R statistical programming related stuff
In this post, we explore how to count rows in R using nrow() for both data.frames and data.tables. We compare the performance of each method using a large dataset and discuss which one is quicker. Discover the speed differences and learn more about counting rows in R!
How to Get Number of Rows in R Using data.table Read More »
Filtering data is a a common step in data analysis. In this post, we explore how to filter in data.table in R, including subsetting by conditions and selecting specific groups. We also show how to save the filtered data as a new data frame for further analysis.
How to Filter in data.table in R Read More »
This post explores summing multiple columns in data.table, including group-wise summation and dynamic column selection with %in%. We also compare this approach with dplyr and base R. Whether you’re working with large datasets or need flexible column selection, these techniques will help you get the job done. Read on to learn more!
How to Sum Multiple Columns in data.table Read More »
Learn how to select columns in data.table using names, character vectors, and indices. This guide covers selecting single and multiple columns, using .SDcols, and indexing. With practical examples, you’ll see how data.table offers a fast and flexible way to manipulate large datasets in R.
How to Select Columns from data.table in R Read More »
This blog post focuses on the practical aspects of conducting mediation analysis in R. First, we will look at how to do it using the mediation package. Then, we will walk through an example of using the Lavaan package to perform mediation analysis. Both mediation examples will include R code chunks with explanations. This blog
Mediation Analysis in R: How to Run it with two Packages Read More »
In this volcano plot in R tutorial, we will use ggplot2, a popular package for creating beautiful and customizable graphics in R. A volcano plot in R is a scatter plot showing the relationship between the fold change and the statistical significance in certain data types. Outline In this data visualization tutorial, we will start
How to Make a Volcano Plot in R using ggplot2 Read More »
A random intercept model in R is useful for analyzing data from experiments that involve repeated measurements of the same participants or items. It allows you to control for the variability in the outcome variable due to random effects, such as individual differences or item difficulty while estimating the fixed effects of your predictors of
Random Intercept Model in R: Interpretation and Visualization Read More »
In this post, we will look at how to use the unique function in R, which is a good tool for identifying and removing duplicate values in different data structures. We will first have a look at what the unique() function is and how it works. Next, we will look at some examples of how
The Unique Function in R: How to Use it in 4 Ways Read More »
Mann whitney u test in R with ggstatsplot
Mann Whitney U Test in R: A Comprehensive Guide Read More »
Sometimes, when we use data frames in R, we need to remove rows with specific values. For example, we might want to exclude rows that have missing values, outliers, or errors. Or we might want to subset our data based on some criteria, such as a range of values, a category, or a pattern. In
R: Remove Rows with Certain Values using dplyr Read More »