# Data Validation Rules

#### Duncan Garmonsway

#### 2020-11-09

## What data validation rules are

Data validation rules control what constants can be entered into a cell, e.g. any whole number between 0 and 9, or one of several values from another part of the spreadsheet.

‘xlsx_validation()’ returns each of the data validation rules in an xlsx file, and the ranges of cells to which each rule applies.

Here is a rule that restricts input to integers between 0 and 9 inclusive, or no value (blank). If any other value is attempted, then an error message is displayed with the imaginative title “message title”, the informative body text “message body”, and a “stop” symbol.

    library(tidyxl)
    library(dplyr)
    #>
    #> Attaching package: 'dplyr'
    #> The following objects are masked from 'package:stats':
    #>
    #>     filter, lag
    #> The following objects are masked from 'package:base':
    #>
    #>     intersect, setdiff, setequal, union
    library(tidyr)
    examples <- system.file("extdata/examples.xlsx", package = "tidyxl")
    glimpse(xlsx_validation(examples)[1, ])
    #> Rows: 1
    #> Columns: 14
    #> $ sheet              <chr> "Sheet1"
    #> $ ref                <chr> "A106"
    #> $ type               <chr> "whole"
    #> $ operator           <chr> "between"
    #> $ formula1           <chr> "0"
    #> $ formula2           <chr> "9"
    #> $ allow_blank        <lgl> TRUE
    #> $ show_input_message <lgl> TRUE
    #> $ prompt_title       <chr> "message title"
    #> $ prompt_body        <chr> "message body"
    #> $ show_error_message <lgl> TRUE
    #> $ error_title        <chr> "error title"
    #> $ error_body         <chr> "error body"
    #> $ error_symbol       <chr> "stop"

The gamut of possible rules is given in the examples for `xlsx_validation()`.

    as.data.frame(xlsx_validation(examples))
    #>     sheet            ref       type           operator            formula1
    #> 1  Sheet1           A106      whole            between                   0
    #> 2  Sheet1           A108       list               <NA>              $B$108
    #> 3  Sheet1           A110       date            between 2017-01-01 00:00:00
    #> 4  Sheet1           A111       time            between            00:00:00
    #> 5  Sheet1           A112 textLength            between                   0
    #> 6  Sheet1           A114      whole         notBetween                   0
    #> 7  Sheet1 A115,A121:A122      whole              equal                   0
    #> 8  Sheet1           A116      whole           notEqual                   0
    #> 9  Sheet1           A117      whole        greaterThan                   0
    #> 10 Sheet1           A119      whole greaterThanOrEqual                   0
    #> 11 Sheet1           A120      whole    lessThanOrEqual                   0
    #> 12 Sheet1           A118      whole           lessThan                   0
    #> 13 Sheet1           A107    decimal         notBetween                   0
    #> 14 Sheet1           A113     custom               <NA>     A113<=LEN(B113)
    #> 15 Sheet1           A109       list               <NA>              $B$108
    #>               formula2 allow_blank show_input_message  prompt_title
    #> 1                    9        TRUE               TRUE message title
    #> 2                 <NA>        TRUE               TRUE          <NA>
    #> 3  2017-01-09 09:00:00        TRUE               TRUE          <NA>
    #> 4             09:00:00        TRUE               TRUE          <NA>
    #> 5                    9        TRUE               TRUE          <NA>
    #> 6                    9        TRUE               TRUE          <NA>
    #> 7                 <NA>        TRUE               TRUE          <NA>
    #> 8                 <NA>        TRUE               TRUE          <NA>
    #> 9                 <NA>        TRUE               TRUE          <NA>
    #> 10                <NA>        TRUE               TRUE          <NA>
    #> 11                <NA>        TRUE               TRUE          <NA>
    #> 12                <NA>        TRUE               TRUE          <NA>
    #> 13                   9       FALSE              FALSE          <NA>
    #> 14                <NA>        TRUE               TRUE          <NA>
    #> 15                <NA>        TRUE               TRUE          <NA>
    #>     prompt_body show_error_message error_title error_body error_symbol
    #> 1  message body               TRUE error title error body         stop
    #> 2          <NA>               TRUE        <NA>       <NA>      warning
    #> 3          <NA>               TRUE        <NA>       <NA>         stop
    #> 4          <NA>               TRUE        <NA>       <NA>         stop
    #> 5          <NA>               TRUE        <NA>       <NA>         stop
    #> 6          <NA>               TRUE        <NA>       <NA>         stop
    #> 7          <NA>               TRUE        <NA>       <NA>         stop
    #> 8          <NA>               TRUE        <NA>       <NA>         stop
    #> 9          <NA>               TRUE        <NA>       <NA>         stop
    #> 10         <NA>               TRUE        <NA>       <NA>         stop
    #> 11         <NA>               TRUE        <NA>       <NA>         stop
    #> 12         <NA>               TRUE        <NA>       <NA>         stop
    #> 13         <NA>              FALSE        <NA>       <NA>         stop
    #> 14         <NA>               TRUE        <NA>       <NA>         stop
    #> 15         <NA>               TRUE        <NA>       <NA>  information

