Charty (RubyGrant 2018)

Charty (RubyGrant 2018) - RubyKaigi 2019 RubyData WorkShop

Transcript

1. Charty (RubyGrant 2018)
   RubyKaigi 2019
   Kazuma Furuhashi ඵ଎@284km
   

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2. Ruby Association Grant 2018
   • 12/1 => Development
   
   • 1/11 => Intermediate Report
   
   • 3/11 => Final Report
   
   • https://www.ruby.or.jp/en/news/20181106
   

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3. Charty
   

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4. What is Charty
   • Charty is an open-source Ruby library for visualizing your data in a simple
   way.
   
   • https://github.com/red-data-tools/charty
   

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5. red-data-tools/charty
   • In Charty, you need to write very few lines of code for representing what
   you want to do.
   
   • It lets you focus on your analysis of data, instead of plotting.
   
   • i.e. We aim at convenience.
   

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6. Characteristics of charty
   • Charty has two abstraction layers
   
   • Data Abstraction Layer
   
   • Plotting Abstraction Layer
   

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8. Abstraction Layer
   We can do what you want in a
   combination of different
   languages, data structures, and
   libraries.
   

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9. Data Abstraction Layer
   • Daru::DataFrame
   
   • Numo::NArray
   
   • NMatrix
   
   • ActiveRecord
   

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10. Plotting Abstraction Layer
    • Matplotlib
    
    • Gruff
    
    • rubyplot
    
    • chart.js (Experimental implementation) demo later
    
    • 284km/benchmark_driver-output-charty
    

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11. 284km/benchmark_driver-output-charty
    $ be benchmark-driver examples/parse.yaml -o charty
    

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12. Demo
    

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13. Activeecord x Chart.js
    

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14. Reference:
    • holoviews (Python)
    
    • Gadfly.jl (Julia)
    
    • ggplot2 (R)
    
    • Julia Package GR (GR Framework)
    
    • Python Package GR (GR Framework)
    
    • Codes to use via PyCall Library (matplotlib.rb, matplotlib, pyplot ͱ͔)
    
    • and so on ……
    

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15. Future Plans
    • Data Abstraction Layer
    
    • Support Red::Arrow
    
    • Improve benchmark_driver-output-charty
    
    • Plotting Abstraction Layer
    
    • Add type of graph that can be output
    
    • Horizontal bar with Gruff
    
    • Support bokeh ? maybe.
    
    • Use in business
    

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16. Red Data Tools
    • https://red-data-tools.github.io/
    
    • 5/14 (Ր) 19:00 - 21:30
    
    • Code Party: Today 19:00 - 21:00
    
    • After Hack: Sun. 10:30 - 17:30
    
    • Develop together !!
    

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17. Red Data Tools
    

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18. Enjoy !! :)
    

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