creating kendall correlation matrix - r

Question

i have data that looks like this :
in total 38 columns .
data code sample :
df <- structure(
list(
Christensenellaceae = c(
0.010484508,
0.008641566,
0.010017172,
0.010741488,
0.1,
0.2,
0.3,
0.4,
0.7,
0.8,
0.9,
0.1,
0.3,
0.45,
0.5,
0.55
),
Date=c(27,27,27,27,27,27,27,27,28,28,28,28,28,28,28,28),
Treatment = c(
"Treatment 1",
"Treatment 1",
"Treatment 1",
"Treatment 1",
"Treatment 2",
"Treatment 2",
"Treatment 2",
"Treatment 2",
"Treatment 1",
"Treatment 1",
"Treatment 1",
"Treatment 1",
"Treatment 2",
"Treatment 2",
"Treatment 2",
"Treatment 2"
)
),class = "data.frame",
row.names = c(NA,-9L)
)
whay i wish to do is to create kendall correlation matrix (the data doesnt have linear behavor) between the treatment types(10 in total but 2 in example)for every column (except treatment and date) so in total 36 correlation matrix with size 1010 (here will be 22) .
this is my code:
res2 <- cor(as.matrix(data),method ="kendall")
but i get the error:
Error in cor(data, method = "kendall") : 'x' must be numeric
is there any way to solve this ? thank you:)

Answer 1

You can do that using a tidyverse approach by first making some data wrangling and then using correlate to calculate the correlation in pairs for every combination of variables.
library(corrr)
library(tidyverse)
df |>
# Transform data into wide format
pivot_wider(id_cols = Date,
names_from = Treatment,
values_from = -starts_with(c("Treatment", "Date"))) |>
# Unnest lists inside each column
unnest(cols = starts_with("Treatment")) |>
# Remove Date from the columns
select(-Date) |>
# Correlate all columns using kendall
correlate(method = "kendall")
# A tibble: 2 x 3
# term `Treatment 1` `Treatment 2`
# <chr> <dbl> <dbl>
#1 Treatment 1 NA 0.546
#2 Treatment 2 0.546 NA