This week, Ellis Hughes and I begin a new series on RMarkdown. We will be going over the functionality of RMarkdown files and how you can quickly and easily build reports.
This first episode covers some of the basics of RMarkdown files:
To watch our screen cast, CLICK HERE.
To access our code, CLICK HERE.
This week, Ellis Hughes and I delve into our mailbag to answer a question posed to us inquiring how we would go about creating tables for research publication in R. Most of the time it seems that people will get their model outputs and transpose them into Excel to build a table. But, in R you can go directly from the model output straight to a nice table that meets that journal’s requirements.
In this episode, we build a regression model and use {broom} to tidy the model outputs into a clean data frame. When then take that output and walk through different ways of using {gt} to customize your table for publication. We wrap up by covering how to build a plot of the interquartile range and annotate that plot to provide more context using {ggplot2}.
To watch our screen cast, CLICK HERE.
To access our code, CLICK HERE.
We recently completed a 10 episode series on the Tidy Explained screen cast about building models within the {tidymodels} framework of R.
To tie it the series together I put together an RMarkdown file that walks through the model fitting process in {tidymodels}. The RMarkdown template provides a step-by-step process that one can take when building {tidymodels} on their own data.
If you knit the RMarkdown template, you will get an html report that covers the basics of:
To access the template, go to my GITHUB page.
Below are the 10 {tidymodels} episodes we did on Tidy Explained if you’d like to see the processes performed in real time:
TidyX 77: Intro to tidymodels
TidyX 78: Splits & Recipes
TidyX 79: Cross-Validation & Model Metrics
TidyX 80: Tuning Decision Trees
TidyX 81: Logistic Regression
TidyX 82: Random Forest Classifier
TidyX 83: Naive Bayes Classifier
TidyX 84: Workflowsets
TidyX 85: Workflowsets & Parameter Tuning
TIdyX 86: Tidymodels interview with Julia Silge
Continuing from last week, Ellis Hughes and I step through a solution for Advent of Code Day 7. This week’s code puzzle has us trying to solve a method for finding a minimum value in a string of numbers created by some simple mathematical operations.
The task requires us to use some for() loops and build a lookup table for identifying values.
To watch our screen cast, CLICK HERE.
To access our code, CLICK HERE.
This week, Ellis Hughes and I decide to try our hand at some of the coding challenges put on by the annual Advent of Code event.
For those that don’t know, Advent of Code is a fun, holiday event, where the founder, Eric Wastl, creates 25 straight days of puzzles and brain teasers to be solved via code. The event is coding language agnostic (some use R, some use Python, some use other languages) and is a lot of fun. If you search on Twitter you will find a large number of people sharing solutions and ideas.
This week, we go over code to solve the Day 6 puzzle about laternfish.
To watch our screen cast, CLICK HERE.
To access our code, CLICK HERE.