course
/
r4ds
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Reduce contents of programming intro

This commit is contained in:
Hadley Wickham 2023-01-24 09:46:19 -06:00
parent c9d9426f67
commit 69d813e56b
1 changed files with 6 additions and 27 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

33
program.qmd
View File

@ -14,8 +14,7 @@ Programming is a cross-cutting skill needed for all data science work: you must
#| echo: false
#| out.width: ~
#| fig-cap: >
#| Programming is the water in which all other components of the data
#| science process swims.
#| Programming is the water in which all the other components swim.
#| fig-alt: >
#| Our model of the data science process with program (import, tidy,
#| transform, visualize, model, and communicate, i.e. everything)
@ -33,14 +32,6 @@ Writing clear code is important so that others (like future-you) can understand
That means getting better at programming also involves getting better at communicating.
Over time, you want your code to become not just easier to write, but easier for others to read.
Writing code is similar in many ways to writing prose.
One parallel which we find particularly useful is that in both cases rewriting is the key to clarity.
The first expression of your ideas is unlikely to be particularly clear, and you may need to rewrite multiple times.
After solving a data analysis challenge, it's often worth looking at your code and thinking about whether or not it's obvious what you've done.
If you spend a little time rewriting your code while the ideas are fresh, you can save a lot of time later trying to recreate what your code did.
But this doesn't mean you should rewrite every function: you need to balance what you need to achieve now with saving time in the long run.
(But the more you rewrite your functions the more likely your first attempt will be clear.)
In the following three chapters, you'll learn skills to improve your programming skills:
1. Copy-and-paste is a powerful tool, but you should avoid doing it more than twice.
@ -53,21 +44,9 @@ In the following three chapters, you'll learn skills to improve your programming
3. As you read more code written by others, you'll see more code that doesn't use the tidyverse.
In @sec-base-r, you'll learn some of the most important base R functions that you'll see in the wild.
These functions tend to be designed to use individual vectors, rather than data frames, often making them a good fit for your programming needs.
The goal of these chapters is to teach you the minimum about programming that you need to practice data science.
Once you have mastered the material in this book, we strongly believe you should continue to invest in your programming skills.
Learning more about programming is a long-term investment: it won't pay off immediately, but in the long term it will allow you to solve new problems more quickly, and let you reuse your insights from previous problems in new scenarios.
To learn more you need to study R as a programming language, not just an interactive environment for data science.
We have written two books that will help you do so:
- [*Hands on Programming with R*](https://rstudio-education.github.io/hopr/), by Garrett Grolemund.
This is an introduction to R as a programming language and is a great place to start if R is your first programming language.
It covers similar material to these chapters, but with a different style and different motivation examples (based in the casino).
It's a useful complement if you find that these four chapters go by too quickly.
- [*Advanced R*](https://adv-r.hadley.nz/) by Hadley Wickham.
This dives into the details of R the programming language.
This is a great place to start if you have existing programming experience.
It's also a great next step once you've internalized the ideas in these chapters.
The goal of these chapters is to teach you the minimum about programming that you need for data science.
Once you have mastered the material here, we strongly recommend that you continue to invest in your programming skills.
We've written two books that you might find helpful.
[*Hands on Programming with R*](https://rstudio-education.github.io/hopr/), by Garrett Grolemund, is an introduction to R as a programming language and is a great place to start if R is your first programming language.
[*Advanced R*](https://adv-r.hadley.nz/) by Hadley Wickham dives into the details of R the programming language; it's great place to start if you have existing programming experience and great next step once you've internalized the ideas in these chapters.