revdep/library/simts/new/tibble/doc/formats.R

In SMAC-Group/simts: Time Series Analysis Tools

## ---- 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)