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stemgraphic

Overview

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 (no size limit, graphical tool). It also supports categorical and text as input.

A typical stem_graphic output:

stem_graphic example

For an in depth look at the algorithms and the design of stemgraphic, see

Stemgraphic: A Stem-and-Leaf Plot for the Age of Big Data

Documentation is available as pdf stemgraphic.pdf and online html.

The official website of stemgraphic is: http://stemgraphic.org

Installation

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 setup.py install

Latest changes

Version 0.6.2

  • Bugfix for VERSION

Version 0.6.1

  • back-to-back stem-and-leaf plots can use predefined axes (secondary ax added)
  • added quantize function (basically a round trip number->stem-and-leaf->number))
  • density_plot added for numerical values with stem-and-leaf quantization and sampling
  • density_plot also support multiple secondary plots like box, violin, rug, strip
  • notebook demoing density_plot
  • notebook demoing comparison of violin, box and stem-and-leaf for certain distributions

Version 0.6.0

Version bump to 0.6 due to order of params changing. Shouldn't affect using named args

Major code change and expansion for num.stem_graphic including:

  • back-to-back stem-and-leaf plots
  • allows comparison of very skewed data
  • bug fix (rounding issue) due to python precision
  • better stem handling
  • alpha down to 10% for bars
  • median alpha can be specified
  • stems can be hidden
  • added title option, besides the legend

Other changes:

  • More notebook examples
  • added leaf_skip, stem_skip to a few functions missing them
  • heatmap_grid bugfix
  • added reverse to a few functions missing it
  • improved documentation
  • matrix_difference ord param added added
  • ngram_data now properly defaults to case insensitive
  • switched magenta to 'C4' - compatible with mpl styles now
  • functions to read/write .npy and .pkl files
  • more unicode typographical glyphs added to the list of non alpha

Version 0.5.3

  • scatter 3d support
  • added 3rd source to compare (in 3d) with scatter plots
  • more scatter plot fixes
  • some warnings added to deal with 3d and log scale issues
  • added fig_xy to scatter - useful to quickly adjust figsize in a notebook
  • added normalize, percentage and whole (integer) to scatter
  • added alpha to scatter

Version 0.5.2

  • added documentation for scatter plots
  • added jitter to scatter plots
  • added log scale to scatter plots
  • more notebooks

Version 0.5.1

  • stem_text legend fix
  • missed adding the code for scatter plots
  • more notebooks

Version 0.5.0

Major new release.

  • All 0.4.0 private changes were merged
  • new module stemgraphic.alpha:
    • n-gram support
    • stem_graphic supporting categorical
    • stem_graphic supporting text
    • stem_text supporting categorical
    • stem_text supporting text
    • stem command line supporting categorical when column specified
    • heatmap for n-grams
    • heatmap grid to compare multiple text sources
    • Frobenius norm on diff matrices
    • radar plot with Levenshtein distance
    • frequency plot (bar, barh, hist, area, pie)
    • sunburst char
    • interactive charts with cufflinks
  • new module stemgraphic.num to match .alpha
  • stop word dictionaries for English, Spanish and French
  • Massively improved documentation of modules and functions
  • Improved HTML documentation
  • Improved PDF documentation

Version 0.4.0

Internal release for customer.

  • Added Heatmap

  • Basic PDF documentation

  • Quickstart notebook

Version 0.3.7

Matploblib 2.0 compatibility

Version 0.3.6

  • 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.

TODO

  • 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.
  • add unit tests
  • add feather, hdf5 etc support, particularly on sample persistence
  • more charts
  • more examples