input: Write a function to convert a given SQL statement into a Python Pandas DataFrame. The function should take the SQL statement as a string and a database connection object, and then return a Pandas DataFrame. If the SQL statement is empty, the function should return an empty DataFrame.
  assert convert_sql_to_df("SELECT * FROM book", conn).equals(pd.read_sql_query("SELECT * FROM book;", conn))==True
  assert convert_sql_to_df("", conn).empty==True
  assert convert_sql_to_df("SELECT title FROM book", conn).equals(pd.read_sql_query("SELECT title FROM book;", conn))==True
  assert convert_sql_to_df("SELECT author, year FROM book", conn).equals(pd.read_sql_query("SELECT author, year FROM book;", conn))==True
  assert convert_sql_to_df("SELECT * FROM nonexistent_table", conn).equals(pd.DataFrame())==True
output: def convert_sql_to_df(sql_statement, conn):
      if not sql_statement:
          return pd.DataFrame()
      try:
          return pd.read_sql_query(sql_statement, conn)
      except:
          return pd.DataFrame()