First impression from a new user

Also, you are using some parameters (usecols, unpack) to

    > load() that
    > http://matplotlib.sourceforge.net/matplotlib.pylab.html#-load
    > doesn't know about.

The web page is a bit out of date and needs updating -- thanks for the
pointers to the stale and broken links. The "load" parameters used
here were recently introduced. I suggest keeping an ipython shell
open when working with matplotlib, so you have ready access to the
online help

In [1]: help load

load(fname, comments='%', delimiter=None, converters=None,
     skiprows=0, usecols=None, unpack=False):
    
    Load ASCII data from fname into an array and return the array.

    The data must be regular, same number of values in every row

    fname can be a filename or a file handle. Support for gzipped
    files is automatic, if the filename ends in .gz

    matfile data is not currently supported, but see
    Nigel Wade's matfile ftp://ion.le.ac.uk/matfile/matfile.tar.gz

    Example usage:

      X = load('test.dat') # data in two columns
      t = X[:,0]
      y = X[:,1]

    Alternatively, you can do the same with "unpack"; see below

      X = load('test.dat') # a matrix of data
      x = load('test.dat') # a single column of data

    comments - the character used to indicate the start of a comment
    in the file

    delimiter is a string-like character used to seperate values in the
    file. If delimiter is unspecified or None, any whitespace string is
    a separator.

    converters, if not None, is a dictionary mapping column number to
    a function that will convert that column to a float. Eg, if
    column 0 is a date string: converters={0:datestr2num}

    skiprows is the number of rows from the top to skip

    usecols, if not None, is a sequence of integer column indexes to
    extract where 0 is the first column, eg usecols=(1,4,5) to extract
    just the 2nd, 5th and 6th columns

    unpack, if True, will transpose the matrix allowing you to unpack
    into named arguments on the left hand side

        t,y = load('test.dat', unpack=True) # for two column data
        x,y,z = load('somefile.dat', usecols=(3,5,7), unpack=True)

    See examples/load_demo.py which exeercises many of these options.