"📝 Title: {dataset[i].get('title', 'N/A')}")
+        print(f"💡 TL;DR: {dataset[i].get('tldr', 'N/A')}")
+        print(f"🔬 Primary area: {dataset[i].get('primary_area', 'N/A')}")
+        print(f"🏷️  Keywords: {dataset[i].get('keywords', 'N/A')}")
+        print("=" * 50)
+
+
+if __name__ == "__main__":
+    # Load the dataset
+    dataset = load_dataset("vivianchen98/LearningPaper24", data_files="metadata/catalog.jsonl", split="train")
+    print(f"Successfully loaded LearningPaper24 dataset with {len(dataset)} entries.")
+
+    # Display statistics
+    display_dataset_statistics(dataset)
+
+    # Display sample entries
+    display_sample_entries(dataset)