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Graphic and text stem-and-leaf plots

Project Description



John Tukey’s stem-and-leaf plot first appeared in 1970. Although very useful back then, it cannot handle more than 300 data points and is completely text-based. Stemgraphic is a very easy to use python package providing a solution to these limitations.

A typical stem_graphic output:

stem_graphic example

For an in depth look at


Stemgraphic requires docopt, matplotlib and pandas. Optionally, having Scipy installed will give you secondary plots and Dask (see requirements_dev.txt for all needed to run all the functional tests) will allow for out of core, big data visualization.

Installation is simple:

pip3 install -U stemgraphic

or from this cloned repository, in the package root:

python3 install

Latest changes

Persist sample from command line tool (-k filename.pkl or -k filename.csv).

Windows compatible bat file wrapper (stem.bat).

Added full command line access to dask distributed server (-d, -s, use file in ‘’ when using glob / wildcard).

For operations with dask, performance has been increased by 25% in this latest release, by doing a compute once of min, max and count all at once. Count replaces len(x).

Added the companion PDF as it will be presented at PyData Carolinas 2016.


Plenty… but to start:

  • back to back and scale calculation
  • multivariate support
  • provide support for secondary plots with dask
  • automatic dense layout
  • add a way to provide an alternate function to the sampling
  • support for spark rdds and/or sparkling pandas
  • create a bokeh version. Ideally rbokeh too.
  • interactive version based on the above
  • add unit tests
  • add feather, hdf5 etc support, particularly on sample persistence

Release History

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