First impression from a new user

* My data file consists of a date (in ISO format) and

    > integers. Parsing the date was a bit of work. I
    > understand that python's datetime doesn't provide any
    > parsing of dates - but maybe matplotlib should have
    > some functions for that then? FWIW, here is how
    > gnuplot does this (adapted from

    > set xdata time set timefmt "%Y-%m-%d" set format
    > x "%Y-%m"

gnuplot does handle file plots nicely -- here is an example of how to
parse files with date entries and plot them in matplotlib. Basically,
the load function takes a dictionary mapping column index to a
converter function which returns a float.

    from pylab import figure, show, datestr2num, load
    dates, closes = load(
        'data/msft.csv', delimiter=',',
        converters={0:datestr2num}, skiprows=1, usecols=(0,2),

    fig = figure()
    ax = fig.add_subplot(111)
    ax.plot_date(dates, closes)

The function datestr2num takes any date string recognized by
dateutils.parse (most of them) and returns a floating point number
days since 0000-00-00 which is how matplotlib represents dates.

    > * gnuplot has a plot style "steps"
    > (
    > - I could only fake that with with extra "dummy"
    > points in matplotlib as I understand it. It would be
    > nice if matplotlib could do this for me.

We have steps too!

  plot(x, y, linestyle='steps')

Hope this helps,