How to skip empty dates (weekends) in a financial Matplotlib Python graph?

One of the advertised features of scikits.timeseries is "Create time series plots with intelligently spaced axis labels".

You can see some example plots here. In the first example (shown below) the 'business' frequency is used for the data, which automatically excludes holidays and weekends and the like. It also masks missing data points, which you see as gaps in this plot, rather than linearly interpolating them.

Up to date answer (2018) with Matplotlib 2.1.2, Python 2.7.12

The function equidate_ax handles everything you need for a simple date x-axis with equidistant spacing of data points. Realised with ticker.FuncFormatter based on this example.

from __future__ import division
from matplotlib import pyplot as plt
from matplotlib.ticker import FuncFormatter
import numpy as np
import datetime


def equidate_ax(fig, ax, dates, fmt="%Y-%m-%d", label="Date"):
    """
    Sets all relevant parameters for an equidistant date-x-axis.
    Tick Locators are not affected (set automatically)

    Args:
        fig: pyplot.figure instance
        ax: pyplot.axis instance (target axis)
        dates: iterable of datetime.date or datetime.datetime instances
        fmt: Display format of dates
        label: x-axis label
    Returns:
        None

    """    
    N = len(dates)
    def format_date(index, pos):
        index = np.clip(int(index + 0.5), 0, N - 1)
        return dates[index].strftime(fmt)
    ax.xaxis.set_major_formatter(FuncFormatter(format_date))
    ax.set_xlabel(label)
    fig.autofmt_xdate()


#
# Some test data (with python dates)
#
dates = [datetime.datetime(year, month, day) for year, month, day in [
    (2018,2,1), (2018,2,2), (2018,2,5), (2018,2,6), (2018,2,7), (2018,2,28)
]]
y = np.arange(6)


# Create plots. Left plot is default with a gap
fig, [ax1, ax2] = plt.subplots(1, 2)
ax1.plot(dates, y, 'o-')
ax1.set_title("Default")
ax1.set_xlabel("Date")


# Right plot will show equidistant series
# x-axis must be the indices of your dates-list
x = np.arange(len(dates))
ax2.plot(x, y, 'o-')
ax2.set_title("Equidistant Placement")
equidate_ax(fig, ax2, dates)