""" When plotting time series, eg financial time series, one often wants to leave out days on which there is no data, eh weekends. The example below shows how to use an 'index formatter' to achieve the desired plot """ import numpy as np import matplotlib.pyplot as plt import matplotlib.mlab as mlab import matplotlib.ticker as ticker r = mlab.csv2rec('../data/aapl.csv') r.sort() r = r[-30:] # get the last 30 days # first we'll do it the default way, with gaps on weekends fig = plt.figure() ax = fig.add_subplot(111) ax.plot(r.date, r.adj_close, 'o-') fig.autofmt_xdate() # next we'll write a custom formatter N = len(r) ind = np.arange(N) # the evenly spaced plot indices def format_date(x, pos=None): thisind = np.clip(int(x+0.5), 0, N-1) return r.date[thisind].strftime('%Y-%m-%d') fig = plt.figure() ax = fig.add_subplot(111) ax.plot(ind, r.adj_close, 'o-') ax.xaxis.set_major_formatter(ticker.FuncFormatter(format_date)) fig.autofmt_xdate() plt.show()