tell us
Dplyr::recode is from the dplyr package. The dplyr package provides a basic set of tools that makes it easier to work with data. The dplyr package itself is part of the tidyverse package.
The dplyr recode() function allows us to replace numeric, character and factor values with the desired values/names. However, this only applies to individual values in a specific column.
This is very helpful for psychology students when wanting to: - reverse score certain items e.g. changing values 1, 2, 3 into 3, 2, 1 on a scale - replace numbers with names e.g. changing 1 into females and 2 into males for a column coding for sex
show us
install and load packages
library(dplyr)
library(palmerpenguins)
library(tidyverse)get some data
penguins <- penguins %>% na.omit()
print(penguins)## # A tibble: 333 x 8
## species island bill_length_mm bill_depth_mm flipper_length_mm body_mass_g
## <fct> <fct> <dbl> <dbl> <int> <int>
## 1 Adelie Torgersen 39.1 18.7 181 3750
## 2 Adelie Torgersen 39.5 17.4 186 3800
## 3 Adelie Torgersen 40.3 18 195 3250
## 4 Adelie Torgersen 36.7 19.3 193 3450
## 5 Adelie Torgersen 39.3 20.6 190 3650
## 6 Adelie Torgersen 38.9 17.8 181 3625
## 7 Adelie Torgersen 39.2 19.6 195 4675
## 8 Adelie Torgersen 41.1 17.6 182 3200
## 9 Adelie Torgersen 38.6 21.2 191 3800
## 10 Adelie Torgersen 34.6 21.1 198 4400
## # ... with 323 more rows, and 2 more variables: sex <fct>, year <int>use the function
The following example would not be practical for the penguins dataset since the dataframe is already presented very clearly.
To use the recode() function, the specific dataset/column is specified first followed by the original value/name and then the desired value/name to substitute in. The desired value/name to be substituted in must be in quotation marks. For example, penguins$island is the specific column, Biscoe is the original name coded in the column and “B” is the desired name to be substituted in.
rec_island <- dplyr::recode(penguins$island, Biscoe = "B", Dream = "D", Torgersen = "T")
print(rec_island)## [1] T T T T T T T T T T T T T T T B B B B B B B B B B D D D D D D D D D D D D
## [38] D D D D D D D B B B B B B B B B B B B B B B B B B T T T T T T T T T T T T
## [75] T T T T D D D D D D D D D D D D D D D D B B B B B B B B B B B B B B B B T
## [112] T T T T T T T T T T T T T T T D D D D D D D D D D D D D D D D D D D D B B
## [149] B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B
## [186] B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B
## [223] B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B
## [260] B B B B B B D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D
## [297] D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D
## Levels: B D Tmore resources
We used the Rdocumentation website (https://www.rdocumentation.org/packages/dplyr/versions/0.7.8/topics/recode) and the help panel in R (via ?recode in console).