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 (conn) as arguments, and it should return a Pandas DataFrame containing the result of the SQL query. If the SQL statement is invalid or there is an issue with the connection, the function should return an empty DataFrame.
  
  def sql_to_dataframe(sql_query, conn):
      import pandas as pd
      try:
          df = pd.read_sql_query(sql_query, conn)
          return df
      except:
          return pd.DataFrame()
  
  assert sql_to_dataframe("SELECT * FROM book;", conn).equals(pd.DataFrame({"title":["Book1", "Book2"], "author":["Author1", "Author2"]}))
  assert sql_to_dataframe("SELECT invalid FROM book;", conn).empty == True
  assert sql_to_dataframe("", conn).empty == True
  assert sql_to_dataframe("SELECT * FROM nonexistent_table;", conn).empty == True
  assert sql_to_dataframe("SELECT * FROM book;", None).empty == True
output: def sql_to_dataframe(sql_query, conn):
      import pandas as pd
      try:
          df = pd.read_sql_query(sql_query, conn)
          return df
      except:
          return pd.DataFrame()