[SPARK-23645][MINOR][DOCS][PYTHON] Add docs RE pandas_udf with keyw…

…ord args

## What changes were proposed in this pull request?

Add documentation about the limitations of `pandas_udf` with keyword arguments and related concepts, like `functools.partial` fn objects.

NOTE: intermediate commits on this PR show some of the steps that can be taken to fix some (but not all) of these pain points.

### Survey of problems we face today:

(Initialize) Note: python 3.6 and spark 2.4snapshot.
```
 from pyspark.sql import SparkSession
 import inspect, functools
 from pyspark.sql.functions import pandas_udf, PandasUDFType, col, lit, udf

 spark = SparkSession.builder.getOrCreate()
 print(spark.version)

 df = spark.range(1,6).withColumn('b', col('id') * 2)

 def ok(a,b): return a+b
```

Using a keyword argument at the call site `b=...` (and yes, *full* stack trace below, haha):
```
---> 14 df.withColumn('ok', pandas_udf(f=ok, returnType='bigint')('id', b='id')).show() # no kwargs

TypeError: wrapper() got an unexpected keyword argument 'b'
```

Using partial with a keyword argument where the kw-arg is the first argument of the fn:
*(Aside: kind of interesting that lines 15,16 work great and then 17 explodes)*
```
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-9-e9f31b8799c1> in <module>()
     15 df.withColumn('ok', pandas_udf(f=functools.partial(ok, 7), returnType='bigint')('id')).show()
     16 df.withColumn('ok', pandas_udf(f=functools.partial(ok, b=7), returnType='bigint')('id')).show()
---> 17 df.withColumn('ok', pandas_udf(f=functools.partial(ok, a=7), returnType='bigint')('id')).show()

/Users/stu/ZZ/spark/python/pyspark/sql/functions.py in pandas_udf(f, returnType, functionType)
   2378         return functools.partial(_create_udf, returnType=return_type, evalType=eval_type)
   2379     else:
-> 2380         return _create_udf(f=f, returnType=return_type, evalType=eval_type)
   2381
   2382

/Users/stu/ZZ/spark/python/pyspark/sql/udf.py in _create_udf(f, returnType, evalType)
     54                 argspec.varargs is None:
     55             raise ValueError(
---> 56                 "Invalid function: 0-arg pandas_udfs are not supported. "
     57                 "Instead, create a 1-arg pandas_udf and ignore the arg in your function."
     58             )

ValueError: Invalid function: 0-arg pandas_udfs are not supported. Instead, create a 1-arg pandas_udf and ignore the arg in your function.
```

Author: Michael (Stu) Stewart <mstewart141@gmail.com>

Closes #20900 from mstewart141/udfkw2.

python/pyspark/sql/functions.py

@@ -2154,6 +2154,8 @@ def udf(f=None, returnType=StringType()):
         in boolean expressions and it ends up with being executed all internally. If the functions
         can fail on special rows, the workaround is to incorporate the condition into the functions.
 
+    .. note:: The user-defined functions do not take keyword arguments on the calling side.
+
     :param f: python function if used as a standalone function
     :param returnType: the return type of the user-defined function. The value can be either a
         :class:`pyspark.sql.types.DataType` object or a DDL-formatted type string.
@@ -2337,6 +2339,8 @@ def pandas_udf(f=None, returnType=None, functionType=None):
     .. note:: The user-defined functions do not support conditional expressions or short circuiting
         in boolean expressions and it ends up with being executed all internally. If the functions
         can fail on special rows, the workaround is to incorporate the condition into the functions.
+
+    .. note:: The user-defined functions do not take keyword arguments on the calling side.
     """
     # decorator @pandas_udf(returnType, functionType)
     is_decorator = f is None or isinstance(f, (str, DataType))