Data science

Stage 1 · Lesson 1 of 7

Notebooks and a clean environment

R for data: the tidyverse

work in notebooks: documents where code, output, charts and notes sit together and run one cell at a time. and Google Colab are the Python choices; with Quarto is the R one. Alongside the notebook, set up a project environment, a folder with its own list of package versions, so the analysis runs the same on another computer.

In Python that is a with a requirements file; in R it is renv with its . Keep every project in its own Git repository from day one.

Common traprunning cells out of order for weeks until the notebook only works in your open session: restart and run everything from the top before you trust or share a result.

A question to check yourself, an AI practice session and 2 cheat sheet entries come with the full roadmap. Unlock

Resources for this stage

Start with

  • BookFree
    R for Data Science (2e)

    Wickham, Çetinkaya-Rundel, Grolemund · Beginner

    Free online: the Whole game and Transform chapters teach the tidyverse verbs in the order you need them

Practise

  • Pick one dataset on a topic you care about and repeat every operation in this stage on it

Keep handy

  • Set up projects, the console and Quarto documents properly before you start

Mark this stage as not done?