# I is for I Want to Learn More

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This could have easily been a post about a function beginning with the letter I. But I wanted to take the opportunity to share some the resources that really helped me learn R as well as I do.**Deeply Trivial**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Obviously, practice and looking things up on stackoverflow and github as I encountered problems was incredibly useful. But those resources gave me many piecemeal solutions. The tidy data paradigm and the tidyverse helped me develop a more unified understanding of how I approached data and data analysis.

So here are my recommended resources for getting into that approach, hopefully earlier in your R journey than me:

*R for Data Science*– you can read the book for free here or purchase your own copy*Text Mining with R*– this book is about mining text with R but really helped me understand the tidy data approach- Variance Explained blog – David Robinson, who cowrote the Text Mining book above, writes many wonderful blog posts about using R and the virtues of learning the tidyverse first
- The tidyverse website
- Also, do check out the rstudio section of github for some cool things R-Studio can do to enhance your R experience

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