Update app.py

app.py

@@ -3,44 +3,54 @@ import pandas as pd
 import seaborn as sns
 import matplotlib.pyplot as plt
 
-# Load dataset automatically from GitHub
-CSV_URL = "https://raw.githubusercontent.com/datablist/sample-csv-files/main/files/people/people-100.csv"
-
-def load_data():
-    df = pd.read_csv(CSV_URL)
-    return df.head(10)
-
-def visualize_data(column_x, column_y):
-    df = pd.read_csv(CSV_URL)
-    plt.figure(figsize=(7, 5))
-    sns.scatterplot(x=df[column_x], y=df[column_y])
-    plt.title(f"Scatter Plot: {column_x} vs {column_y}")
+# Load dataset
+url = "https://raw.githubusercontent.com/laxmimerit/All-CSV-ML-Data-Files-Download/master/IMDB-Movie-Data.csv"
+df = pd.read_csv(url)
+
+# --- Visualization Functions ---
+def show_data(n):
+    """Show top n rows of the dataset."""
+    return df.head(n)
+
+def plot_visualizations(choice):
+    """Generate different plots based on user choice."""
+    plt.figure(figsize=(8, 5))
+    if choice == "Rating Distribution":
+        sns.histplot(df["Rating"], bins=15, kde=True)
+        plt.title("Distribution of Movie Ratings")
+    elif choice == "Top 10 Directors":
+        top_directors = df["Director"].value_counts().head(10)
+        sns.barplot(x=top_directors.values, y=top_directors.index)
+        plt.title("Top 10 Directors by Movie Count")
+    elif choice == "Genre Frequency":
+        all_genres = df["Genre"].str.split(",").explode().str.strip()
+        top_genres = all_genres.value_counts().head(10)
+        sns.barplot(x=top_genres.values, y=top_genres.index)
+        plt.title("Top 10 Movie Genres")
+    elif choice == "Revenue vs Rating":
+        sns.scatterplot(x="Rating", y="Revenue (Millions)", data=df)
+        plt.title("Revenue vs Rating")
     plt.tight_layout()
     return plt.gcf()
 
-def get_column_names():
-    df = pd.read_csv(CSV_URL)
-    return list(df.columns)
-
-# Dropdown options
-cols = get_column_names()
-
-# Gradio interface
-with gr.Blocks(title="CSV Visualizer using Gradio") as demo:
-    gr.Markdown("# 📊 CSV Visualizer\nUpload from GitHub and Explore the Data!")
-
-    with gr.Tab("View Data"):
-        view_btn = gr.Button("Load Data")
-        data_output = gr.Dataframe(label="Data Preview")
-        view_btn.click(load_data, outputs=data_output)
-
-    with gr.Tab("Visualize Data"):
-        x_col = gr.Dropdown(choices=cols, label="Select X-axis Column")
-        y_col = gr.Dropdown(choices=cols, label="Select Y-axis Column")
-        plot_btn = gr.Button("Generate Plot")
-        plot_output = gr.Plot(label="Visualization Output")
-
-        plot_btn.click(visualize_data, inputs=[x_col, y_col], outputs=plot_output)
+# --- Gradio Interface ---
+with gr.Blocks() as demo:
+    gr.Markdown("# 🎬 IMDB Movie Data Explorer")
+    gr.Markdown("Explore insights from the IMDB Movie Dataset with visualizations.")
+    
+    with gr.Tab("📊 View Data"):
+        n_slider = gr.Slider(5, 50, value=10, step=5, label="Select number of rows")
+        data_output = gr.Dataframe(label="Dataset Preview")
+        n_slider.change(show_data, inputs=n_slider, outputs=data_output)
+        
+    with gr.Tab("📈 Visualize"):
+        choice = gr.Radio(
+            ["Rating Distribution", "Top 10 Directors", "Genre Frequency", "Revenue vs Rating"],
+            label="Select Visualization",
+        )
+        plot_output = gr.Plot(label="Visualization")
+        choice.change(plot_visualizations, inputs=choice, outputs=plot_output)
+    
+    gr.Markdown("Made with ❤️ using Gradio + Seaborn")
 
-# Launch app
 demo.launch()