I'm attempting to Transpose a data frame in a R Shiny App using Tidyr/Dplyr techniques and can't seem to get a result that is desired. For example, I have the below table
I'd like to transpose it to the following data frame.
library(stringr)
library(tidyr)
library(dplyr)
dates <- c('2022-06-01','2022-06-02','2022-06-03','2022-06-04','2022-06-05')
price <- c(11,18,15,10,15)
Quantity <- c(20,19,14,19,17)
Tax <- c(2,4,4,1,5)
df <- data.frame(dates,price,Quantity, Tax)
df <- df %>%
mutate(dates = str_replace(str_sub(dates, start= -5), "-", "/")) %>%
pivot_wider(names_from= dates, values_from= c(price, Quantity, Tax))
df
CodePudding user response：
This is just transposing the data. In base R:
setNames(data.frame(t(df[-1])), df$dates)
2022-06-01 2022-06-02 2022-06-03 2022-06-04 2022-06-05
price 11 18 15 10 15
Quantity 20 19 14 19 17
Tax 2 4 4 1 5
Using data.table:
data.table::transpose(df, make.names = 'dates', keep.names = 'rn')
rn 2022-06-01 2022-06-02 2022-06-03 2022-06-04 2022-06-05
1 price 11 18 15 10 15
2 Quantity 20 19 14 19 17
3 Tax 2 4 4 1 5
CodePudding user response：
The other method using dplyr and tidyr:
require(dplyr)
require(tidyr)
require(tibble)
df %>%
pivot_longer(, cols = -dates) %>%
pivot_wider(, names_from = dates) %>%
rename("dates" = 1) %>%
as.data.frame()
dates 2022-06-01 2022-06-02 2022-06-03 2022-06-04 2022-06-05
1 price 11 18 15 10 15
2 Quantity 20 19 14 19 17
3 Tax 2 4 4 1 5
CodePudding user response：
We can use rotate_df from sjmisc:
library(sjmisc)
df %>%
rotate_df(cn = TRUE)
Output
2022-06-01 2022-06-02 2022-06-03 2022-06-04 2022-06-05
price 11 18 15 10 15
Quantity 20 19 14 19 17
Tax 2 4 4 1 5