revdep/library/simts/new/tidyr/doc/pivot.R

In SMAC-Group/simts: Time Series Analysis Tools

## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
options(tibble.print_max = 10)

## ----setup, message = FALSE---------------------------------------------------
library(tidyr)
library(dplyr)
library(readr)

## -----------------------------------------------------------------------------
relig_income

## -----------------------------------------------------------------------------
relig_income %>% 
  pivot_longer(!religion, names_to = "income", values_to = "count")

## -----------------------------------------------------------------------------
billboard

## -----------------------------------------------------------------------------
billboard %>% 
  pivot_longer(
    cols = starts_with("wk"), 
    names_to = "week", 
    values_to = "rank",
    values_drop_na = TRUE
  )

## ---- eval = FALSE------------------------------------------------------------
#  billboard %>%
#    pivot_longer(
#      cols = starts_with("wk"),
#      names_to = "week",
#      names_prefix = "wk",
#      names_transform = list(week = as.integer),
#      values_to = "rank",
#      values_drop_na = TRUE,
#    )

## ---- eval = FALSE------------------------------------------------------------
#  billboard %>%
#    pivot_longer(
#      cols = starts_with("wk"),
#      names_to = "week",
#      names_transform = list(week = readr::parse_number),
#      values_to = "rank",
#      values_drop_na = TRUE,
#    )

## -----------------------------------------------------------------------------
who

## -----------------------------------------------------------------------------
who %>% pivot_longer(
  cols = new_sp_m014:newrel_f65,
  names_to = c("diagnosis", "gender", "age"), 
  names_pattern = "new_?(.*)_(.)(.*)",
  values_to = "count"
)

## ---- eval = FALSE------------------------------------------------------------
#  who %>% pivot_longer(
#    cols = new_sp_m014:newrel_f65,
#    names_to = c("diagnosis", "gender", "age"),
#    names_pattern = "new_?(.*)_(.)(.*)",
#    names_transform = list(
#      gender = ~ readr::parse_factor(.x, levels = c("f", "m")),
#      age = ~ readr::parse_factor(
#        .x,
#        levels = c("014", "1524", "2534", "3544", "4554", "5564", "65"),
#        ordered = TRUE
#      )
#    ),
#    values_to = "count",
#  )

## -----------------------------------------------------------------------------
family <- tribble(
  ~family,  ~dob_child1,  ~dob_child2, ~gender_child1, ~gender_child2,
       1L, "1998-11-26", "2000-01-29",             1L,             2L,
       2L, "1996-06-22",           NA,             2L,             NA,
       3L, "2002-07-11", "2004-04-05",             2L,             2L,
       4L, "2004-10-10", "2009-08-27",             1L,             1L,
       5L, "2000-12-05", "2005-02-28",             2L,             1L,
)
family <- family %>% mutate_at(vars(starts_with("dob")), parse_date)
family

## -----------------------------------------------------------------------------
family %>% 
  pivot_longer(
    !family, 
    names_to = c(".value", "child"), 
    names_sep = "_", 
    values_drop_na = TRUE
  )

## -----------------------------------------------------------------------------
anscombe

## -----------------------------------------------------------------------------
anscombe %>% 
  pivot_longer(everything(), 
    names_to = c(".value", "set"), 
    names_pattern = "(.)(.)"
  ) %>% 
  arrange(set)

## -----------------------------------------------------------------------------
pnl <- tibble(
  x = 1:4,
  a = c(1, 1,0, 0),
  b = c(0, 1, 1, 1),
  y1 = rnorm(4),
  y2 = rnorm(4),
  z1 = rep(3, 4),
  z2 = rep(-2, 4),
)

pnl %>% 
  pivot_longer(
    !c(x, a, b), 
    names_to = c(".value", "time"), 
    names_pattern = "(.)(.)"
  )

## -----------------------------------------------------------------------------
df <- tibble(id = 1:3, y = 4:6, y = 5:7, y = 7:9, .name_repair = "minimal")
df

## -----------------------------------------------------------------------------
df %>% pivot_longer(!id, names_to = "name", values_to = "value")

## -----------------------------------------------------------------------------
df <- tibble(id = 1:3, x1 = 4:6, x2 = 5:7, y1 = 7:9, y2 = 10:12)
df %>% pivot_longer(!id, names_to = ".value", names_pattern = "(.).")

