precision.md
In Tplyr: A Traceability Focused Grammar of Clinical Data Summary

Missing by variables are handled as specified in precision data

i In index: 1.
Caused by error:
! The precision data provided is missing by variable cases:
           vs
Datsun 710  1

i In index: 1.
Caused by error:
! The precision data provided is missing by variable cases:
           vs
Datsun 710  1

'arg' should be one of "error", "auto"

Code
  t <- tplyr_table(mtcars, gear)
  l <- group_desc(t, wt, by = vs) %>% set_precision_data(prec2, default = "auto")
  t <- add_layers(t, l)
  as.data.frame(build(t))
Message
  Unhandled precision cases were found - calculating precision based on source data
Output
     row_label1 row_label2           var1_3           var1_4           var1_5
  1           0          n               12                2                4
  2           0  Mean (SD)     4.10 (0.768)     2.75 (0.180)     2.91 (0.610)
  3           0     Median             3.81             2.75             2.97
  4           0     Q1, Q3       3.56, 4.36       2.68, 2.81       2.61, 3.27
  5           0   Min, Max         3.4, 5.4         2.6, 2.9         2.1, 3.6
  6           0    Missing                0                0                0
  7           1          n                3               10                1
  8           1  Mean (SD) 3.0467 (0.51842) 2.5905 (0.69357) 1.5130 (       )
  9           1     Median           3.2150           2.5500           1.5130
  10          1     Q1, Q3   2.8400, 3.3375   2.0012, 3.1800   1.5130, 1.5130
  11          1   Min, Max     2.465, 3.460     1.615, 3.440     1.513, 1.513
  12          1    Missing                0                0                0
     ord_layer_index ord_layer_1 ord_layer_2
  1                1           1           1
  2                1           1           2
  3                1           1           3
  4                1           1           4
  5                1           1           5
  6                1           1           6
  7                1           2           1
  8                1           2           2
  9                1           2           3
  10               1           2           4
  11               1           2           5
  12               1           2           6

Data validation for external precision data works effectively

Precision dataset must include the variables max_int and max_dec

Precision dataset must include the variables max_int and max_dec

max_int and max_dec in precision dataset must be valid integer values

max_int and max_dec in precision dataset must be valid integer values

i In index: 1.
Caused by error:
! By variable types mismatch between precision dataset and target data

Partially provided decimal precision caps populate correctly

Code
  as.data.frame(d %>% select(starts_with("var1")))
Output
        var1_Placebo var1_Xanomeline High Dose var1_Xanomeline Low Dose
  1    322.2 ( 65.0)             298.8 ( 55.5)            287.1 ( 76.8)
  2 322.223 (64.969)          298.849 (55.543)         287.149 (76.822)
  3     322.2 (65.0)              298.8 (55.5)             287.1 (76.8)