Update app.py

app.py

@@ -55,5 +55,43 @@ def main():
 # Run the app
 if __name__ == "__main__":
     main()
+    import dash
+from dash import dcc, html
+import plotly.express as px
+import pandas as pd
+
+# Load data
+df = pd.read_csv('your_data.csv')
+
+# Create Dash app
+app = dash.Dash(__name__)
+
+# Generate a plotly chart
+fig = px.scatter(df, x='column_x', y='column_y', color='category_column', title="Interactive Scatter Plot")
+
+# Define the layout with a dropdown for filtering
+app.layout = html.Div([
+    html.H1("Interactive Data Visualization"),
+    dcc.Dropdown(
+        id='category-dropdown',
+        options=[{'label': i, 'value': i} for i in df['category_column'].unique()],
+        value=df['category_column'].unique()[0]  # Default value
+    ),
+    dcc.Graph(id='scatter-plot', figure=fig)
+])
+
+# Callback to update figure based on dropdown selection
+@app.callback(
+    dash.dependencies.Output('scatter-plot', 'figure'),
+    [dash.dependencies.Input('category-dropdown', 'value')]
+)
+def update_graph(selected_category):
+    filtered_df = df[df['category_column'] == selected_category]
+    return px.scatter(filtered_df, x='column_x', y='column_y', color='category_column', title="Filtered Scatter Plot")
+
+# Run the app
+if __name__ == '__main__':
+    app.run_server(debug=True)
+