Fix: Standardize date_local format between AQS and Envista data

- Convert Envista date_local from ISO timestamp to YYYY-MM-DD format in transform_env.py
- Update calculate_aqi.py cutoff_date to use timezone-naive datetime for comparison
- Ensures consistent date format when AQS and Envista data are consolidated

Author: DEQabiberi

src/envista/transformers/calculate_aqi.py

@@ -52,8 +52,9 @@ def pm25_to_aqi_new(concentration: float) -> int | Any:
 def pm25_to_aqi_with_date_check(row: pd.Series) -> int | Any:
     """Apply appropriate AQI calculation based on date."""
     concentration = row["arithmetic_mean"]
+    # Parse date_local without timezone info and compare with naive datetime
     date_local = pd.to_datetime(row["date_local"])
-    cutoff_date = pd.to_datetime("2024-05-06 00:00:00-0800")
+    cutoff_date = pd.to_datetime("2024-05-06")
 
     if date_local < cutoff_date:
         return pm25_to_aqi_old(concentration)

src/envista/transformers/transform_env.py

@@ -61,6 +61,9 @@ def transform_env_daily(year: str, raw_daily_files: list[Path], unique_monitors:
         "data_channels_valid":"validity_indicator",
         "stations_tag":"site_code"})
 
+    # Standardize date_local format to match AQS (YYYY-MM-DD)
+    transformed_df["date_local"] = pd.to_datetime(transformed_df["date_local"]).dt.strftime("%Y-%m-%d")
+    
     # Add and populate columns to match AQS schema
     transformed_df["poc"] = "99" # Dummy value to distinguish from AQS data
     transformed_df["parameter_code"] = "88502" # True AQS code for non-regulatory PM2.5 data