The Next Level of Data Visualization in Python
The sunk-cost fallacy is one of many harmful cognitive biases to which humans fall prey. It refers to our tendency to continue to devote time and resources to a lost cause because we have already…
How to Use Excel: 18 Simple Excel Tips, Tricks, and Shortcuts
Learn about why you might want to use Excel to organize your data and 18 simple formulas, functions, shortcuts, and tips you can use to master the software.
Introduction to Matplotlib in Python
This is a great book to use as a starting point if you are new to data visualization — Storytelling with Data Python is a programming language that lets you work more quickly and integrate your…
7 Interactive Bioinformatics Plots made in Python and R
Plotly serves a large bioinformatics and biostats research community. These users leverage the uniquely interactive features of plotly charts for dendrograms,
Supervised vs Unsupervised Learning: algorithms, example, difference
The difference between supervised and unsupervised learning - explained. Supervised learning algorithms: list, definition, examples, advantages, and disadvantages. Unsupervised learning algorithms: list, definition, examples, pros, and cons. Unsupervised vs supervised learning comparison chart in PDF.
Data exploration with alluvial plots - An introduction to easyalluvial
Introduction easyalluvial Features Install Wide Format Sample data alluvial_wide() Long Format Sample Data alluvial_long() General Missing Data Colors Connect Flows to observations in original data ggplot2 manipulations Introduction Alluvial plots are a form of sankey diagrams that are a great tool for exploring categorical data. They group categorical data into flows that can easily be traced in the diagram.