Update app.py

app.py

@@ -1,27 +1,60 @@
 import gradio as gr
 import pandas as pd
-import plotly.express as px
 import plotly.graph_objects as go
 
+# The URL from your original script
 CSV_URL = "https://gardenstatemls.stats.showingtime.com/infoserv/s-v1/kpou-Asg"
 
-def plot_csv(area):
-    df = pd.read_csv(CSV_URL)
-    fig = go.Figure()
+def plot_csv():
+    """
+    Reads data from the specified URL, processes it, and creates a plot.
 
-# 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))
+    This function skips the first 9 rows of the CSV, which contain metadata,
+    and removes any empty columns before plotting the data.
 
-# 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})"))
+    Returns:
+        A Plotly figure object showing the median sales price over time.
+    """
+    try:
+        # Read the CSV from the URL, skipping the metadata at the top
+        df = pd.read_csv(CSV_URL, skiprows=9)
 
-fig.update_layout(title="Full CSV Data Plot with Area Filter Overlay")
-return fig
+        # Clean up the DataFrame
+        if 'Unnamed: 2' in df.columns:
+            df = df.drop(columns=['Unnamed: 2'])
 
-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)
+        # Rename columns for easier use
+        df.columns = ['Date', 'Median Sales Price']
 
+        # Create a Plotly figure
+        fig = go.Figure()
+
+        # Add the data series to the plot
+        fig.add_trace(go.Scatter(x=df['Date'], y=df['Median Sales Price'], mode='lines', name='Median Sales Price'))
+
+        # Update the plot layout for a professional look
+        fig.update_layout(
+            title="Median Sales Price - Entire MLS",
+            xaxis_title="Date",
+            yaxis_title="Median Sales Price ($)",
+            showlegend=True
+        )
+
+        return fig
+
+    except Exception as e:
+        # If there's an error fetching or plotting the data, return the error message
+        return str(e)
+
+
+# Set up the Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("## Median Sales Price Plotter")
+    plot_output = gr.Plot()
+    run_button = gr.Button("Plot Data")
+
+    # Link the button to the plotting function
+    run_button.click(plot_csv, inputs=None, outputs=plot_output)
+
+# Launch the Gradio app
 demo.launch(debug=True)