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medalla-viz

Visualizations using data from the Medalla Eth2 testnet

https://github.com/clabornd/medalla-viz

Science Score: 18.0%

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    CITATION.cff file
    Found CITATION.cff file
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    codemeta.json file
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    .zenodo.json file
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    DOI references
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    Scientific vocabulary similarity
    Low similarity (5.1%) to scientific vocabulary
Last synced: 10 months ago · JSON representation ·

Repository

Visualizations using data from the Medalla Eth2 testnet

Basic Info
  • Host: GitHub
  • Owner: clabornd
  • Language: HTML
  • Default Branch: master
  • Size: 3.8 MB
Statistics
  • Stars: 0
  • Watchers: 2
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 5 years ago · Last pushed over 5 years ago
Metadata Files
Citation

https://github.com/clabornd/medalla-viz/blob/master/ 

# Code for the Medalla data challenge

The Ethereum foundation help a competition to visualize data surrounding the Medalla test net.  At the time, I was interested in crypto and wanted to participate in something for the purposes of learning.  This code was used to create the rpubs page here:  https://rpubs.com/clabornd/676930.  This turned out to be good enough for a reward :).  The original competition details are here:  https://blog.ethereum.org/2020/11/17/medalla-data-challenge-results

Unfortunately, it is probably nontrivial to recreate the plots in these notebooks, as the data comes this tool from https://github.com/wealdtech/chaind, which requires you to run an ethereum-2 node.  However if you can get that working then maybe everything is gravy.

I'm now a very skeptical observer of the crypto space, especially after the 2021-2022 madness, however this was still a fun learning experience.

Owner

  • Name: Daniel Claborne
  • Login: clabornd
  • Kind: user

Data scientist at Pacific Northwest National Laboratory. Stats, Machine Learning, Shiny.

Citation (citations.bib) 

@Manual{reticulate,
    title = {reticulate: Interface to 'Python'},
    author = {Kevin Ushey and JJ Allaire and Yuan Tang},
    year = {2020},
    note = {R package version 1.16},
    url = {https://CRAN.R-project.org/package=reticulate},
  }
  
@Manual{rmarkdown,
    title = {R Markdown: The Definitive Guide. Chapman and Hall},
    author = {Yihui Xie and J.J. Allaire and Garrett Grolemund},
    year = {2018},
    url = {https://bookdown.org/yihui/rmarkdown},
}

@online{plotly, 
	author = {Plotly Technologies Inc.}, 
	title = {Collaborative data science}, 
	publisher = {Plotly Technologies Inc.}, 
	address = {Montreal, QC}, 
	year = {2015}, 
	url = {https://plot.ly} 
}

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Dependencies

requirements.txt pypi
  • DT ==0.16
  • dplyr ==1.0.2
  • knitr ==1.30
  • numpy ==1.19.2
  • pandas ==1.1.2
  • plotly ==4.10.0
  • pyspark ==3.0.1
  • reticulate ==1.16
  • rmarkdown ==2.4
  • shiny ==1.5.0