Update app.py

app.py

@@ -1,36 +1,22 @@
-import gradio as gr
-import pandas as pd
-import matplotlib.pyplot as plt
+import gradio as gr import pandas as pd import plotly.express as px import plotly.graph_objects as go
 
 CSV_URL = "https://gardenstatemls.stats.showingtime.com/infoserv/s-v1/kpou-Asg"
 
-# Function to fetch and plot CSV data
-def plot_csv():
-    # Read CSV directly from URL
-    df = pd.read_csv(CSV_URL)
+def plot_csv(area): df = pd.read_csv(CSV_URL) fig = go.Figure()
 
-    # Create a simple plot - adjust as needed based on CSV columns
-    plt.figure(figsize=(10, 6))
-    df.plot(x=df.columns[0], y=df.columns[1:], marker='o')
-    plt.title("CSV Data Plot")
-    plt.xlabel(df.columns[0])
-    plt.ylabel("Values")
-    plt.grid(True)
-    plt.tight_layout()
+# Add full data traces
+for col in df.columns[1:]:
+    fig.add_trace(go.Scatter(x=df[df.columns[0]], y=df[col], mode='lines', name=col))
 
-    # Save the plot to a file
-    plt.savefig("plot.png")
-    plt.close()
+# Add filtered trace if area is specified
+if area and 'Area' in df.columns:
+    filtered_df = df[df['Area'].str.contains(area, case=False, na=False)]
+    for col in filtered_df.columns[1:]:
+        fig.add_trace(go.Scatter(x=filtered_df[filtered_df.columns[0]], y=filtered_df[col], mode='lines+markers', name=f"Filtered: {col} ({area})"))
 
-    return "plot.png"
+fig.update_layout(title="Full CSV Data Plot with Area Filter Overlay")
+return fig
 
-# Gradio Interface
-demo = gr.Interface(
-    fn=plot_csv,
-    inputs=[],
-    outputs=gr.Image(type="filepath"),
-    title="CSV Plotter",
-    description="This Space downloads the CSV from GSMLS"
-)
+with gr.Blocks() as demo: gr.Markdown("## Interactive CSV Plotter (Full Plot + Area Filter Overlay)") area_input = gr.Textbox(label="Filter Area", placeholder="Enter area name to highlight") plot_output = gr.Plot() run_button = gr.Button("Plot") run_button.click(plot_csv, inputs=area_input, outputs=plot_output)
 
 demo.launch(debug=True)