## -----------------------------------------------------------------------------
fish_encounters

## -----------------------------------------------------------------------------
fish_encounters %>% pivot_wider(names_from = station, values_from = seen)

## -----------------------------------------------------------------------------
fish_encounters %>% pivot_wider(
  names_from = station, 
  values_from = seen,
  values_fill = 0
)

## -----------------------------------------------------------------------------
warpbreaks <- warpbreaks %>% as_tibble() %>% select(wool, tension, breaks)
warpbreaks

## -----------------------------------------------------------------------------
warpbreaks %>% count(wool, tension)

## -----------------------------------------------------------------------------
warpbreaks %>% pivot_wider(names_from = wool, values_from = breaks)

## -----------------------------------------------------------------------------
warpbreaks %>% 
  pivot_wider(
    names_from = wool, 
    values_from = breaks,
    values_fn = list(breaks = mean)
  )

## -----------------------------------------------------------------------------
production <- expand_grid(
    product = c("A", "B"), 
    country = c("AI", "EI"), 
    year = 2000:2014
  ) %>%
  filter((product == "A" & country == "AI") | product == "B") %>% 
  mutate(production = rnorm(nrow(.)))
production

## -----------------------------------------------------------------------------
production %>% pivot_wider(
  names_from = c(product, country), 
  values_from = production
)

## -----------------------------------------------------------------------------
production %>% pivot_wider(
  names_from = c(product, country), 
  values_from = production,
  names_sep = ".",
  names_prefix = "prod."
)

production %>% pivot_wider(
  names_from = c(product, country), 
  values_from = production,
  names_glue = "prod_{product}_{country}"
)

## -----------------------------------------------------------------------------
us_rent_income

## -----------------------------------------------------------------------------
us_rent_income %>% 
  pivot_wider(names_from = variable, values_from = c(estimate, moe))

## -----------------------------------------------------------------------------
contacts <- tribble(
  ~field, ~value,
  "name", "Jiena McLellan",
  "company", "Toyota", 
  "name", "John Smith", 
  "company", "google", 
  "email", "john@google.com",
  "name", "Huxley Ratcliffe"
)

## -----------------------------------------------------------------------------
contacts <- contacts %>% 
  mutate(
    person_id = cumsum(field == "name")
  )
contacts

## -----------------------------------------------------------------------------
contacts %>% 
  pivot_wider(names_from = field, values_from = value)

## -----------------------------------------------------------------------------
world_bank_pop

## -----------------------------------------------------------------------------
pop2 <- world_bank_pop %>% 
  pivot_longer(`2000`:`2017`, names_to = "year", values_to = "value")
pop2

## -----------------------------------------------------------------------------
pop2 %>% count(indicator)

## -----------------------------------------------------------------------------
pop3 <- pop2 %>% 
  separate(indicator, c(NA, "area", "variable"))
pop3

## -----------------------------------------------------------------------------
pop3 %>% 
  pivot_wider(names_from = variable, values_from = value)

## -----------------------------------------------------------------------------
multi <- tribble(
  ~id, ~choice1, ~choice2, ~choice3,
  1, "A", "B", "C",
  2, "C", "B",  NA,
  3, "D",  NA,  NA,
  4, "B", "D",  NA
)

## -----------------------------------------------------------------------------
multi2 <- multi %>% 
  pivot_longer(!id, values_drop_na = TRUE) %>% 
  mutate(checked = TRUE)
multi2

## -----------------------------------------------------------------------------
multi2 %>% 
  pivot_wider(
    id_cols = id,
    names_from = value, 
    values_from = checked, 
    values_fill = FALSE
  )

## -----------------------------------------------------------------------------
spec <- relig_income %>% build_longer_spec(
  cols = !religion, 
  names_to = "income",
  values_to = "count"
)
pivot_longer_spec(relig_income, spec)

## -----------------------------------------------------------------------------
spec

## -----------------------------------------------------------------------------
us_rent_income %>% 
  pivot_wider(names_from = variable, values_from = c(estimate, moe))

## -----------------------------------------------------------------------------
spec1 <- us_rent_income %>% 
  build_wider_spec(names_from = variable, values_from = c(estimate, moe))
spec1

## -----------------------------------------------------------------------------
spec2 <- spec1 %>%
  mutate(.name = paste0(variable, ifelse(.value == "moe", "_moe", "")))
spec2

## -----------------------------------------------------------------------------
pivot_wider_spec(us_rent_income, spec2)

## -----------------------------------------------------------------------------
construction

## -----------------------------------------------------------------------------
spec <- tribble(
  ~.name,            ~.value, ~units,  ~region,     
  "1 unit",          "n",     "1",     NA,          
  "2 to 4 units",    "n",     "2-4",   NA,          
  "5 units or more", "n",     "5+",    NA,          
  "Northeast",       "n",     NA,      "Northeast", 
  "Midwest",         "n",     NA,      "Midwest",   
  "South",           "n",     NA,      "South",     
  "West",            "n",     NA,      "West",      
)

## -----------------------------------------------------------------------------
pivot_longer_spec(construction, spec)

## -----------------------------------------------------------------------------
construction %>% 
  pivot_longer_spec(spec) %>% 
  pivot_wider_spec(spec)