[SPARK-15264][SPARK-15274][SQL] CSV Reader Error on Blank Column Names

## What changes were proposed in this pull request?

When a CSV begins with:
- `,,`
OR
- `"","",`

meaning that the first column names are either empty or blank strings and `header` is specified to be `true`, then the column name is replaced with `C` + the index number of that given column. For example, if you were to read in the CSV:
```
"","second column"
"hello", "there"
```
Then column names would become `"C0", "second column"`.

This behavior aligns with what currently happens when `header` is specified to be `false` in recent versions of Spark.

### Current Behavior in Spark <=1.6
In Spark <=1.6, a CSV with a blank column name becomes a blank string, `""`, meaning that this column cannot be accessed. However the CSV reads in without issue.

### Current Behavior in Spark 2.0
Spark throws a NullPointerError and will not read in the file.

#### Reproduction in 2.0
https://databricks-prod-cloudfront.cloud.databricks.com/public/4027ec902e239c93eaaa8714f173bcfc/346304/2828750690305044/484361/latest.html

## How was this patch tested?
A new test was added to `CSVSuite` to account for this issue. We then have asserts that test for being able to select both the empty column names as well as the regular column names.

Author: Bill Chambers <bill@databricks.com>
Author: Bill Chambers <wchambers@ischool.berkeley.edu>

Closes #13041 from anabranch/master.

1 files changed, 1 insertions, 1 deletions

diff --git a/python/pyspark/sql/readwriter.py b/python/pyspark/sql/readwriter.py
index 7fd7583972..5cb186016e 100644
--- a/python/pyspark/sql/readwriter.py
+++ b/python/pyspark/sql/readwriter.py
@@ -358,7 +358,7 @@ class DataFrameReader(object):
 
         >>> df = spark.read.csv('python/test_support/sql/ages.csv')
         >>> df.dtypes
-        [('C0', 'string'), ('C1', 'string')]
+        [('_c0', 'string'), ('_c1', 'string')]
         """
         if schema is not None:
             self.schema(schema)