A simple question.
My Data looks like this
division_name word
Finance Good
Commercial Awesome
Finance Lovely
Commercial Support
I am finding pairwise_cor
for all possibilites of words above but I get result like:
library(widyr)
(word_cor <- ps_words %>%
group_by(word) %>%
#filter(n() >= 5) %>%
pairwise_cor(word, division_name) %>%
filter(!is.na(correlation)))
A tibble: 19,740 x 3
item1 item2 correlation
<chr> <chr> <dbl>
1 collaborative excellent 0.745
2 team excellent 0.745
3 ownership excellent 0.447
4 support excellent 0.333
I want to get the above result by group i.e. with division_name
My Data
structure(list(division_name = c("People & Organization", "People & Organization",
"People & Organization", "People & Organization", "People & Organization",
"Finance", "People & Organization", "People & Organization",
"People & Organization", "People & Organization", "Finance",
"People & Organization", "People & Organization", "Finance",
"People & Organization", "Finance", "Finance",
"People & Organization", "Finance", "Finance"
), word = c("excellent", "kick", "start", "nauman", "collaborative",
"team", "deliverable", "takes", "ownership", "ensure", "support",
"collaborative", "designing", "planning", "workshop", "deemed",
"success", "amazing", "knowledge", "sharing")), row.names = c(NA,
20L), class = "data.frame")