When I read the dplyr vignette, I found a convenient way to select sequential columns such as select(data, year:day).
Because I had inputted only column names to select() function, I was deeply affected by the convenient way.
On closer inspection, I found that the select() function accepts many types of input.
Here, I will enumerate the variety of acceptable inputs for select() function.
By the way, these column selection methods also can use in the summarise_each(), mutate_each() and some functions in tidyr package(e.g. gather()).
1. Whole codes.
At first, whole codes were shown for perspicuity.
In the sections below, the details of each command were shown.
# Data preparation ------------------------------------------------------------------
library(dplyr)
library(nycflights13)
set.seed(123)
data <- sample_n(flights, 3)
glimpse(data)
# Basic method of use select() ----------------------------------------------------------------------
select(data, year)
select(data, year, month, day)
select(data, year:day)
select(data, -year, -month, -day)
select(data, -(year:day))
select(data, 1, 2, 3)
select(data, 1:3)
select(data, -1, -2, -3)
select(data, -(1:3))
select(data, year:day, -month)
select(data, -(year:day), month)
select(data, 1:3, -2)
select(data, -(1:3), 2)
# Utility functions of select() --------------------------------------------------------------
select(data, starts_with("arr"))
select(data, ends_with("time"))
select(data, contains("_"))
select(data, matches("^(dep|arr)_"))
data2 <- data
colnames(data2) <- sprintf("x%d", 1:16)
select(data2, num_range("x", 8:11))
select(data2, num_range("x", c(9, 11)))
data3 <- data
colnames(data3) <- sprintf("x%02d", 1:16)
select(data3, num_range("x", 8:11, width=2))
col_vector <- c("year", "month", "day")
select(data, col_vector)
select(data, one_of(col_vector))
select(data, everything())
select(data, -starts_with("arr"))
# Standard evaluation --------------------------------------------------------------------
select_(data, "year", "month", "day")
col_vector <- c("year", "month", "day")
select_(data, .dots = col_vector)
select_(data, 'year:day')
select_(data, 'year:day', '-month')
select_(data, '-(year:day)')
select_(data, 'starts_with("arr")')
select_(data, '-ends_with("time")')
select_(data, .dots = c('starts_with("arr")', '-ends_with("time")'))
2. Data preparation.
To follow the dplyr vignette, flights data set in nycflights13 package were used as an example.
library(dplyr)
library(nycflights13)
set.seed(123)
data <- sample_n(flights, 3)
glimpse(data)
Variables: $ year (int) 2013, 2013, 2013 $ month (int) 12, 7, 3 $ day (int) 15, 17, 2 $ dep_time (int) 2124, 651, 1636 $ dep_delay (dbl) -4, -9, 1 $ arr_time (int) 2322, 936, 1800 $ arr_delay (dbl) 1, -28, 0 $ carrier (chr) "UA", "DL", "WN" $ tailnum (chr) "N801UA", "N194DN", "N475WN" $ flight (int) 289, 763, 1501 $ origin (chr) "EWR", "JFK", "LGA" $ dest (chr) "DTW", "LAX", "MKE" $ air_time (dbl) 88, 306, 103 $ distance (dbl) 488, 2475, 738 $ hour (dbl) 21, 6, 16 $ minute (dbl) 24, 51, 36
This data set includes the 16 columns shown above.
3. Basic method of use select().
At first, the ways of using select() were shown.
select(data, year)
year 1 2013 2 2013 3 2013
This process shows the way to take the year column out of data. To pick multiple columns, you can write the following.
select(data, year, month, day)
year month day 1 2013 12 15 2 2013 7 17 3 2013 3 2
If columns were sequential in the dataset, you could write the following to pick sequential columns.
select(data, year:day)
year month day 1 2013 12 15 2 2013 7 17 3 2013 3 2
If you want to remove a specific column, add - in the head of the column name as follows.
select(data, -year, -month, -day)
dep_time dep_delay arr_time arr_delay carrier tailnum flight origin dest air_time distance hour minute 1 2124 -4 2322 1 UA N801UA 289 EWR DTW 88 488 21 24 2 651 -9 936 -28 DL N194DN 763 JFK LAX 306 2475 6 51 3 1636 1 1800 0 WN N475WN 1501 LGA MKE 103 738 16 36
To remove sequential columns, put sequential columns in brackets () connected with a colon.
select(data, -(year:day))
dep_time dep_delay arr_time arr_delay carrier tailnum flight origin dest air_time distance hour minute 1 2124 -4 2322 1 UA N801UA 289 EWR DTW 88 488 21 24 2 651 -9 936 -28 DL N194DN 763 JFK LAX 306 2475 6 51 3 1636 1 1800 0 WN N475WN 1501 LGA MKE 103 738 16 36
It is also possible to pick columns by choosing the column number.
select(data, 1, 2, 3)
select(data, 1:3)
year month day 1 2013 12 15 2 2013 7 17 3 2013 3 2
Next topics are slightly advanced.
