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 »
When working with data in Python, using Pandas to read JSON from URL is an excellent tool that lets you directly load JSON data from a web source into a Pandas dataframe. This tutorial focuses on the steps to accomplish this task, building upon our previous discussions on reading JSON with Python more generally.
Using Pandas to Read JSON from URL Read More »
Positiv korrelation är ett grundläggande begrepp inom statistik och ofta använt inom kognitionsvetenskapen för att förstå relationer mellan två och fler variabler. I en tidigare post lärde vi oss utföra korrelationsanalys i både R och Excel, vilket är användbart när vi vill undersöka samband. Men vad innebär egentligen att ett samband är positivt, och vad
Positiv Korrelation: Vad Det Betyder och Exempel Read More »
In this volcano plot in R tutorial, we will use ggplot2, a 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 This data visualization tutorial will start by learning the
How to Make a Volcano Plot in R using ggplot2 Read More »
In this post, you will learn how to set up a random intercept model in R. This model is useful for analyzing data from experiments that involve repeated measurements of the same participants or items. It lets you control for variability in the outcome variable due to random effects, such as individual differences or item
Random Intercept Model in R: Interpretation and Visualization Read More »
In this post, we will explore how to utilize the unique function in R, a valuable tool for identifying and removing duplicate values across various data structures. We will start by examining the unique() function to learn how it works. Next, we will examine examples of how to apply it to vectors, matrices, and data frames,
The Unique Function in R: How to Use it in 4 Ways Read More »