A simple, step-by-step guide to setting up an .Rprofile file to automatically load your data and customize your R environment.
Discover how to elevate your research presentations with these essential R plot exporting techniques.
Exploratory data analysis (EDA) is a crucial step in the analytical process, offering a profound understanding of our data and revealing hidden insights.
A short description of the post.
I love exploring the data as soon as I import. In this post, I describe some basics of exploratory analyses and graphs which reveal a lot about your data.
A friend of mine wanted to quickly write a loop in R. Here is how to approach it
I had to generate a random numbers list of n=100. This is how I achieved it in R.
You have > 1 excel sheet with same variable names and you want to merge them to 1 dataframe. Here is what you do!
Before and After Changes with Dumbbells.
We learn to override R's intuitiveness when it is not helpful as it arranges the bars by itself.
Approaching grouped scatterplots one step at a time.
How to create variables using the function `case_when`?
Let us see how to draw boxplots with individual data points depicted on them.
A detailed walkthrough of drawing density plots.
A beginner-friendly table making in R: Create the demographics table 1 and export to word document
Adding sample sizes to your ggplot.
Learn to draw histograms by three beginner-friendly ways.
Let's learn to start projects in RStudio - an important step to a good workflow in R.
Moving from working in the console to working from the R script.
As we import the data, there are some immediate steps to follow for a good workflow.
As a beginner in R, importing data is the first step to master before exploring the data viz and analyses. This blogpost takes a step-by-step approach to import your data into RStudio.
Recently I completed a 30 days writing challenge wherein I wrote 30 atomic essays for 30 continuous days. This is an atomic essay I wrote on R - This would serve as a warm welcome to my blog.