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"""
When plotting daily data, a frequent request is to plot the data
ignoring skips, eg no extra spaces for weekends. This is particularly
common in financial time series, when you may have data for M-F and
not Sat, Sun and you don't want gaps in the x axis. The approach is
to simply use the integer index for the xdata and a custom tick
Formatter to get the appropriate date string for a given index.
"""
import numpy
from matplotlib.mlab import csv2rec
from pylab import figure, show
import matplotlib.cbook as cbook
from matplotlib.ticker import Formatter
datafile = cbook.get_sample_data('msft.csv', asfileobj=False)
print 'loading', datafile
r = csv2rec(datafile)[-40:]
class MyFormatter(Formatter):
def __init__(self, dates, fmt='%Y-%m-%d'):
self.dates = dates
self.fmt = fmt
def __call__(self, x, pos=0):
'Return the label for time x at position pos'
ind = int(round(x))
if ind>=len(self.dates) or ind<0: return ''
return self.dates[ind].strftime(self.fmt)
formatter = MyFormatter(r.date)
fig = figure()
ax = fig.add_subplot(111)
ax.xaxis.set_major_formatter(formatter)
ax.plot(numpy.arange(len(r)), r.close, 'o-')
fig.autofmt_xdate()
show()
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