class DataTransformer:
  def transform_data(self, train_df, test_df):
    for idx, df in enumerate([train_df, test_df]):
      df['DateTime'] = pd.to_datetime(df['DateTime'])

      # Build 'Time' column
      df['Time'] = [date.hour * 3600 + date.minute * 60 + date.second for date in df['DateTime']]

      # Convert DateTime to Unix timestamp
      unixtime = [time.mktime(date.timetuple()) for date in df['DateTime']]
      df['DateTime'] = unixtime

      # Perform one-hot encoding on the DataFrame
      df = pd.get_dummies(df)

      if idx == 0:
        # Split training DataFrame into features (X_train) and target (y_train)
        X_train = df.drop(['Vehicles'], axis=1)
        y_train = df[['Vehicles']]
      elif idx == 1:
        # Store test DataFrame
        X_test = df

    return X_train, y_train, X_test