Problem:
Have a large df with many variables. Trying to create a summary kable table with different column names than the original variables.
library(knitr)
library(dplyr)
knitr::kable(iris %>% head(),
col.names = c("Sepal length", "Sepal width", "Petal length",
"Petal width", "Species"))
| Sepal length| Sepal width| Petal length| Petal width|Species |
|------------:|-----------:|------------:|-----------:|:-------|
| 5.1| 3.5| 1.4| 0.2|setosa |
| 4.9| 3.0| 1.4| 0.2|setosa |
| 4.7| 3.2| 1.3| 0.2|setosa |
| 4.6| 3.1| 1.5| 0.2|setosa |
| 5.0| 3.6| 1.4| 0.2|setosa |
| 5.4| 3.9| 1.7| 0.4|setosa |
I want to be able to select specific columns without having to manually rename them via:
knitr::kable(iris %>% filter(Species == "setosa") %>%
select(Sepal.Length, Sepal.Width, Species) %>% head(),
col.names = c("Sepal length", "Sepal width", "Species"))
| Sepal length| Sepal width|Species |
|------------:|-----------:|:-------|
| 5.1| 3.5|setosa |
| 4.9| 3.0|setosa |
| 4.7| 3.2|setosa |
| 4.6| 3.1|setosa |
| 5.0| 3.6|setosa |
| 5.4| 3.9|setosa |
Is there a way to specify only once that I want "Sepal.Length" to be "Sepal Length." That way if I include a certain variable, my code will recognize the variable and rename it to a new column name automatically without me having to go back and do it manually?
Why not rename the columns up front, and use the formatted column names in subsequent calls to filter and select?
library(tidyverse)
rename(iris, `Sepal length` = Sepal.Length, `Sepal width` = Sepal.Width) %>%
filter(Species == "setosa") %>%
select(contains("Sepal"), Species) %>%
head() %>%
knitr::kable()
| Sepal length| Sepal width|Species |
|------------:|-----------:|:-------|
| 5.1| 3.5|setosa |
| 4.9| 3.0|setosa |
| 4.7| 3.2|setosa |
| 4.6| 3.1|setosa |
| 5.0| 3.6|setosa |
| 5.4| 3.9|setosa |