## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

## ----create-df----------------------------------------------------------------

df <- tibble::tribble(
  ~name,           ~x,  ~y,              ~z,  
  "N/A",           1,   "N/A",           -100, 
  "N A",           3,   "NOt available", -99,
  "N / A",         NA,  "29",              -98,
  "Not Available", -99, "25",              -101,
  "John Smith",    -98, "28",              -1)


## ----load-naniar--------------------------------------------------------------
library(naniar)

## ----replace-with-na-ex1------------------------------------------------------
df %>% replace_with_na(replace = list(x = -99))

## ----replace-with-na-ex2------------------------------------------------------
df %>%
  replace_with_na(replace = list(x = c(-99, -98)))

## ----replace-with-na-ex3------------------------------------------------------
df %>%
  replace_with_na(replace = list(x = c(-99,-98),
                             z = c(-99, -98)))

## ----replace-with-na-all-ex1--------------------------------------------------

df %>% replace_with_na_all(condition = ~.x == -99)


## ----replace-with-na-all-ex2--------------------------------------------------

# write out all the offending strings
na_strings <- c("NA", "N A", "N / A", "N/A", "N/ A", "Not Available", "NOt available")

## ----replace-with-na-all-ex3--------------------------------------------------

df %>%
  replace_with_na_all(condition = ~.x %in% na_strings)


## ----print-common-na-numbers-strings------------------------------------------
common_na_numbers
common_na_strings

## ----using-common-na-strings--------------------------------------------------
df %>%
  replace_with_na_all(condition = ~.x %in% common_na_strings)


## ----replace-with-na-at-ex1---------------------------------------------------

df %>% 
  replace_with_na_at(.vars = c("x","z"),
                     condition = ~.x == -99)


## ----replace-with-na-at-ex2---------------------------------------------------

df %>% 
  replace_with_na_at(.vars = c("x","z"),
                     condition = ~ exp(.x) < 1)

## ----replace-with-na-if-ex1---------------------------------------------------

df %>%
  replace_with_na_if(.predicate = is.character,
                     condition = ~.x %in% ("N/A"))

# or
df %>%
  replace_with_na_if(.predicate = is.character,
                     condition = ~.x %in% (na_strings))


## ----dplyr-na-if--------------------------------------------------------------

# instead of:
df_1 <- df %>% replace_with_na_all(condition = ~.x == -99)
df_1

df_2 <- df %>% dplyr::mutate(
  x = dplyr::na_if(x, -99),
  y = dplyr::na_if(z, -99)
)
df_2

# are they the same?
all.equal(df_1, df_2)

## ----replace-with-na-all-final-example----------------------------------------

na_strings <- c("NA", "N A", "N / A", "N/A", "N/ A", "Not Available", "NOt available")
df_3 <- df %>% replace_with_na_all(condition = ~.x %in% na_strings)


## ----replace-with-na-all-na-if, eval = FALSE----------------------------------
#  
#  # Not run:
#  df_4 <- df %>% dplyr::na_if(x = ., y = na_strings)
#  # Error in check_length(y, x, fmt_args("y"), glue("same as {fmt_args(~x)}")) :
#    # argument "y" is missing, with no default

## ----readr-example, eval = FALSE----------------------------------------------
#  # not run
#  dat_raw <- readr::read_csv("original.csv", na = na_strings)
#