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R for Data Science 2nd Edition has just been released! This new edition is a major rework of the original, offering:

1.) New "Whole Game" section providing a rough sketch of core data science elements.

2.) Expanded and detailed chapters on data transformation and tidying.
An enhanced "Visualize" section.

3.) The newly added "Import" and "Transform" sections that dive into various data formats and transformation techniques.

4.) A redefined "Program" part focusing on function writing and iteration.
The "Communicate" section now featuring Quarto, the tool of the future.

Interestingly, the modeling section has been removed, acknowledging that there are more comprehensive resources available elsewhere, such as the tidymodels packages and "Tidy Modeling with R" by Max Kuhn and Julia Silge.

You can get your hands on a physical copy using the link below with the free version being available at r4ds.hadley.nz!


https://lnkd.in/g7Gq_PPF

R for Data Science: Import, Tidy, Transform, Visualize, and Model Data R for Data Science: Import, Tidy, Transform, Visualize, and Model Data

📢 Exciting Updates in the World of R Programming! 🚀

Attention R enthusiasts! We have some game-changing updates to share with you about the Tidyverse, the ultimate toolkit for data science in R. Let's dive in and explore the latest advancements that will enhance your data manipulation and analysis skills:

1️⃣ Introducing the versatile vctrs package: It revolutionizes how you handle different data structures, offering a streamlined way to merge data frames and lists in your R scripts. Say goodbye to traditional bind_rows() and embrace the power of vec_rbind()!

2️⃣ Say hello to the new and improved glue syntax in dplyr: This syntax brings more readability and flexibility to your code, making string manipulation tasks a breeze during data wrangling. It's time to make your code cleaner and more elegant.

3️⃣ Piping made easier with R 4.1.0: The native pipe operator, '|>', introduced in R 4.1.0, offers a simpler way to chain operations in your R code. While it doesn't replicate all the features of '%>%' from the magrittr package, it streamlines your workflow for a smoother coding experience.

Ready to harness the powers of these updates and level up your R skills? At R-Tutoring Academy, our expert tutors are here to guide you every step of the way. Join our comprehensive R programming courses and gain hands-on experience with these cutting-edge tools.

Stay ahead in the ever-evolving world of data science. Let's embrace the power of Tidyverse together! Drop a comment below if you're excited about these updates or want to learn more.

If you're looking for tutoring in the R programming language, be sure to check us out using the link below!

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