Nothing
## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(message = FALSE, warning = FALSE)
if (rlang::is_installed("ggplot2")) {
run <- TRUE
} else {
run <- FALSE
}
knitr::opts_chunk$set(
eval = run
)
## -----------------------------------------------------------------------------
library(broom)
library(tibble)
library(ggplot2)
library(dplyr)
library(tidyr)
library(purrr)
theme_set(theme_minimal())
## -----------------------------------------------------------------------------
data(Orange)
Orange <- as_tibble(Orange)
Orange
## -----------------------------------------------------------------------------
cor(Orange$age, Orange$circumference)
ggplot(Orange, aes(age, circumference, color = Tree)) +
geom_line()
## ----message = FALSE, warning = FALSE-----------------------------------------
Orange %>%
group_by(Tree) %>%
summarize(correlation = cor(age, circumference))
## -----------------------------------------------------------------------------
ct <- cor.test(Orange$age, Orange$circumference)
ct
## -----------------------------------------------------------------------------
tidy(ct)
## -----------------------------------------------------------------------------
nested <- Orange %>%
nest(data = -Tree)
## -----------------------------------------------------------------------------
nested %>%
mutate(test = map(data, ~ cor.test(.x$age, .x$circumference)))
## -----------------------------------------------------------------------------
nested %>%
mutate(
test = map(data, ~ cor.test(.x$age, .x$circumference)), # S3 list-col
tidied = map(test, tidy)
)
## -----------------------------------------------------------------------------
Orange %>%
nest(data = -Tree) %>%
mutate(
test = map(data, ~ cor.test(.x$age, .x$circumference)), # S3 list-col
tidied = map(test, tidy)
) %>%
unnest(tidied)
## -----------------------------------------------------------------------------
lm_fit <- lm(age ~ circumference, data = Orange)
summary(lm_fit)
## -----------------------------------------------------------------------------
tidy(lm_fit)
## -----------------------------------------------------------------------------
Orange %>%
nest(data = -Tree) %>%
mutate(
fit = map(data, ~ lm(age ~ circumference, data = .x)),
tidied = map(fit, tidy)
) %>%
unnest(tidied)
## -----------------------------------------------------------------------------
data(mtcars)
mtcars <- as_tibble(mtcars) # to play nicely with list-cols
mtcars
mtcars %>%
nest(data = -am) %>%
mutate(
fit = map(data, ~ lm(wt ~ mpg + qsec + gear, data = .x)), # S3 list-col
tidied = map(fit, tidy)
) %>%
unnest(tidied)
## -----------------------------------------------------------------------------
regressions <- mtcars %>%
nest(data = -am) %>%
mutate(
fit = map(data, ~ lm(wt ~ mpg + qsec + gear, data = .x)),
tidied = map(fit, tidy),
glanced = map(fit, glance),
augmented = map(fit, augment)
)
regressions %>%
unnest(tidied)
regressions %>%
unnest(glanced)
regressions %>%
unnest(augmented)
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