First let’s load the library:

I often want to get the first, last or *n*^{th} number in a string.

`#> [1] 1000`

`#> [1] 488`

`#> [1] 512`

```
#> [[1]]
#> [1] "A population of " " comprised of " " dogs and "
#> [4] " cats."
```

```
#> [[1]]
#> [1] "A population of " "1000" " comprised of "
#> [4] "488" " dogs and " "512"
#> [7] " cats."
```

Sometimes we don’t want to know is something *is* numeric, we want to know if it could be considered to be numeric (or could be coerced to numeric). For this, there’s `can_be_numeric()`

.

`#> [1] TRUE`

`#> [1] FALSE`

`#> [1] TRUE`

`#> [1] TRUE`

`#> [1] FALSE`

`#> [1] "b"`

`#> [1] "z"`

`stringr`

’s `str_trim`

just trims whitespace. What if you want to trim something else? Now you can `trim_anything()`

.

`#> [1] "rmarkdown"`

`#> [1] 10`

`#> [1] 2`

Suppose we want to remove double spacing:

```
double__spaced <- "Hello world, pretend it's Saturday :-)"
count_matches(double__spaced, " ") # count the spaces
```

`#> [1] 10`

`#> [1] "Hello world, pretend it's Saturday :-)"`

`#> [1] 5`

Suppose we have sentences telling us about a couple of boxes:

```
box_infos <- c("Box 1 has weight 23kg and volume 0.3 cubic metres.",
"Box 2 has weight 20kg and volume 0.33 cubic metres.")
```

We can get (for example) the weights of the boxes by taking the first number that appears after the word “weight”.

```
#> [1] " 23kg and volume 0.3 cubic metres."
#> [2] " 20kg and volume 0.33 cubic metres."
```

`#> [1] 23 20`

We’d like to put all of the box information into a nice data frame. Here’s how.

```
tibble::tibble(box = nth_number(box_infos, 1),
weight = str_after_nth(box_infos, "weight", 1) %>%
nth_number(1, decimals = TRUE),
volume = str_after_nth(box_infos, "volume", 1) %>%
nth_number(1, decimals = TRUE)
)
```

```
#> # A tibble: 2 x 3
#> box weight volume
#> <int> <dbl> <dbl>
#> 1 1 23 0.3
#> 2 2 20 0.33
```

Sometimes people use camel case (CamelCase) to avoid using spaces. What if we want to put the spaces back in?

```
#> [[1]]
#> [1] "Joe" "Bloggs"
#>
#> [[2]]
#> [1] "Janey" "Mac"
```