PERF: Explore even faster path for df.to_csv
iotop and a simple-mined c program indicates we're nowhere 
near IO-bound in df.to_csv, at about ~10-15x. 

It might be possible to speed things up considerably with a fast path
for special cases (numerical only) that don't need fancy quoting and other
bells and whistles provided by the underlying csv python module.

``` c
#include <stdio.h>
#include <stdlib.h>

int main(int argc,char **argv)
{
    int i;
    FILE *f;
    char fmt[] = "%f,%f,%f,%f,%f\n";
    while (1) {
    f = fopen("out.csv","wb");
    for(i=0;i<1000000;i++) {
        fprintf(f,fmt, 1.0,2.0,3.0,4.0,5.0);
    }
    fclose(f);
    }
}
```

sustains about 30MB/s on my machine (without even batching writes)
vs ~2-3MB/s for the new (0.11.0) cython df.to_csv().

need to check if it's the stringifying, quoting logic, memory layout, or something 
else that constitutes the difference.

Should also yield insights for any future binary serialization format
implemented.
