
"""
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.
"""

from __future__ import print_function
import numpy
from matplotlib.mlab import csv2rec
import matplotlib.pyplot as plt
import matplotlib.cbook as cbook
from matplotlib.ticker import Formatter

datafile = cbook.get_sample_data('msft.csv', asfileobj=False)
print ('loading %s' % 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, ax = plt.subplots()
ax.xaxis.set_major_formatter(formatter)
ax.plot(numpy.arange(len(r)), r.close, 'o-')
fig.autofmt_xdate()
plt.show()
