docs: def gp_datdir(initial, topN):
    """example for plotting from a text file via numpy.loadtxt
  
    1. prepare input/output directories
    2. load the data into an OrderedDict() [adjust axes units]
    3. sort countries from highest to lowest population
    4. select the <topN> most populated countries
    5. call ccsgp.make_plot with data from 4
  
    Below is an output image for country initial T and the 4 most populated
    countries for this initial (click to enlarge). Also see::
  
      $ python -m ccsgp_get_started.examples.gp_datdir -h
  
    for help on the command line options.
  
    .. image:: pics/T.png
       :width: 450 px
  
    .. image:: pics/U.png
       :width: 450 px
  
    :param initial: country initial
    :type initial: str
    :param topN: number of most populated countries to plot
    :type topN: int
    :ivar inDir: input directory according to package structure and initial
    :ivar outDir: output directory according to package structure
    :ivar data: OrderedDict with datasets to plot as separate keys
    :ivar file: data input file for specific country, format: [x y] OR [x y dx dy]
    :ivar country: country, filename stem of input file
    :ivar file_url: absolute url to input file
    :ivar nSets: number of datasets
    """
    # prepare input/output directories
    inDir, outDir = getWorkDirs()
    initial = initial.capitalize()
    inDir = os.path.join(inDir, initial)
    if not os.path.exists(inDir): # catch missing initial
      return "initial %s doesn't exist" % initial
    # prepare data
    data = OrderedDict()
    for file in os.listdir(inDir):
      country = os.path.splitext(file)[0]
      file_url = os.path.join(inDir, file)
      data[country] = np.loadtxt(open(file_url, 'rb')) # load data
      # set y-axis unit to 1M
      data[country][:, 1] /= 1e6
      if data[country].shape[1] > 2: data[country][:, 3:] /= 1e6
    logging.debug(data) # shown if --log flag given on command line
    # sort countries according to mean population (highest -> lowest)
    sorted_data = OrderedDict(sorted(
      data.items(), key = lambda t: np.mean(t[1][:,1]), reverse = True
    ))
    # "pop" (select) N most populated countries
    top_data = OrderedDict(
      sorted_data.popitem(last = False) for i in xrange(topN)
      if sorted_data
    )
    # generate plot using ccsgp.make_plot
    nSets = len(top_data)
    make_plot(
      data = top_data.values(),
      properties = [ getOpts(i) for i in xrange(nSets) ],
      titles = top_data.keys(), # use data keys as legend titles
      name = os.path.join(outDir, initial),
      key = [ 'at graph 1., 1.2', 'maxrows 2' ],
      ylabel = 'total population ({/Symbol \664} 10^{6})',
      xlabel = 'year', rmargin = 0.99, tmargin = 0.85, size='8.5in,8in'
    )
    return 'done'