📣 Exciting news, everyone! 🌟 Make sure to head over to this weeks blog "What's new in R 4.4.0?" by Russ Hyde, and dive into the world of the latest R release📊🔬💻
Discover some of the amazing new features that this version has to offer! 🔍 🔭 🚀
🌟 Join Pfizer's exclusive webinar covering their journey from SAS to R with Natalia Andriychuk from Pfizer. Discover how they're shaping the future with community-driven development.
Logistic regression is a crucial tool for predicting binary outcomes. In my latest blog post, I walk you through the process of plotting a logistic regression curve in R. It's an essential skill for data scientists, statisticians, and anyone interested in predictive modeling.
If you work with text data in R, the gregexpr() function is essential for pattern matching. It finds all occurrences of a pattern within a string. Key parameters include pattern, text, ignore.case, perl, fixed, and useBytes. You can match characters, ignore case, use advanced regex, and search fixed strings.
The newest version of my #R#package TidyDensity really took off for me. Now wait until the next release which introduces 39 new functions. #R#RStats#RProgramming
🚀 Elevate Your R Programming Skills: Removing Elements from Vectors
Want to level up your R programming game? Let's talk about removing specific elements from vectors! It's a fundamental skill.
But here's the real fun: try it yourself! Experiment with your own data and see which method resonates with you. To get yourself familiar with what's happening, you have to experiment.
Learn how to handle rows in R containing specific strings using base R's grep() and dplyr's filter() with str_detect(). Select or drop rows efficiently and enhance your data manipulation skills. Give it a try with your datasets for better data cleaning and organization.