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## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
error = (Sys.getenv("IN_PKGDOWN") == "")
)
## ----setup--------------------------------------------------------------------
library(tibble)
## -----------------------------------------------------------------------------
library(formattable)
tbl <- tibble(x = digits(9:11, 3))
tbl
## ----echo = FALSE-------------------------------------------------------------
vec_ptype_abbr.formattable <- function(x, ...) {
"dbl:fmt"
}
pillar_shaft.formattable <- function(x, ...) {
pillar::new_pillar_shaft_simple(format(x), align = "right")
}
## -----------------------------------------------------------------------------
library(dplyr)
tbl2 <-
tbl %>%
mutate(
y = x + 1,
z = x * x,
v = y + z,
lag = lag(x, default = x[[1]]),
sin = sin(x),
mean = mean(v),
var = var(x)
)
tbl2
## -----------------------------------------------------------------------------
tbl2 %>%
group_by(lag) %>%
summarize(z = mean(z)) %>%
ungroup()
## -----------------------------------------------------------------------------
library(tidyr)
stocks <-
expand_grid(id = factor(1:4), year = 2018:2022) %>%
mutate(stock = currency(runif(20) * 10000))
stocks %>%
pivot_wider(id, names_from = year, values_from = stock)
## -----------------------------------------------------------------------------
library(ggplot2)
# Needs https://github.com/tidyverse/ggplot2/pull/4065 or similar
stocks %>%
ggplot(aes(x = year, y = stock, color = id)) +
geom_line()
## ----echo = FALSE-------------------------------------------------------------
DiagrammeR::mermaid("r4ds.mmd")
## ----echo = FALSE-------------------------------------------------------------
DiagrammeR::mermaid("formats.mmd")
## -----------------------------------------------------------------------------
tbl3 <-
tibble(id = letters[1:3], x = 9:11) %>%
mutate(
y = x + 1,
z = x * x,
v = y + z,
lag = lag(x, default = x[[1]]),
sin = sin(x),
mean = mean(v),
var = var(x)
)
tbl3
tbl3 %>%
mutate(
across(where(is.numeric), digits, 3),
across(where(~ is.numeric(.x) && mean(.x) > 50), digits, 1)
)
## -----------------------------------------------------------------------------
rules <- quos(
across(where(is.numeric), digits, 3),
across(where(~ is.numeric(.x) && mean(.x) > 50), digits, 1)
)
tbl3 %>%
mutate(!!!rules)
|
