tests/testthat/_snaps/compact.md

In DanChaltiel/crosstable: Crosstables for Descriptive Analyses

Compact method OK with data.frame

Code
  ct_compact(df, name_from = "Species")
Output
       variable Sepal.Length Sepal.Width Petal.Length Petal.Width
  1      setosa                                                  
  2                      5.1         3.5          1.4         0.2
  3                      4.9           3          1.4         0.2
  4                      4.7         3.2          1.3         0.2
  5                      4.6         3.1          1.5         0.2
  6                        5         3.6          1.4         0.2
  7  versicolor                                                  
  8                        7         3.2          4.7         1.4
  9                      6.4         3.2          4.5         1.5
  10                     6.9         3.1          4.9         1.5
  11                     5.5         2.3            4         1.3
  12                     6.5         2.8          4.6         1.5
  13  virginica                                                  
  14                     6.3         3.3            6         2.5
  15                     5.8         2.7          5.1         1.9
  16                     7.1           3          5.9         2.1
  17                     6.3         2.9          5.6         1.8
  18                     6.5           3          5.8         2.2
Code
  ct_compact(df, name_from = "Species", name_to = "Petal.Length")
Output
     Petal.Length Sepal.Length Sepal.Width Petal.Width
  1        setosa                                     
  2           1.4          5.1         3.5         0.2
  3           1.4          4.9           3         0.2
  4           1.3          4.7         3.2         0.2
  5           1.5          4.6         3.1         0.2
  6           1.4            5         3.6         0.2
  7    versicolor                                     
  8           4.7            7         3.2         1.4
  9           4.5          6.4         3.2         1.5
  10          4.9          6.9         3.1         1.5
  11            4          5.5         2.3         1.3
  12          4.6          6.5         2.8         1.5
  13    virginica                                     
  14            6          6.3         3.3         2.5
  15          5.1          5.8         2.7         1.9
  16          5.9          7.1           3         2.1
  17          5.6          6.3         2.9         1.8
  18          5.8          6.5           3         2.2
Code
  df$Species2 = substr(df$Species, 1, 1)
  ct_compact(df, name_from = "Species", name_to = "Petal.Length", wrap_cols = "Species2")
Output
     Petal.Length Sepal.Length Sepal.Width Petal.Width Species2
  1        setosa                                             s
  2           1.4          5.1         3.5         0.2         
  3           1.4          4.9           3         0.2         
  4           1.3          4.7         3.2         0.2         
  5           1.5          4.6         3.1         0.2         
  6           1.4            5         3.6         0.2         
  7    versicolor                                             v
  8           4.7            7         3.2         1.4         
  9           4.5          6.4         3.2         1.5         
  10          4.9          6.9         3.1         1.5         
  11            4          5.5         2.3         1.3         
  12          4.6          6.5         2.8         1.5         
  13    virginica                                             v
  14            6          6.3         3.3         2.5         
  15          5.1          5.8         2.7         1.9         
  16          5.9          7.1           3         2.1         
  17          5.6          6.3         2.9         1.8         
  18          5.8          6.5           3         2.2

Compact method OK with crosstable

Code
  ct_compact(ct)
Output
  # A tibble: 17 x 3
     variable              straight             vshaped              
   * <chr>                 <chr>                <chr>                
   1 Displacement (cu.in.) ""                   ""                   
   2 Min / Max             "71.1 / 258.0"       "120.3 / 472.0"      
   3 Med [IQR]             "120.5 [83.0;162.4]" "311.0 [275.8;360.0]"
   4 Mean (std)            "132.5 (56.9)"       "307.1 (106.8)"      
   5 N (NA)                "14 (0)"             "18 (0)"             
   6 Gross horsepower      ""                   ""                   
   7 Min / Max             "52.0 / 123.0"       "91.0 / 335.0"       
   8 Med [IQR]             "96.0 [66.0;109.8]"  "180.0 [156.2;226.2]"
   9 Mean (std)            "91.4 (24.4)"        "189.7 (60.3)"       
  10 N (NA)                "14 (0)"             "18 (0)"             
  11 Number of cylinders   ""                   ""                   
  12 4                     "10 (90.91%)"        "1 (9.09%)"          
  13 6                     "4 (57.14%)"         "3 (42.86%)"         
  14 8                     "0 (0%)"             "14 (100.00%)"       
  15 Transmission          ""                   ""                   
  16 auto                  "7 (36.84%)"         "12 (63.16%)"        
  17 manual                "7 (53.85%)"         "6 (46.15%)"         
Code
  ct_compact(ct, name_from = ".id")
Output
  # A tibble: 17 x 4
     variable   label                   straight             vshaped              
   * <chr>      <chr>                   <chr>                <chr>                
   1 disp       ""                      ""                   ""                   
   2 Min / Max  "Displacement (cu.in.)" "71.1 / 258.0"       "120.3 / 472.0"      
   3 Med [IQR]  "Displacement (cu.in.)" "120.5 [83.0;162.4]" "311.0 [275.8;360.0]"
   4 Mean (std) "Displacement (cu.in.)" "132.5 (56.9)"       "307.1 (106.8)"      
   5 N (NA)     "Displacement (cu.in.)" "14 (0)"             "18 (0)"             
   6 hp         ""                      ""                   ""                   
   7 Min / Max  "Gross horsepower"      "52.0 / 123.0"       "91.0 / 335.0"       
   8 Med [IQR]  "Gross horsepower"      "96.0 [66.0;109.8]"  "180.0 [156.2;226.2]"
   9 Mean (std) "Gross horsepower"      "91.4 (24.4)"        "189.7 (60.3)"       
  10 N (NA)     "Gross horsepower"      "14 (0)"             "18 (0)"             
  11 cyl        ""                      ""                   ""                   
  12 4          "Number of cylinders"   "10 (90.91%)"        "1 (9.09%)"          
  13 6          "Number of cylinders"   "4 (57.14%)"         "3 (42.86%)"         
  14 8          "Number of cylinders"   "0 (0%)"             "14 (100.00%)"       
  15 am         ""                      ""                   ""                   
  16 auto       "Transmission"          "7 (36.84%)"         "12 (63.16%)"        
  17 manual     "Transmission"          "7 (53.85%)"         "6 (46.15%)"

DanChaltiel/crosstable documentation built on Jan. 23, 2025, 10:10 a.m.