gsoc

GSOC NOTES:

Use the unit framework to convert the data into categorical numbers Enhance the unit framework to be more dynamic

Categorical ToDo

Close out PR:

1. update axis_unit & rerender - can't change original order

• convert unit_data to an object
• formatters need references (not copies) to seqs and locs

ax.plot(['a','b'])
ax.plot(['a', 'b', 'c'])
ax.plot(['b', 'c', 'd'])

2. make image tests

Other

1. categorical colors:

• cmap/norm that does 1-1 mapping (like when plotting satellite missing value codes...)
• categorical colormap that goes {category=color....} (dictColormap...)
• set axis properties to get good label mapping

2. sorted categories

3. hierarchical categories

4. mouseover report label by snapping to nearest one

5. Clean up docs and write examples following code guide, can use blog posts as basis,

6. scales: data mapped to visual properties: x, y (color, shape) (altair introduces this)

• scales: map data to visual properties
• guides: axes and legends
• marks: visual elements

Other

• matplotlib simple plots tutorials: line, scatter, bar, pie, heatmap
• Py3.5 dict support in numpy
• Enum (convertor)
• Support for pd.series category (look at support for regular series type) - this is a PR to Pandas
• kwargs as cycler: https://github.com/pydata/pandas/pull/12547
• labels only exist after rendering (fig.canvas.draw(), plt.draw(), plt.show())

misc notes:

build: export MPLLOCALFREETYPE=1 (& update docs)

Python Framework Bug: pythonw -m "nose" test_categorical.py