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README.md

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+---
+title: YT Comments Explorer
+emoji: 🐢
+colorFrom: blue
+colorTo: purple
+sdk: gradio
+sdk_version: 5.36.2
+app_file: app.py
+pinned: false
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+import pandas as pd
+import matplotlib.pyplot as plt
+import plotly.express as px
+import networkx as nx
+import io
+
+# --- Load your dataset
+df = pd.read_csv("comments.csv", parse_dates=["date"])  # Ensure 'date' is datetime
+df["date"] = pd.to_datetime(df["date"])
+
+# --- 1. Plot messages by day or month
+def plot_messages_over_time(group_by="D"):
+    df_grouped = df.groupby(pd.Grouper(key="date", freq=group_by)).size().reset_index(name="count")
+    fig = px.line(df_grouped, x="date", y="count", title="Messages Over Time")
+    return fig
+
+# --- 2. Plot messages by author
+def plot_messages_by_author(top_n=20):
+    top_authors = df["author"].value_counts().head(top_n).reset_index()
+    top_authors.columns = ["author", "message_count"]
+    fig = px.bar(top_authors, x="author", y="message_count", title=f"Top {top_n} Authors")
+    return fig
+
+# --- 3. Network of threads
+def generate_thread_network(min_replies=1):
+    edges = df[["parent_id", "comment_id"]].dropna()
+    G = nx.DiGraph()
+    for _, row in edges.iterrows():
+        G.add_edge(row["parent_id"], row["comment_id"])
+
+    # Filter small components
+    G_filtered = G.copy()
+    isolated = [node for node in G.nodes if G.degree(node) < min_replies]
+    G_filtered.remove_nodes_from(isolated)
+
+    fig = plot_network(G_filtered)
+    return fig
+
+def plot_network(G):
+    pos = nx.spring_layout(G, seed=42)
+    fig, ax = plt.subplots(figsize=(8, 6))
+    nx.draw(G, pos, with_labels=False, node_size=50, edge_color='gray', alpha=0.7, ax=ax)
+    return fig
+
+# --- Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# 🧠 YouTube Comment Explorer")
+    gr.Markdown("Explore messages by time, author, and discussion threads")
+
+    with gr.Tab("📆 Messages Over Time"):
+        freq_choice = gr.Radio(["D", "M"], label="Group by (D=day, M=month)", value="M")
+        time_plot = gr.Plot()
+        freq_choice.change(fn=plot_messages_over_time, inputs=freq_choice, outputs=time_plot)
+
+    with gr.Tab("👤 Messages by Author"):
+        author_slider = gr.Slider(5, 50, value=20, step=1, label="Top N Authors")
+        author_plot = gr.Plot()
+        author_slider.change(fn=plot_messages_by_author, inputs=author_slider, outputs=author_plot)
+
+    with gr.Tab("🔗 Thread Network"):
+        thread_slider = gr.Slider(1, 10, value=1, step=1, label="Min Replies to Include Node")
+        network_plot = gr.Plot()
+        thread_slider.change(fn=generate_thread_network, inputs=thread_slider, outputs=network_plot)
+
+demo.launch()

requirements.txt

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+gradio
+pandas
+matplotlib
+plotly
+networkx