EFAshiny
EFAshiny: An User-Friendly Shiny Application for Exploratory Factor Analysis - Published in JOSS (2018)
pygwalker
PyGWalker: Turn your dataframe into an interactive UI for visual analysis
GeneTonic
Enjoy your transcriptomic data and analysis responsibly - like sipping a cocktail
ydata-profiling
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
pheno-ranker-ui
The web ui (R-Shiny application) for Pheno-Ranker, a tool designed for performing semantic similarity analysis on phenotypic data structured in JSON format, such as Beacon v2 Models or Phenopackets v2
https://github.com/abhayspawar/featexp
Feature exploration for supervised learning
https://github.com/copyleftdev/x12-edi-tools
A comprehensive set of tools for working with X12 EDI files
explore
R package that makes basic data exploration radically simple (interactive data exploration, reproducible data science)
https://github.com/SimonBlanke/search-data-explorer
Visualize search-data from your gradient-free-optimization run.
https://github.com/cnag-biomedical-informatics/pheno-ranker
Pheno-Ranker is a tool for comparing phenotypic data structured in JSON/YAML format, such as Beacon v2 Models or Phenopackets v2, as well as CSV.
https://github.com/nagapv/edexplore
A simple widget for interactive EDA / QA. Works on top of Pandas [in Jupyter Notebook] using IPyWidgets with a sprinkle of Regex.
https://github.com/desbordante/desbordante-core
Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.
https://github.com/brains-on-code/codersmuse
CodersMUSE is a prototype implementation to explore multi-modal data of program-comprehension experiments.
rath
Next generation of automated data exploratory analysis and visualization platform.