According to the docs numpy.loadtxt is
a fast reader for simply formatted files. The genfromtxt function provides more sophisticated handling of, e.g., lines with missing values.
so there are only a few options to handle more complicated files.
As mentioned numpy.genfromtxt has more options. So as an example you could use
import numpy as np
data = np.genfromtxt('e:\dir1\datafile.csv', delimiter=',', skip_header=10,
skip_footer=10, names=['x', 'y', 'z'])
to read the data and assign names to the columns (or read a header line from the file with names=True) and than plot it with
ax1.plot(data['x'], data['y'], color='r', label='the data')
I think numpy is quite well documented now. You can easily inspect the docstrings from within ipython or by using an IDE like spider if you prefer to read them rendered as HTML.