Q:

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

ax.plot_date((dates, dates), (highs, lows), '-')

I'm currently using this command to plot financial highs and lows using Matplotlib. It works great, but how do I remove the blank spaces in the x-axis left by days without market data, such as weekends and holidays?
I have lists of dates, highs, lows, closes and opens. I can't find any examples of creating a graph with an x-axis that show dates but doesn't enforce a constant scale. 

A:

There's an example of how to do this on the Matplotlib site:
https://matplotlib.org/gallery/ticks_and_spines/date_index_formatter.html

A:

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.

A:

I think you need to "artificially synthesize" the exact form of plot you want by using xticks to set the tick labels to the strings representing the dates (of course placing the ticks at equispaced intervals even though the dates you're representing aren't equispaced) and then using a plain plot.

