Discover versatile methods to convert multiple columns to numeric in R. From base R’s simplicity to dplyr’s efficiency, learn essential techniques. Enhance your data manipulation skills and tackle real-world challenges with confidence. Dive into this comprehensive guide and elevate your R programming expertise.
Programming related posts
In this category you will find posts that are related to programming and should be interesting for psychologists, cognitive scientists, and neuroscientists. Well, almost every researcher would probably find some of the information useful at some time!
Every research psychologist, cognitive scientist, and neuroscientist, should know how to program.. Knowing how to program and write scripts will make many of a researchers everyday tasks much easier. For instance, instead of going through line after line of raw data you can write a Python script that runs through each cell in each column. Furthermore, you get the possibility to use more advanced, and cutting edge, statistical techniques by using R statistical programming environment.
Another example might be to create experiments using PsychoPy (either by coding using Python or using the drag-and-drop interface) and the cheap and open-source Arduino microcontroller. Also, coding is fun and relaxing!
Discover how to filter data in R using the %in% operator’s counterpart, ! (NOT) with filter(). This powerful technique allows you to exclude specific values from your dataset, providing fine-grained control over your data filtering process. Streamline your data manipulation with this essential skill. Explore more in our comprehensive guide.
Introduction Running R in Jupyter Notebook allows users to harness the power and simplicity of notebooks for their data analysis and research tasks. This post will explore the benefits and capabilities of using R in Jupyter Notebook. Firstly, let’s briefly introduce the concept of a notebook. A notebook is an interactive document that combines code, …
Discover the key to data manipulation in R by learning how to check and manage variable types. Uncover the nuances of data types and elevate your data analysis expertise with the comprehensive insights provided in this post. Get ready to enhance your data-handling skills and drive more precise analyses!