Fix DataFrame Error Handling for Non-existent Columns #625

examples/bug_simulation.py

@@ -0,0 +1,68 @@
+import traceback
+
+import pandas as pd
+
+from preswald.engine.runner import validate_dataframe_operation
+
+
+def simulate_bug_and_fix():
+    """
+    Simulate the original bug and demonstrate our fix.
+    """
+    print("🔍 Bug Simulation: Column 'value' not found in DataFrame")
+    print("==================================================")
+
+    # Create a sample DataFrame (similar to the weather data)
+    df = pd.DataFrame(
+        {
+            "Humidity": [0.81, 0.76, 0.68, 0.92, 0.95],
+            "Temperature": [21.2, 22.1, 19.5, 18.7, 16.3],
+            "Summary": ["Partly Cloudy", "Mostly Cloudy", "Clear", "Foggy", "Rain"],
+        }
+    )
+
+    print("\n📊 Sample DataFrame:")
+    print(df.head())
+    print("\n📋 Available columns:", ", ".join(df.columns))
+
+    # Scenario 1: Original bug - trying to access 'value' column
+    print("\n❌ Scenario 1: Original bug - trying to access 'value' column")
+    threshold = 50
+    try:
+        # This would fail with a cryptic error
+        filtered_data = df[df["value"] > threshold]
+        print(filtered_data)  # This line won't execute
+    except Exception as e:
+        print(f"Error: {e}")
+        print("Traceback:", "".join(traceback.format_tb(e.__traceback__)))
+
+    # Scenario 2: With our fix - validation before operation
+    print("\n✅ Scenario 2: With our fix - validation before operation")
+    threshold = 50
+    try:
+        # This will fail with a helpful error message
+        validate_dataframe_operation(df, "value", "filtering")
+        filtered_data = df[df["value"] > threshold]
+        print(filtered_data)  # This line won't execute
+    except ValueError as e:
+        print(f"Error: {e}")
+
+    # Scenario 3: Correct usage
+    print("\n✅ Scenario 3: Correct usage with valid column")
+    humidity_threshold = 0.8
+    try:
+        validate_dataframe_operation(df, "Humidity", "filtering")
+        filtered_data = df[df["Humidity"] > humidity_threshold]
+        print(filtered_data)
+    except Exception as e:
+        print(f"Error: {e}")
+
+    print("\n🎯 Summary of fixes:")
+    print("1. Added early validation of DataFrame operations")
+    print("2. Improved error messages with available columns")
+    print("3. Made error handling consistent between preview and published modes")
+    print("4. Added helpful suggestions to guide users")
+
+
+if __name__ == "__main__":
+    simulate_bug_and_fix()

examples/dataframe_validation_example.py

@@ -0,0 +1,31 @@
+from preswald import connect, get_df, slider, table, text
+from preswald.engine.runner import validate_dataframe_operation
+
+
+text("# DataFrame Validation Example")
+
+# Initialize connection
+connect()
+
+# Load sample data
+df = get_df("weatherhistory_csv")
+
+# Show available columns
+text("## Available Columns")
+text(f"Columns in the dataset: {', '.join(df.columns)}")
+
+# Example 1: Valid column access
+text("## Example 1: Valid Column Access")
+threshold = slider("Humidity Threshold", min_val=0, max_val=1, default=0.5)
+# Use validation function before operation
+validate_dataframe_operation(df, "Humidity", "filtering")
+table(df[df["Humidity"] > threshold], title="Filtered by Humidity")
+
+# Example 2: Invalid column access (will show helpful error)
+text("## Example 2: Invalid Column Access")
+threshold2 = slider("Value Threshold", min_val=0, max_val=100, default=50)
+try:
+    validate_dataframe_operation(df, "value", "filtering")
+    table(df[df["value"] > threshold2], title="Filtered by Value")
+except ValueError as e:
+    text(f"Error: {e!s}")