Pierrette Lo 10/9/2020
- Chapter 12
library(tidyverse)
- What do the
extraandfillarguments do inseparate()? Experiment with the various options for the following two toy datasets.
extra= what to do if there are too many piecesfill= what to do if there are not enough pieces
In the first example, by default the extra piece “g” is dropped with a warning:
tibble(x = c("a,b,c", "d,e,f,g", "h,i,j")) %>%
separate(x, c("one", "two", "three"))## Warning: Expected 3 pieces. Additional pieces discarded in 1 rows [2].
## # A tibble: 3 x 3
## one two three
## <chr> <chr> <chr>
## 1 a b c
## 2 d e f
## 3 h i j
Can keep the extra value using “merge”:
tibble(x = c("a,b,c", "d,e,f,g", "h,i,j")) %>%
separate(x, c("one", "two", "three"),
extra = "merge")## # A tibble: 3 x 3
## one two three
## <chr> <chr> <chr>
## 1 a b c
## 2 d e f,g
## 3 h i j
In the second example, the 2nd row doesn’t have enough pieces, so by
default is filled with NA on the right:
tibble(x = c("a,b,c", "d,e", "f,g,i")) %>%
separate(x, c("one", "two", "three"))## Warning: Expected 3 pieces. Missing pieces filled with `NA` in 1 rows [2].
## # A tibble: 3 x 3
## one two three
## <chr> <chr> <chr>
## 1 a b c
## 2 d e <NA>
## 3 f g i
Fill from left instead:
tibble(x = c("a,b,c", "d,e", "f,g,i")) %>%
separate(x, c("one", "two", "three"),
fill = "left")## # A tibble: 3 x 3
## one two three
## <chr> <chr> <chr>
## 1 a b c
## 2 <NA> d e
## 3 f g i
- Both
unite()andseparate()have a remove argument. What does it do? Why would you set it toFALSE?
remove indicates whether you remove the original column(s) that is
being separated/united. It can be helpful to leave these in so you can
check.
Eg:
tibble(x = c("a,b,c", "d,e", "f,g,i")) %>%
separate(x, c("one", "two", "three"),
remove = FALSE)## Warning: Expected 3 pieces. Missing pieces filled with `NA` in 1 rows [2].
## # A tibble: 3 x 4
## x one two three
## <chr> <chr> <chr> <chr>
## 1 a,b,c a b c
## 2 d,e d e <NA>
## 3 f,g,i f g i
- Compare and contrast
separate()andextract().
- separate = split a column by indicating what to separate by
- extract = split a column by using regular expressions to indicate what to capture (more flexible)
E.g. imagine trying to separate the colors from numbers in a column like this:
green1
blue25
red2699
There isn’t a common separator or position number, so you can’t use
separate(). However, you could use extract() with regular
expressions (more about this in
Chapter 14.3)
to capture “any number of alphabets before a digit”.
- Why are there three variations of separation (by position, by separator, and with groups), but only one unite?
There are different options for searching for separators to split up a column, but only one option is needed for merging a column.
- Compare and contrast the fill arguments to pivot_wider() and complete().
Example copied from text:
- explicit missing value: 2015 Q4
- implicit missing value: 2016 Q1
stocks <- tibble(
year = c(2015, 2015, 2015, 2015, 2016, 2016, 2016),
qtr = c( 1, 2, 3, 4, 2, 3, 4),
return = c(1.88, 0.59, 0.35, NA, 0.92, 0.17, 2.66)
)complete fills in NA for 2016 Q1:
stocks %>%
complete(year, qtr)## # A tibble: 8 x 3
## year qtr return
## <dbl> <dbl> <dbl>
## 1 2015 1 1.88
## 2 2015 2 0.59
## 3 2015 3 0.35
## 4 2015 4 NA
## 5 2016 1 NA
## 6 2016 2 0.92
## 7 2016 3 0.17
## 8 2016 4 2.66
Use fill argument to replace NA with 0:
stocks %>%
complete(year, qtr, fill = list(return = 0))## # A tibble: 8 x 3
## year qtr return
## <dbl> <dbl> <dbl>
## 1 2015 1 1.88
## 2 2015 2 0.59
## 3 2015 3 0.35
## 4 2015 4 0
## 5 2016 1 0
## 6 2016 2 0.92
## 7 2016 3 0.17
## 8 2016 4 2.66
pivot_wider also fills 2016 Q1 with NA:
stocks %>%
pivot_wider(names_from = year, values_from = return)## # A tibble: 4 x 3
## qtr `2015` `2016`
## <dbl> <dbl> <dbl>
## 1 1 1.88 NA
## 2 2 0.59 0.92
## 3 3 0.35 0.17
## 4 4 NA 2.66
Use values_fill argument:
(Note that it only fills the implicit values - the NA that was already there for 2015 Q4 doesn’t get replaced.)
stocks %>%
pivot_wider(names_from = year,
values_from = return,
values_fill = 0)## # A tibble: 4 x 3
## qtr `2015` `2016`
## <dbl> <dbl> <dbl>
## 1 1 1.88 0
## 2 2 0.59 0.92
## 3 3 0.35 0.17
## 4 4 NA 2.66
- What does the
.directionargument tofill()do?
Indicates which direction to copy/paste (up or down)
Example from ?fill:
tidy_pets <- tibble::tribble(
~rank, ~pet_type, ~breed,
1L, NA, "Boston Terrier",
2L, NA, "Retrievers (Labrador)",
3L, NA, "Retrievers (Golden)",
4L, NA, "French Bulldogs",
5L, NA, "Bulldogs",
6L, "Dog", "Beagles",
1L, NA, "Persian",
2L, NA, "Maine Coon",
3L, NA, "Ragdoll",
4L, NA, "Exotic",
5L, NA, "Siamese",
6L, "Cat", "American Short"
)Fill “up”:
tidy_pets %>%
fill(pet_type, .direction = "up")## # A tibble: 12 x 3
## rank pet_type breed
## <int> <chr> <chr>
## 1 1 Dog Boston Terrier
## 2 2 Dog Retrievers (Labrador)
## 3 3 Dog Retrievers (Golden)
## 4 4 Dog French Bulldogs
## 5 5 Dog Bulldogs
## 6 6 Dog Beagles
## 7 1 Cat Persian
## 8 2 Cat Maine Coon
## 9 3 Cat Ragdoll
## 10 4 Cat Exotic
## 11 5 Cat Siamese
## 12 6 Cat American Short
Note that you get the wrong result if you fill “down”:
tidy_pets %>%
fill(pet_type, .direction = "down")## # A tibble: 12 x 3
## rank pet_type breed
## <int> <chr> <chr>
## 1 1 <NA> Boston Terrier
## 2 2 <NA> Retrievers (Labrador)
## 3 3 <NA> Retrievers (Golden)
## 4 4 <NA> French Bulldogs
## 5 5 <NA> Bulldogs
## 6 6 Dog Beagles
## 7 1 Dog Persian
## 8 2 Dog Maine Coon
## 9 3 Dog Ragdoll
## 10 4 Dog Exotic
## 11 5 Dog Siamese
## 12 6 Cat American Short