title: how do use pyspark filter when column name has blank
body: <p>My pyspark data frame has several columns that has blank in them for e.g. Inbound Delivery ( note space in between). When i'm trying to compare using .filter i'm getting an error . I dont want to redefine the schema removing the blank since i have huge table with almost all have the same space in name. is there a quick way to use filter with name having blank</p>
  
  <p>dfjoin.where ('Inbound Delivery=0090043373' ).show()</p>
  
  <p>Error</p>
  
  <hr>
  
  <p>Py4JJavaError                             Traceback (most recent call last)
  ~\Desktop\spark\spark-2.4.3-bin-hadoop2.7\python\pyspark\sql\utils.py in deco(*a, **kw)
       62         try:
  ---> 63             return f(*a, **kw)
       64         except py4j.protocol.Py4JJavaError as e:</p>
  
  <p>~\Desktop\spark\spark-2.4.3-bin-hadoop2.7\python\lib\py4j-0.10.7-src.zip\py4j\protocol.py in get_return_value(answer, gateway_client, target_id, name)
      327                     "An error occurred while calling {0}{1}{2}.\n".
  --> 328                     format(target_id, ".", name), value)
      329             else:</p>
  
  <p>Py4JJavaError: An error occurred while calling o1424.filter.
  : org.apache.spark.sql.catalyst.parser.ParseException: 
  mismatched input '=' expecting (line 1, pos 16)</p>