It is possible to pick sequential columns temporarily and remove some of these.
select(data, year:day, -month)
year day 1 2013 15 2 2013 17 3 2013 2
It is also possible to remove sequential columns and keep a part of these.
select(data, -(year:day), month)
dep_time dep_delay arr_time arr_delay carrier tailnum flight origin dest air_time distance hour minute month 1 2124 -4 2322 1 UA N801UA 289 EWR DTW 88 488 21 24 12 2 651 -9 936 -28 DL N194DN 763 JFK LAX 306 2475 6 51 7 3 1636 1 1800 0 WN N475WN 1501 LGA MKE 103 738 16 36 3
Even using a column number can give the same result with the column name. (The results are omitted.)
select(data, 1:3, -2)
select(data, -(1:3), 2)
4. Utility functions of select().
Utility functions existing in select(), summarise_each() and mutate_each() in dplyr as well as some functions in the tidyr package.
Seven functions existed in the utility functions of select().
starts_with(match, ignore.case = TRUE)ends_with(match, ignore.case = TRUE)contains(match, ignore.case = TRUE)matches(match, ignore.case = TRUE)num_range(prefix, range, width = NULL)one_of(...)everything()
We now check the respective commands and how to use them.
First, starts_with() picks columns whose name starts with the specified string.
select(data, starts_with("arr"))
arr_time arr_delay 1 2322 1 2 936 -28 3 1800 0
The argument ignore.case specifies whether the lowercase is classified as a capital letter(default is TRUE).
The ends_with() picks columns whose name ends with the specified string .
select(data, ends_with("time"))
dep_time arr_time air_time 1 2124 2322 88 2 651 936 306 3 1636 1800 103
The contains() picks columns whose name contains the specified string.
select(data, contains("_"))
dep_time dep_delay arr_time arr_delay air_time 1 2124 -4 2322 1 88 2 651 -9 936 -28 306 3 1636 1 1800 0 103
The matches() picks columns based on a regular expression matching string.
select(data, contains("_"))
dep_time dep_delay arr_time arr_delay air_time 1 2124 -4 2322 1 88 2 651 -9 936 -28 306 3 1636 1 1800 0 103
When the numbers were included in column names, num_range() might be useful.
In this example, we change the column names to be x1-x16 and execute num_range() command for the data set.
data2 <- data
colnames(data2) <- sprintf("x%d", 1:16)
select(data2, num_range("x", 8:11))
x8 x9 x10 x11 1 UA N801UA 289 EWR 2 DL N194DN 763 JFK 3 WN N475WN 1501 LGA
By specifying as num_range("x", 8:11), columns x8 to x11 can be identified.
Numbers in the column name are not necessarily sequential.
select(data2, num_range("x", c(9, 11)))
x9 x11 1 N801UA EWR 2 N194DN JFK 3 N475WN LGA
When column names were padded, the column name was shown as x01.
Here, the argument width in num_range() might be useful.
We now try this process for a data that changes the column names as x01-x16.
data3 <- data
colnames(data3) <- sprintf("x%02d", 1:16)
select(data3, num_range("x", 8:11, width=2))
x08 x09 x10 x11 1 UA N801UA 289 EWR 2 DL N194DN 763 JFK 3 WN N475WN 1501 LGA
By specifying as width=2, the zero filled columns can be picked out.
When a column is named as a vector or character string, one_of() might be useful.
An error occurs in the following case with select().
col_vector <- c("year", "month", "day")
select(data, col_vector)
Error: All select() inputs must resolve to integer column positions. The following do not: * col_vector
However, an intended process occurs in the case of one_of().
select(data, one_of(col_vector))
year month day 1 2013 12 15 2 2013 7 17 3 2013 3 2
The everything() selects all columns. (Result was omitted.)
select(data, everything())
If add - is in the head of a utility function name, we can pick out all except for the area specified in the utility function.
select(data, -starts_with("arr"))
year month day dep_time dep_delay carrier tailnum flight origin dest air_time distance hour minute 1 2013 12 15 2124 -4 UA N801UA 289 EWR DTW 88 488 21 24 2 2013 7 17 651 -9 DL N194DN 763 JFK LAX 306 2475 6 51 3 2013 3 2 1636 1 WN N475WN 1501 LGA MKE 103 738 16 36
5. Standard evaluation.
Thus far, we explained the normal select() function; however, the normal select() function cannot handle character strings as arguments.
This might become a problem when column names are given as a string vector for example.
To solve this problem, the select_() function was equipped in dplyr.
(Caution: An underscore was added in the function name.)
The use of the select_() function is the same as the select() except specifying columns by string; however, attention is needed when specifying a column name by a vector.
select_(data, "year", "month", "day")
year month day 1 2013 12 15 2 2013 7 17 3 2013 3 2
When specifying column names by a vector, the vector should be given the .dot argument.
col_vector <- c("year", "month", "day")
select_(data, .dots = col_vector)
year month day 1 2013 12 15 2 2013 7 17 3 2013 3 2
All arguments that can use the select() function are also possible candidates for the select_() function.
select_(data, 'year:day')
select_(data, 'year:day', '-month')
select_(data, '-(year:day)')
select_(data, 'starts_with("arr")')
select_(data, '-ends_with("time")')
Furthermore, also in this case, the argument vector should be given the .dot argument in the select_() function.
select_(data, .dots = c('starts_with("arr")', '-ends_with("time")'))
6. References.
Introduction to dplyr
https://cran.rstudio.com/web/packages/dplyr/vignettes/introduction.html
Help page for select() function
> help("select", package = "dplyr")
Original entry in Japanese by hoxo_m
https://qiita.com/hoxo_m/items/f2f1793c6f086d381340
Translated by siero
0 件のコメント:
コメントを投稿