read_csv is inefficient for wide tables
I was loading some relatively large CSV files (roughly three hundred by one million), and noticed that the layout of those CSVs is actually critical to Pandas' ability to read them to memory.  A "wide" format uses large amounts of memory and takes an extremely long time to run (killed the process after a half hour).  The exact same data, but presented in a "tall" format (ie 300 columns and one million rows) reads within about sixty seconds.  Given there is no sort of "warning" message regarding the number of columns when reading the CSV file, I could easily see this confusing a new user and leading them to believe that Pandas is simply unable to handle that volume of data, when in fact it can, given that the data is formatted correctly.  Perhaps some broader documentation on wide vs tall inputs would be appropriate.
