"All-column" vis when only few columns in dataframe #199

[caitlynachen]

Overview

Current-vis: "All-column" vis when only few columns in dataframe #199

Changes

If dataframe has only 2 or 3 columns, use current_vis to show an all-column visualization

Example Output

[codecov]

Codecov Report

Merging #336 (1b7cf75) into master (084cf77) will increase coverage by 0.04%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##           master     #336      +/-   ##
==========================================
+ Coverage   84.39%   84.44%   +0.04%     
==========================================
  Files          51       51              
  Lines        3891     3902      +11     
==========================================
+ Hits         3284     3295      +11     
  Misses        607      607              

Impacted Files	Coverage Δ
lux/action/enhance.py	100.00% <ø> (ø)
lux/action/filter.py	91.66% <100.00%> (ø)
lux/core/frame.py	81.50% <100.00%> (+0.47%)	⬆️
lux/vis/Vis.py	75.59% <100.00%> (+0.14%)	⬆️
lux/vislib/matplotlib/ScatterChart.py	76.47% <100.00%> (ø)

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[dorisjlee]

Hi @caitlynachen, Thanks for the PR! The all-column visualization looks much better than the recommendations that we had before! This is especially true when we filter to only 2 or 3 columns in a dataframe. Here are some examples of this:

I was playing around with this feature and had a couple of suggestions on what we can do to improve this:

• We might want to modify the text under the Current Visualization and title Current Visualization to say that the visualization is not based on the current intent, but based on all the columns in the current dataframe (Dataframe Visualization:based on all columns in the dataframe, with the text on "all columns" highlightable showing the columns involved.)

• What happens when there is an intent set and there is an actual Current Visualization, in this case, do we hide the all-column vis? or show it as a separate tab?
  

• You might want to look into some of the failing tests, which is related to calling the print displays

[jinimukh]

Great idea! Maybe we can extend this feature to the entire dataframe and set a global config like small_dataframe_ok or show_all_data_columns depending on the use-case you were thinking of!