matplotlib finance

tacaswell · January 30, 2015, 6:30pm

Boris,

Please direct such questions to the user list in the future (I have included the list on my reply). You may need to join the list to be able to post.

The reason that mpl.finance was deprecated is that none of the current core developers work in finance and hence do not have the domain expertise to maintain the module. We are currently looking for a volunteer to take responsibility for that bit of code.

I have no experience with plotting financial data and am hesitant to speculate about performance, but have gotten 20-30 fps out of mpl on other applications.

Tom

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On Fri Jan 30 2015 at 1:19:47 PM tbad <tbad2009@…287…> wrote:

Hello Thomas,

You write in Github that matplotlib finance is deprecated since matplotlib 1.4. What is instead of it?

Can you please advice on what to use if i want to use matplotlib for charting stocks, volume in different formats like candlesticks, tick charts, bar charts with technical analysis add-ons like moving averages etc.? I want to have charts with intra-day real time streaming with a lot of stocks (i have a data feed provider). Or the only way is to do everything manually?

And will matplotlib be capable of streaming a lot of stocks tick by tick without delays?

Also maybe there are other python packages useful for trading purposes?

Thank you for any answers beforehand,

Best regards,

Boris

Benjamin_Root · January 30, 2015, 10:55pm

To be clear, most of what was in finance.py were convenience functions for parsing through stock data from the yahoo interface, and for plotting. Taking a quick look, perhaps it might make sense to pull out a couple fundamental chart types, but most of the code are just simply convenience wrappers, and largely outdated now.

The problem we are having is that users would file bug reports saying that we were doing a particular chart incorrectly, and none of us had any domain knowledge to know if that was the truth, false, or just a matter of opinion in the field. Matplotlib is also intended to be a general-purpose plotting library. It really shouldn’t be doing much of the data preparatory work. You should just tell it what to plot and let it crank. If that data happened to have used a moving window, it wouldn’t matter if it was an average, median, or what-have-you. Matplotlib is fairly low-level, and works very well that way. For example, there isn’t an “streamed_data_plot()” function. You have to do the streaming yourself and update the plot.

For data wrangling, I would suggest using Pandas. It interfaces quite nicely (mostly) with matplotlib, and it is considered the de facto tool to use for time series statistical analyses. Once the data is mashed into the form you need, then you can plot it however you like.

If you really want to keep finance.py alive, then all we are looking for is someone knowledgable to stand up and take responsibility for it. It is mostly self-contained, so it is even possible to spin it off as its own mpl_toolkit managed separately from matplotlib.

I mean, let’s face it… do you really want your finances managed by a bunch of meteorologists and astrophysicists?

Cheers!
Ben Root

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On Fri, Jan 30, 2015 at 1:30 PM, Thomas Caswell <tcaswell@…287…> wrote: