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Typos in Vectors chapter (#490)

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Nirmal Patel 2016-10-26 18:59:32 +05:30 committed by Hadley Wickham
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vectors.Rmd
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@ -26,7 +26,7 @@ There are two types of vectors:
1. __Lists__, which are sometimes called recursive vectors because lists can
contain other lists.
The chief difference between atomic vectors is that atomic vectors are __homogeneous__, while lists can be __heterogeneous__. There's one other related object: `NULL`. `NULL` is often used to represent the absence of a vector (as opposed to `NA` which is used to represent the absence of a value in a vector). `NULL` typically behaves like a vector of length 0. Figure \@ref(fig:datatypes) summarises the interrelationships.
The chief difference between atomic vectors and lists is that atomic vectors are __homogeneous__, while lists can be __heterogeneous__. There's one other related object: `NULL`. `NULL` is often used to represent the absence of a vector (as opposed to `NA` which is used to represent the absence of a value in a vector). `NULL` typically behaves like a vector of length 0. Figure \@ref(fig:datatypes) summarises the interrelationships.
```{r datatypes, echo = FALSE, out.width = "50%", fig.cap = "The hierarchy of R's vector types"}
knitr::include_graphics("diagrams/data-structures-overview.png")
@ -99,8 +99,7 @@ The distinction between integers and doubles is not usually important, but there
some numerical tolerance.
1. Integers have one special value: `NA`, while doubles have four:
`NA`, `NaN`, `Inf` and `-Inf`. All three special values can arise in
during division:
`NA`, `NaN`, `Inf` and `-Inf`. All three special values `NaN`, `Inf` and `-Inf` can arise in during division:
```{r}
c(-1, 0, 1) / 0
@ -415,7 +414,7 @@ x_named <- list(a = 1, b = 2, c = 3)
str(x_named)
```
Unlike atomic vectors, `lists()` can contain a mix of objects:
Unlike atomic vectors, `list()` can contain a mix of objects:
```{r}
y <- list("a", 1L, 1.5, TRUE)
@ -458,7 +457,7 @@ There are three principles:
### Subsetting
There are three ways to subset a list, which I'll illustrate with `a`:
There are three ways to subset a list, which I'll illustrate with a list named `a`:
```{r}
a <- list(a = 1:3, b = "a string", c = pi, d = list(-1, -5))
@ -478,8 +477,8 @@ a <- list(a = 1:3, b = "a string", c = pi, d = list(-1, -5))
hierarchy from the list.
```{r}
str(y[[1]])
str(y[[4]])
str(a[[1]])
str(a[[4]])
```
* `$` is a shorthand for extracting named elements of a list. It works
@ -583,7 +582,8 @@ The most important S3 generic is `print()`: it controls how the object is printe
Atomic vectors and lists are the building blocks for other important vector types like factors and dates. I call these __augmented vectors__, because they are vectors with additional __attributes__, including class. Because augmented vectors have a class, they behave differently to the atomic vector on which they are built. In this book, we make use of four important augmented vectors:
* Factors.
* Date-times and times.
* Date-times
* Times.
* Tibbles.
These are described below.
@ -671,5 +671,5 @@ The main difference is the class. The class of tibble includes "data.frame" whic
1. Try and make a tibble that has columns with different lengths. What
happens?
1. Based of the definition above, is it ok to have a list as a
1. Based on the definition above, is it ok to have a list as a
column of a tibble?