Update app.py

app.py

@@ -7,6 +7,19 @@ from pandas.tseries.offsets import MonthEnd
 import datetime
 
 def plot_and_predict(zip, start_year, start_month, prediction_months):
+    # Input validation for ZIP code
+    if not zip.isdigit() or len(zip) != 5:
+        return "Error: Please enter a valid 5-digit ZIP code."
+    
+    # Input validation for start year
+    current_year = datetime.datetime.now().year
+    if not start_year.isdigit() or not (2000 <= int(start_year) <= current_year):
+        return f"Error: Please enter a valid year between 2000 and {current_year}."
+
+    # Combine year and month into a start date
+    start_date = f"{start_year}-{start_month:02d}-01"
+    start_date = pd.to_datetime(start_date)
+
     # Read and process the real estate data from Zillow
     df = pd.read_csv('https://files.zillowstatic.com/research/public_csvs/zhvi/Zip_zhvi_uc_sfrcondo_tier_0.33_0.67_sm_sa_month.csv')
     df = df[df['RegionName'] == int(zip)]
@@ -15,11 +28,13 @@ def plot_and_predict(zip, start_year, start_month, prediction_months):
     df.columns = ['Date', 'Price']
     df['Date'] = pd.to_datetime(df['Date'])
 
-    # Combine year and month into a start date and filter data based on it
-    start_date = f"{start_year}-{start_month:02d}-01"
-    start_date = pd.to_datetime(start_date)
+    # Filter data based on start date
     df = df[df['Date'] >= start_date]
 
+    # Check for empty dataframe
+    if df.empty:
+        return "Error: No data found for the provided ZIP code or start year/month. Please check your inputs."
+
     # Train linear regression model
     df['MonthsSinceStart'] = np.arange(len(df))
     X = df['MonthsSinceStart'].values.reshape(-1, 1)
@@ -60,22 +75,12 @@ def plot_and_predict(zip, start_year, start_month, prediction_months):
 
     return fig
 
-# Custom validation functions
-def validate_zip(zip_code):
-    if not zip_code.isdigit() or len(zip_code) != 5:
-        return "Please enter a valid 5-digit ZIP code."
-
-def validate_year(year):
-    current_year = datetime.datetime.now().year
-    if not year.isdigit() or not (2000 <= int(year) <= current_year):
-        return f"Please enter a valid year between 2000 and {current_year}."
-
-# Gradio interface with updated inputs and validations
+# Gradio interface with updated inputs
 interface = gr.Interface(
     fn=plot_and_predict,
     inputs=[
-        gr.Textbox(label="ZIP Code", placeholder="e.g., 90210", validation=validate_zip),
-        gr.Textbox(label="Start Year", placeholder="e.g., 2020", validation=validate_year),
+        gr.Textbox(label="ZIP Code", placeholder="e.g., 90210"),
+        gr.Textbox(label="Start Year", placeholder="e.g., 2020"),
         gr.Dropdown(label="Start Month", choices=[str(i) for i in range(1, 13)], placeholder="Select Month"),
         gr.Slider(minimum=1, maximum=60, step=1, label="Prediction Months", default=12),
     ],