Category Archives: Data Science

Posts about data science topics.

Statistics Trivia for Data Scientists

Public health, artificial intelligence, and data science trivia! Fun! Educational! Test your knowledge!

Statistics trivia for data scientists will refresh your memory from the courses you’ve taken – or maybe teach you something new! Visit my blog to find out!

Management Tips for Data Scientists

When working in data science, there are some tips and tricks to managing your communication and relationship with superiors that can help you advance in your career.

Management tips for data scientists can be used by anyone – at work and in your personal life! Get the details in my blog post.

REDCap Mess: How it Got There, and How to Clean it Up

REDCap mess on your hands? The REDCap designers made the application so loosey goosey, you can really program yourself into a messy corner if you don't plan well.

REDCap mess happens often in research shops, and it’s an analysis showstopper! Read my blog post to learn my secret tricks for breaking through the barriers and getting on with data analytics!

GitHub Beginners in Data Science: Here’s an Easy Way to Start!

If you are an aspiring data scientist, you will need to know how GitHub works. You will probably want to use it for your projects.

GitHub beginners – even in data science – often feel intimidated when starting their GitHub accounts and trying to interact with the web page. Don’t be shy! Catch the highlights from a recent GitHub beginners workshop I held!

ETL Pipeline Documentation: Here are my Tips and Tricks!

This blog post shows you how to properly document your extract, transform, and load code.

ETL pipeline documentation is great for team communication as well as data stewardship! Read my blog post to learn my tips and tricks.

Benchmarking Runtime is Different in SAS Compared to Other Programs

How do you measure how long it takes for code to run in different programs? And why would you want to measure something like that? Mainly, the reason to benchmark runtime is so that you can figure out how to optimize your code.

Benchmarking runtime is different in SAS compared to other programs, where you have to request the system time before and after the code you want to time and use variables to do subtraction, as I demonstrate in this blog post.

End-to-End AI Pipelines: Can Academics Be Taught How to Do Them?

What is an end-to-end AI pipeline? And why are academics so bad at making one? These are different ideas we will examine in this blog post.

End-to-end AI pipelines are being created routinely in industry, and one complaint is that academics can only contribute to one component of the pipeline. Really? Read my blog post for an alternative viewpoint!

Referring to Columns in R by Name Rather than Number has Pros and Cons

There are different ways to refer to variables in R dataframes. You can use a field names, and you can also use field numbers.

Referring to columns in R can be done using both number and field name syntax. Although field name syntax is easier to use in programming, my blog demonstrates how you can use column numbers to make automation easier.

The Paste Command in R is Great for Labels on Plots and Reports

The paste command is used to concatenate strings in R. You can use it different ways, which is what I demonstrate in my blog and videos.

The paste command in R is used to concatenate strings. You can leverage the paste command to make refreshable label objects for reports and plots, as I describe in my blog post.

Coloring Plots in R using Hexadecimal Codes Makes Them Fabulous!

You do not need to use the default R colors on your plot. You don't even need to limit yourself to named colors on cheat sheets.

Recoloring plots in R? Want to learn how to use an image to inspire R color palettes you can use in ggplot2 plots? Read my blog post to learn how.

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