input: Write a function to convert a given SQL statement into a Python Pandas DataFrame. The function should take the SQL query and the database connection as input and return the DataFrame.
  assert convert_sql_to_df("SELECT * FROM book;", conn).equals(pd.read_sql_query("SELECT * FROM book;", conn))
  assert convert_sql_to_df("SELECT title, author FROM book WHERE year > 2000;", conn).equals(pd.read_sql_query("SELECT title, author FROM book WHERE year > 2000;", conn))
  assert convert_sql_to_df("SELECT * FROM book WHERE genre = 'Mystery';", conn).equals(pd.read_sql_query("SELECT * FROM book WHERE genre = 'Mystery';", conn))
  assert convert_sql_to_df("SELECT year, count(*) FROM book GROUP BY year;", conn).equals(pd.read_sql_query("SELECT year, count(*) FROM book GROUP BY year;", conn))
  assert convert_sql_to_df("SELECT * FROM book LIMIT 5;", conn).equals(pd.read_sql_query("SELECT * FROM book LIMIT 5;", conn))
output: def convert_sql_to_df(sql_query, conn):
      return pd.read_sql_query(sql_query, conn)