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Replace all values with NA where a certain condition is met

Source: R/scoped-replace-with-na.R
replace_with_na_all.Rd

This function takes a dataframe and replaces all values that meet the condition specified as an NA value, following a special syntax.

Usage

replace_with_na_all(data, condition)

Arguments

data

A dataframe

condition

A condition required to be TRUE to set NA. Here, the condition is specified with a formula, following the syntax: ~.x {condition}. For example, writing ~.x < 20 would mean "where a variable value is less than 20, replace with NA".

Examples

dat_ms <- tibble::tribble(~x,  ~y,    ~z,
                          1,   "A",   -100,
                          3,   "N/A", -99,
                          NA,  NA,    -98,
                          -99, "E",   -101,
                          -98, "F",   -1)

dat_ms
#> # A tibble: 5 × 3
#>       x y         z
#>   <dbl> <chr> <dbl>
#> 1     1 A      -100
#> 2     3 N/A     -99
#> 3    NA NA      -98
#> 4   -99 E      -101
#> 5   -98 F        -1
#replace all instances of -99 with NA
replace_with_na_all(data = dat_ms,
                    condition = ~.x == -99)
#> # A tibble: 5 × 3
#>       x y         z
#>   <dbl> <chr> <dbl>
#> 1     1 A      -100
#> 2     3 N/A      NA
#> 3    NA NA      -98
#> 4    NA E      -101
#> 5   -98 F        -1

# replace all instances of -99 or -98, or "N/A" with NA
replace_with_na_all(dat_ms,
                    condition = ~.x %in% c(-99, -98, "N/A"))
#> # A tibble: 5 × 3
#>       x y         z
#>   <dbl> <chr> <dbl>
#> 1     1 A      -100
#> 2     3 NA       NA
#> 3    NA NA       NA
#> 4    NA E      -101
#> 5    NA F        -1
# replace all instances of common na strings
replace_with_na_all(dat_ms,
                    condition = ~.x %in% common_na_strings)
#> # A tibble: 5 × 3
#>       x y         z
#>   <dbl> <chr> <dbl>
#> 1     1 A      -100
#> 2     3 NA      -99
#> 3    NA NA      -98
#> 4   -99 E      -101
#> 5   -98 F        -1

# where works with functions
replace_with_na_all(airquality, ~ sqrt(.x) < 5)
#> # A tibble: 153 × 6
#>    Ozone Solar.R  Wind  Temp Month   Day
#>    <int>   <int> <dbl> <int> <int> <int>
#>  1    41     190    NA    67    NA    NA
#>  2    36     118    NA    72    NA    NA
#>  3    NA     149    NA    74    NA    NA
#>  4    NA     313    NA    62    NA    NA
#>  5    NA      NA    NA    56    NA    NA
#>  6    28      NA    NA    66    NA    NA
#>  7    NA     299    NA    65    NA    NA
#>  8    NA      99    NA    59    NA    NA
#>  9    NA      NA    NA    61    NA    NA
#> 10    NA     194    NA    69    NA    NA
#> # ℹ 143 more rows