tests/testthat/_snaps/cut3.md

In drdsdaniel/Dmisc: Daniel miscellaneous functions

cut3

Code
  cut3(tbl, var_name = "age", breaks = 2)
Output
             age freq sex
  1  (0.991,5.5]    5   F
  2  (0.991,5.5]    5   F
  3  (0.991,5.5]    5   F
  4  (0.991,5.5]    4   F
  5  (0.991,5.5]    3   F
  6     (5.5,10]    3   M
  7     (5.5,10]    5   M
  8     (5.5,10]    3   M
  9     (5.5,10]    4   M
  10    (5.5,10]    5   M

Code
  cut3(tbl, var_name = "age", breaks = c(0, 5, 10))
Output
        age freq sex
  1   (0,5]    5   F
  2   (0,5]    5   F
  3   (0,5]    5   F
  4   (0,5]    4   F
  5   (0,5]    3   F
  6  (5,10]    3   M
  7  (5,10]    5   M
  8  (5,10]    3   M
  9  (5,10]    4   M
  10 (5,10]    5   M

Code
  cut3(tbl, var_name = "age", breaks = c(5), .inf = TRUE)
Output
          age freq sex
  1  (-Inf,5]    5   F
  2  (-Inf,5]    5   F
  3  (-Inf,5]    5   F
  4  (-Inf,5]    4   F
  5  (-Inf,5]    3   F
  6  (5, Inf]    3   M
  7  (5, Inf]    5   M
  8  (5, Inf]    3   M
  9  (5, Inf]    4   M
  10 (5, Inf]    5   M

Code
  cut3(tbl, var_name = "age", breaks = c(2, 5, 8))
Output
       age freq sex
  1   <NA>    5   F
  2   <NA>    5   F
  3  (2,5]    5   F
  4  (2,5]    4   F
  5  (2,5]    3   F
  6  (5,8]    3   M
  7  (5,8]    5   M
  8  (5,8]    3   M
  9   <NA>    4   M
  10  <NA>    5   M

Code
  cut3(tbl, var_name = "age", breaks = c(2, 5, 8), .inf = TRUE)
Output
          age freq sex
  1  (-Inf,2]    5   F
  2  (-Inf,2]    5   F
  3     (2,5]    5   F
  4     (2,5]    4   F
  5     (2,5]    3   F
  6     (5,8]    3   M
  7     (5,8]    5   M
  8     (5,8]    3   M
  9  (8, Inf]    4   M
  10 (8, Inf]    5   M

Code
  cut3(tbl, var_name = "age", breaks = stats::quantile)
Output
            age freq sex
  1        <NA>    5   F
  2    (1,3.25]    5   F
  3    (1,3.25]    5   F
  4  (3.25,5.5]    4   F
  5  (3.25,5.5]    3   F
  6  (5.5,7.75]    3   M
  7  (5.5,7.75]    5   M
  8   (7.75,10]    3   M
  9   (7.75,10]    4   M
  10  (7.75,10]    5   M

Code
  cut3(tbl, var_name = "age", breaks = stats::quantile, include.lowest = T)
Output
            age freq sex
  1    [1,3.25]    5   F
  2    [1,3.25]    5   F
  3    [1,3.25]    5   F
  4  (3.25,5.5]    4   F
  5  (3.25,5.5]    3   F
  6  (5.5,7.75]    3   M
  7  (5.5,7.75]    5   M
  8   (7.75,10]    3   M
  9   (7.75,10]    4   M
  10  (7.75,10]    5   M

Code
  cut3(tbl, var_name = "age", breaks = stats::quantile, .inf = TRUE)
Output
            age freq sex
  1    (-Inf,1]    5   F
  2    (1,3.25]    5   F
  3    (1,3.25]    5   F
  4  (3.25,5.5]    4   F
  5  (3.25,5.5]    3   F
  6  (5.5,7.75]    3   M
  7  (5.5,7.75]    5   M
  8   (7.75,10]    3   M
  9   (7.75,10]    4   M
  10  (7.75,10]    5   M

Code
  cut3(tbl, var_name = "age", breaks = c(0, stats::quantile(tbl$age)))
Output
            age freq sex
  1       (0,1]    5   F
  2    (1,3.25]    5   F
  3    (1,3.25]    5   F
  4  (3.25,5.5]    4   F
  5  (3.25,5.5]    3   F
  6  (5.5,7.75]    3   M
  7  (5.5,7.75]    5   M
  8   (7.75,10]    3   M
  9   (7.75,10]    4   M
  10  (7.75,10]    5   M

