Feature request: read_csv/read_table/read_fwf - read multiple files with the same structure, applying the same parameters (`skiprows`, `skipfooter`, `nrows`)
Hello,

I think it would make sense to make `read_csv()`, `read_table()`, `read_fwf()` able to read multiple  files with the same structure. It might be tricky to read multiple files into one string, especially when all of them have header line(s) and when you want to use the following parameters: `skiprows`, `skipfooter`, `nrows`.
The logic  for (`skiprows`, `skipfooter`, `nrows`) is already implemented, so IMO it shouldn't be very difficult. The `header` parameter (if header exists) must be read/parsed only from the first (from one) file.

Of course one can always do something like: 

`df = pd.concat([pd.read_csv(f, **kwargs) for f in flist], ignore_index=True)
`

but it's not very efficient when working with big files.

In the last days there were plenty of similar questions stackoverflow.com, asking how to merge CSV files with the same structure.

Thank you!
