support more date inferences in the csv reader

### Is your feature request related to a problem or challenge?

given a csv
```csv
mm/dd/yyyy,mm-dd-yyyy,dd/mm/yyyy,dd-mm-yyyy,yyyy/mm/dd,yyyy-mm-dd
01/01/2012,01-01-2012,01/01/2012,01-01-2012,2012/01/01,2012-01-01
02/02/2013,02-02-2013,02/02/2013,02-02-2013,2013/02/02,2013-02-02
03/03/2014,03-03-2014,03/03/2014,03-03-2014,2014/03/03,2014-03-03
04/04/2015,04-04-2015,04/04/2015,04-04-2015,2015/04/04,2015-04-04
05/05/2016,05-05-2016,05/05/2016,05-05-2016,2016/05/05,2016-05-05
06/06/2017,06-06-2017,06/06/2017,06-06-2017,2017/06/06,2017-06-06
07/07/2018,07-07-2018,07/07/2018,07-07-2018,2018/07/07,2018-07-07
```
currently only the last column will get converted to a `Date32`

```sql
❯ SELECT
arrow_typeof("mm/dd/yyyy") AS "mm/dd/yyyy",
arrow_typeof("mm-dd-yyyy") AS "mm-dd-yyyy",
arrow_typeof("dd/mm/yyyy") AS "dd/mm/yyyy",
arrow_typeof("dd-mm-yyyy") AS "dd-mm-yyyy",
arrow_typeof("yyyy/mm/dd") AS "yyyy/mm/dd",
arrow_typeof("yyyy-mm-dd") AS "yyyy-mm-dd"
from 'testdata/csv/dates.csv' limit 1;
+------------+------------+------------+------------+------------+------------+
| mm/dd/yyyy | mm-dd-yyyy | dd/mm/yyyy | dd-mm-yyyy | yyyy/mm/dd | yyyy-mm-dd |
+------------+------------+------------+------------+------------+------------+
| Utf8 | Utf8 | Utf8 | Utf8 | Utf8 | Date32 |
+------------+------------+------------+------------+------------+------------+
```

### Describe the solution you'd like

it'd be nice to auto detect more of these formats. I thought at the very least `YYYY/MM/DD` or `DD/MM/YYYY` would be valid as they are both extremely common.

### Describe alternatives you've considered

there really arent any good alternatives as there aren't any ergonomic ways to cast the utf8 field to date32 through the sql interface.

### Additional context

_No response_

Reproduce the issue with the CSV example and the SQL type inspection query shown in the report. Trace the CSV reader's existing date inference for the yyyy-mm-dd column and determine how the requested formats should be distinguished, especially where day and month are ambiguous. Done means the intended formats are inferred consistently and covered by tests.

Written by the indexing model from the issue text.