Code
  cut3(tbl, var_name = "age", breaks = stats::quantile, probs = c(0.3, 0.7))
Output
            age freq sex
  1        <NA>    5   F
  2    (1,3.25]    5   F
  3    (1,3.25]    5   F
  4  (3.25,5.5]    4   F
  5  (3.25,5.5]    3   F
  6  (5.5,7.75]    3   M
  7  (5.5,7.75]    5   M
  8   (7.75,10]    3   M
  9   (7.75,10]    4   M
  10  (7.75,10]    5   M

Code
  cut3(tbl, var_name = "age", breaks = 2, labels = FALSE)
Output
     age freq sex
  1    1    5   F
  2    1    5   F
  3    1    5   F
  4    1    4   F
  5    1    3   F
  6    2    3   M
  7    2    5   M
  8    2    3   M
  9    2    4   M
  10   2    5   M

Code
  cut3(tbl, var_name = "age", breaks = 2, labels = c("Menor o igual que 5",
    "Mayor a 5"))
Output
                     age freq sex
  1  Menor o igual que 5    5   F
  2  Menor o igual que 5    5   F
  3  Menor o igual que 5    5   F
  4  Menor o igual que 5    4   F
  5  Menor o igual que 5    3   F
  6            Mayor a 5    3   M
  7            Mayor a 5    5   M
  8            Mayor a 5    3   M
  9            Mayor a 5    4   M
  10           Mayor a 5    5   M

Code
  cut3(tbl, var_name = "age", breaks = 2, labels = c("low", "high"))
Output
      age freq sex
  1   low    5   F
  2   low    5   F
  3   low    5   F
  4   low    4   F
  5   low    3   F
  6  high    3   M
  7  high    5   M
  8  high    3   M
  9  high    4   M
  10 high    5   M

Code
  cut3(tbl, var_name = "age", breaks = 2, groups = "sex")
Output
  # A tibble: 10 × 3
     age        freq sex  
     <fct>     <dbl> <chr>
   1 (0.996,3]     5 F    
   2 (0.996,3]     5 F    
   3 (0.996,3]     5 F    
   4 (3,5]         4 F    
   5 (3,5]         3 F    
   6 (6,8]         3 M    
   7 (6,8]         5 M    
   8 (6,8]         3 M    
   9 (8,10]        4 M    
  10 (8,10]        5 M

Code
  cut3(tbl, var_name = "age", breaks = function(x) {
    quantile(x, probs = c(0.3, 0.7))
  })
Output
           age freq sex
  1       <NA>    5   F
  2       <NA>    5   F
  3       <NA>    5   F
  4  (3.7,7.3]    4   F
  5  (3.7,7.3]    3   F
  6  (3.7,7.3]    3   M
  7  (3.7,7.3]    5   M
  8       <NA>    3   M
  9       <NA>    4   M
  10      <NA>    5   M

Code
  cut3(tbl, var_name = "age", breaks = function(x) {
    quantile(x, probs = c(0.3, 0.7))
  }, .inf = TRUE)
Output
            age freq sex
  1  (-Inf,3.7]    5   F
  2  (-Inf,3.7]    5   F
  3  (-Inf,3.7]    5   F
  4   (3.7,7.3]    4   F
  5   (3.7,7.3]    3   F
  6   (3.7,7.3]    3   M
  7   (3.7,7.3]    5   M
  8  (7.3, Inf]    3   M
  9  (7.3, Inf]    4   M
  10 (7.3, Inf]    5   M

Code
  cut3(tbl, var_name = "age", breaks = 2, groups = "sex")
Output
  # A tibble: 10 × 3
     age        freq sex  
     <fct>     <dbl> <chr>
   1 (0.996,3]     5 F    
   2 (0.996,3]     5 F    
   3 (0.996,3]     5 F    
   4 (3,5]         4 F    
   5 (3,5]         3 F    
   6 (6,8]         3 M    
   7 (6,8]         5 M    
   8 (6,8]         3 M    
   9 (8,10]        4 M    
  10 (8,10]        5 M

drdsdaniel/Dmisc documentation built on Oct. 23, 2024, 9:28 p.m.