Execute SQL queries directly on one or more CSV files

In #259, with the new tool `sql2csv`, it was already suggested that you could execute SQL queries directly on CSV files using a hacky bash script. Now, with these small changes to `csvsql`, you can truly execute SQL queries on one or more CSV files.

This functionality is similar to [TextQL](https://github.com/dinedal/textql) and [Q](https://github.com/harelba/q). However, thanks to the solid codebase of `csvkit`, `csvsql` offers both multiple tables and proper escaping of output. The following example, which joins two data sets that can be found in the examples directory, illustrates the changes:

````bash
 < iris.csv python ../csvkit/utilities/csvsql.py --query 'select m.usda_id, avg(i.sepal_length) as mean_sepal_length from stdin as i join irismeta as m on (i.species = m.species) group by m.species' irismeta.csv | csvlook
|----------+--------------------|
|  usda_id | mean_sepal_length  |
|----------+--------------------|
|  IRSE    | 5.006              |
|  IRVE2   | 5.936              |
|  IRVI    | 6.588              |
|----------+--------------------|
````

Note that you can now mix standard input and filenames. It is no longer necessary to specify `--table` when standard input is provided. Tables based on standard input are named "stdin" by default. Table names can still be overridden by specifying a (comma delimited) string to `--tables`. When `--query` is specified and `--db` is not, `sqlite:///:memory:` is used as the connection string and `--insert` is set to True. Multiple SQL queries can be specified by using ";" as a delimiter. Only the output of the last query is outputted as CSV. This allows you to execute SQL queries in memory.  

No functionality has been removed. Appropriate tests have been added. I'll write the corresponding documentation once these changes have been accepted.