fix: Add check for existing correct columns

app.py

@@ -60,22 +60,26 @@ def plot_anomalies(df_test_value, data, anomalies):
     return fig
 
 def clean_data(df):
-    # Check if 'Date' and 'Hour' columns exist in the dataframe
-    if "Date" in df.columns and "Hour" in df.columns:
+    # Check if the DataFrame already contains the correct columns
+    if "timestamp" in df.columns and "value" in df.columns:
+        df["timestamp"] = pd.to_datetime(df["timestamp"])
+        return df
+
+    # Check if DataFrame contains the columns to be converted
+    elif "Date" in df.columns and "Hour" in df.columns and "Hourly_Labor_Hours_Total" in df.columns:
         # Convert "Date" and "Hour" columns into datetime format
         df["timestamp"] = pd.to_datetime(df["Date"] + ' ' + df["Hour"].astype(str) + ":00:00")
+
         # Keep only necessary columns
         df = df[["timestamp", "Hourly_Labor_Hours_Total"]]
+
         # Rename column
         df.rename(columns={"Hourly_Labor_Hours_Total": "value"}, inplace=True)
-    elif "timestamp" in df.columns:
-        # If 'timestamp' column exists, rename the value column if necessary
-        if "Hourly_Labor_Hours_Total" in df.columns:
-            df.rename(columns={"Hourly_Labor_Hours_Total": "value"}, inplace=True)
-        df = df[["timestamp", "value"]]
+
+        return df
+
     else:
-        raise ValueError("Input data must have either 'Date' and 'Hour' columns, or a 'timestamp' column.")
-    return df
+        raise ValueError("Dataframe does not contain necessary columns.")
 
 def master(file):
     # read file