Improve sentences (#1279)

It slightly improves sentences and fixes some typos.
This commit is contained in:
Zeki Akyol 2023-02-13 22:29:46 +03:00 committed by GitHub
parent b0a395b477
commit 61a4ce719d
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
6 changed files with 8 additions and 8 deletions

View File

@ -502,7 +502,7 @@ We'll use `tibble()` and `tribble()` later in the book to construct small exampl
In this chapter, you've learned how to load CSV files with `read_csv()` and to do your own data entry with `tibble()` and `tribble()`.
You've learned how csv files work, some of the problems you might encounter, and how to overcome them.
We'll come to data import a few times in this book: @sec-import-spreadsheets from Excel and googlesheets, @sec-import-databases will show you how to load data from databases, @sec-arrow from parquet files, @sec-rectangling from JSON, and @sec-scraping from websites.
We'll come to data import a few times in this book: @sec-import-spreadsheets from Excel and Google Sheets, @sec-import-databases will show you how to load data from databases, @sec-arrow from parquet files, @sec-rectangling from JSON, and @sec-scraping from websites.
Now that you're writing a substantial amount of R code, it's time to learn more about organizing your code into files and directories.
In the next chapter, you'll learn all about the advantages of scripts and projects, and some of the many tools that they provide to make your life easier.

View File

@ -397,7 +397,7 @@ household
```
This dataset contains data about five families, with the names and dates of birth of up to two children.
The new challenge in this dataset is that the column names contain the names of two variables (`dob`, `name)` and the values of another (`child,` with values 1 and 2).
The new challenge in this dataset is that the column names contain the names of two variables (`dob`, `name)` and the values of another (`child,` with values 1 or 2).
To solve this problem we again need to supply a vector to `names_to` but this time we use the special `".value"` sentinel.
This overrides the usual `values_to` argument to use the first component of the pivoted column name as a variable name in the output.

View File

@ -278,7 +278,7 @@ flights |>
The `.` is a sign that `.before` is an argument to the function, not the name of a new variable.
You can also use `.after` to add after a variable, and in both `.before` and `.after` you can use the variable name instead of a position.
For example, we could add the new variables after `day:`
For example, we could add the new variables after `day`:
```{r}
flights |>
@ -307,7 +307,7 @@ flights |>
It's not uncommon to get datasets with hundreds or even thousands of variables.
In this situation, the first challenge is often just focusing on the variables you're interested in.
`select()` allows you to rapidly zoom in on a useful subset using operations based on the names of the variables.
`select()` is not terribly useful with the flights data because we only have 19 variables, but you can still get the general idea of how it works:
`select()` is not terribly useful with the `flights` data because we only have 19 variables, but you can still get the general idea of how it works:
```{r}
# Select columns by name

View File

@ -473,7 +473,7 @@ ggplot(penguins, aes(x = flipper_length_mm, y = body_mass_g)) +
geom_point()
```
In the future, you'll also learn about the pipe which will allow you to create that plot with:
In the future, you'll also learn about the pipe, `|>`, which will allow you to create that plot with:
```{r}
#| eval: false

View File

@ -33,7 +33,7 @@ Each chapter addresses one to a few aspects of creating a data visualization.
### Learning more
The absolute best place to learn more is the ggplot2 book: [*ggplot2: Elegant graphics for data analysis*](https://ggplot2-book.org/).
The absolute best place to learn more is the ggplot2 book: [*ggplot2: Elegant graphics for data analysis (3e)*](https://ggplot2-book.org/).
It goes into much more depth about the underlying theory, and has many more examples of how to combine the individual pieces to solve practical problems.
Another great resource is the ggplot2 extensions gallery <https://exts.ggplot2.tidyverse.org/gallery/>.

View File

@ -62,7 +62,7 @@ Code is miserable to read on a good day, so giveyoureyesabreak and use spaces.
## Comments
R will ignore any text after `#`.
R will ignore any text after `#` for that line.
This allows you to write **comments**, text that is ignored by R but read by other humans.
We'll sometimes include comments in examples explaining what's happening with the code.
@ -133,7 +133,7 @@ Change 2.5 to 3.5 and rerun.
Make yet another assignment:
```{r}
r_rocks <- 2 ^ 3
r_rocks <- 2^3
```
Let's try to inspect it: