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Easy to use Python API wrapper to plot charts with matplotlib, plotly, bokeh and more

License: Apache License 2.0

Python 86.74% Batchfile 0.01% CSS 0.49% JavaScript 6.62% HTML 0.01% Less 6.14%
plotting chart matplotlib bokeh plotly

chartpy's Issues

Headless Offline Plotting fails

Hi! Plotting fails when ran headlessly i.e. without iPython notebook, just the python interpreter due to the iplot function.

E.g. python canvas_demo.py gives

/chartpy/engine.py", line 1449, in plot_chart
    fig = data_frame.iplot(kind=chart_type_ord,
AttributeError: 'DataFrame' object has no attribute 'iplot'

Document comparison with HoloViews and hvPlot

Hi! Chartpy looks to have similar goals as HoloViews and hvPlot, which also provide a unified API for creating Matplotlib, Bokeh, or Plotly plots. It would be great if Chartpy's documentation could include a comparison with these existing libraries so that users will be able to choose the best library for their needs!

Adding more Python chart libraries

I've already got a basic API for using matplotlib, bokeh and plotly. I'm working on adding more plotting features for these. I'd also like to explore adding further Python chart APIs into the wrapper, maybe bqplot, highcharts or vispy for example. Anyone interested in helping to add new libraries, or have any views about what's most useful, adding more libraries or adding more features for the existing ones?

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