More convenient syntax for DataFrame constructor to declare order of columns?
I've searched the list, docs and issue list and didn't find this addressed, sorry if it was.  It seems to me that right now, if I want to specify the order of my columns in new DataFrame built from existing Series, the only way to do it is to build a dict and pass the columns argument separately, with a redundant spelling of the column names:

```
df = pd.DataFrame(dict(m30_t10=splits_30, m15_t10=splits_15,
                       m30_m15=splits_m),
                  columns=['m30_t10', 'm15_t10','m30_m15'])
```

I'm wondering if a more convenient syntax could be devised for this operation.  It seems that list-of-tuples already has different semantics, so the minimal change of the above doesn't work:

```
# This gives an error:
df3 = pd.DataFrame([('m30_t10', splits_30), ('m15_t10', splits_15),
                    ('m30_m15', splits_m)])
```

It's unfortunate, b/c the above is incidentally a valid dict constructor:

```
# This is OK:
df3 = pd.DataFrame(dict([('m30_t10', splits_30), ('m15_t10', splits_15),
                    ('m30_m15', splits_m)]))
```

But since a list is an inherently ordered data structure, it would be nice if it was accepted also as a constructor for DataFrame, carrying with it the implicit column order.
