# Some other useful books and guides:

## R Data Science Books:
- [R For Data Science 2e](https://r4ds.hadley.nz/)
- [Data Science in a Box](https://datasciencebox.org/01-overview)
- [R Markdown: The Definitive Guide](https://bookdown.org/yihui/rmarkdown/)
- [R Graphics Cookbook, 2nd edition](https://r-graphics.org/)

## Python Data Science Books:
- [Intro to Cultural Analytics and Python](https://melaniewalsh.github.io/Intro-Cultural-Analytics/welcome.html)
- [The Hitchhiker's Guide to Python](https://docs.python-guide.org/)
- (https://pysd-cookbook.readthedocs.io/en/latest/index.html)

## Reproducible Research:
- [Anna Krystalli, Putting the into Reproducible Research: Directors Cut](https://annakrystalli.me/talks/r-in-repro-research-dc.html)

# Web tools for data scientists:
- ["i want hue: colors for data scientists"](https://medialab.github.io/iwanthue/)
