Science Score: 44.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
  • Academic publication links
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (5.2%) to scientific vocabulary
Last synced: 11 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: justinhblanchard
  • Language: Python
  • Default Branch: main
  • Size: 2.1 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created about 4 years ago · Last pushed almost 4 years ago
Metadata Files
Readme Citation

README.md

ScalabledatalifecycleCOVID-19case_study

Libraries used- pandas, seaborn, numpy, matplotlib.pyplot, sklearn.decomposition, and sklearn.preprocessing.
Test link- https://data.cdc.gov/api/views/muzy-jte6/rows.csv?accessType=DOWNLOAD

Excess- A directory containing a variety of tools (some not fully implemented) that are not in the workflow.

parse.py- The first program to run, it inputs the path to a .csv file and outputs many .csv files, which are renamed to .csv except one named parsed.csv. This program preprocesses the data and split the data into seperate files based on location.
Uses sys and pandas.

heat_pair.py- Runs after parse.py, it inputs the path to a .csv file and outputs a .png plot. This program creates the heatmap and pairplot biplot.
Uses sys, numpy, pandas, seaborn, and matplotlib.pyplot.

standardize.py- Runs after parse.py, it inputs the path to a .csv file and outputs a .csv file named standardized. This program standardizes the data for use for pcagraph.py.
Uses sys, pandas, and sklearn.preprocessing.

pca_graph.py- Runs after standardize.py, it inputs the path to a .csv file and outputs a .png.plot. This program creates the PCA plot and with the weight vectors plotted atop.
Uses sys, numpy, pandas, seaborn, matplotlib.pyplot, and sklearn.decomposition.

Citation (CITATION.cff)

message: "If you use this software, please cite it as below."
authors:
  - family-names: Blanchard
    given-names: Justin
    orcid: 0000-0003-4942-7913
title: "Scalable HPC Workflow and Tools for Data Analysis"
doi: ""
date-released: 

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Dependencies

required.txt pypi
  • matplotlib.pyplot *
  • numpy *
  • os *
  • pandas *
  • seaborn *
  • sklearn.decomposition *
  • sklearn.preprocessing *
  • sys *
  • wget *