data_analysis
Various scripts, mostly Python and R, that have helped me make data management and analysis much more bearable.
Science Score: 44.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (10.4%) to scientific vocabulary
Repository
Various scripts, mostly Python and R, that have helped me make data management and analysis much more bearable.
Basic Info
- Host: GitHub
- Owner: rowanterra
- Language: Jupyter Notebook
- Default Branch: main
- Size: 231 KB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Data_Analysis
Various scripts, mostly Python and R, that have helped me make data management and analysis much more bearable.
Current Uploads
- Line Graph with Double Y Axes
- General Stats and Math Functions
Planned Uploads
- Generic Heatmaps
- PCA and PCoA
- Plotly Heatmaps with Dropdown Menues for Filtering Samples and Applying Different Math
Citations
Please cite this repository if you utilize any code from it with the most updated citaiton file format. It is easily accessed on the righthand side of the repository. As of 2/2024, the citaiton is: - Terra, R. (2024). Diverse Data Visualization Software (Version 1.1.0) [Computer software]. https://github.com/rowanterra/Data_Analysis
Not Python savvy?
Some prerequisites to using these files includes knowing how to pip install packages, use jupyter notebook (suggested), and terminal. Ideally you will know basic Python grammar before using these. If you are starting from scratch, when looking at Python scripts in Jupyter Notebook the naming of DFs, the files you call in, and numbers in green are super easily changed without messing up display. Numbers in green tend to be just altering things like scales, tick spacing, subplot setups, etc.
Not R savvy?
Some prerequisites to using R files includes having R or R Studio (preffered) installed. R is pretty similar to Python, though one big note is that R starts array indexing at 1 which is important to note if using various scripts I upload here. Using Jupyter for R is more difficult as well, so I highly suggest coding directly in R Studio. I find the R studio to be less "clean" when debugging and re-running, so keep good notes as you work!
Data Disclaimer
All test files are fake data. Real data will be uploaded as papers are published.
Owner
- Name: Rowan Terra
- Login: rowanterra
- Kind: user
- Repositories: 1
- Profile: https://github.com/rowanterra
PhD student researching biogeochemical phenomena by day, professional cat cuddler by night.
Citation (CITATION.cff)
cff-version: 1.1.0
message: "If you use any component of the software in this repository, please cite it as below."
authors:
- family-names: Terra
given-names: Rowan
orcid: https://orcid.org/0009-0001-3890-705X
title: "Diverse Data Visualization Software"
version: 1.1.0
date-released: 2024-02-09
url: "https://github.com/rowanterra/Data_Analysis"