## Joining rules to cells

> There are no built-in functions for joining ranges like `A1:D5,G8` to single cells like `B3`. For now, use the snippets in this section. In future I might develop a dplyr-like join function (this is hard currently because dplyr doesn’t yet join on arbitrary functions, or even the standard inequalities like `>=`). Help and advice would be gratefully accepted!

To join rules to cells, a naive method is to use the `sheet` and `ref` columns to match the `sheet` and `address` columns to the output of `xlsx_cells()`.

    rules <- xlsx_validation(examples)
    cells <- filter(xlsx_cells(examples), row >= 106, col == 1)

    rules
    #> # A tibble: 15 x 14
    #>    sheet ref   type  operator formula1 formula2 allow_blank show_input_mess…
    #>    <chr> <chr> <chr> <chr>    <chr>    <chr>    <lgl>       <lgl>
    #>  1 Shee… A106  whole between  0        9        TRUE        TRUE
    #>  2 Shee… A108  list  <NA>     $B$108   <NA>     TRUE        TRUE
    #>  3 Shee… A110  date  between  2017-01… 2017-01… TRUE        TRUE
    #>  4 Shee… A111  time  between  00:00:00 09:00:00 TRUE        TRUE
    #>  5 Shee… A112  text… between  0        9        TRUE        TRUE
    #>  6 Shee… A114  whole notBetw… 0        9        TRUE        TRUE
    #>  7 Shee… A115… whole equal    0        <NA>     TRUE        TRUE
    #>  8 Shee… A116  whole notEqual 0        <NA>     TRUE        TRUE
    #>  9 Shee… A117  whole greater… 0        <NA>     TRUE        TRUE
    #> 10 Shee… A119  whole greater… 0        <NA>     TRUE        TRUE
    #> 11 Shee… A120  whole lessTha… 0        <NA>     TRUE        TRUE
    #> 12 Shee… A118  whole lessThan 0        <NA>     TRUE        TRUE
    #> 13 Shee… A107  deci… notBetw… 0        9        FALSE       FALSE
    #> 14 Shee… A113  cust… <NA>     A113<=L… <NA>     TRUE        TRUE
    #> 15 Shee… A109  list  <NA>     $B$108   <NA>     TRUE        TRUE
    #> # … with 6 more variables: prompt_title <chr>, prompt_body <chr>,
    #> #   show_error_message <lgl>, error_title <chr>, error_body <chr>,
    #> #   error_symbol <chr>
    cells
    #> # A tibble: 93 x 21
    #>    sheet address   row   col is_blank data_type error logical numeric
    #>    <chr> <chr>   <int> <int> <lgl>    <chr>     <chr> <lgl>     <dbl>
    #>  1 Shee… A106      106     1 FALSE    numeric   <NA>  NA          0
    #>  2 Shee… A107      107     1 FALSE    numeric   <NA>  NA          0.1
    #>  3 Shee… A108      108     1 FALSE    character <NA>  NA         NA
    #>  4 Shee… A109      109     1 FALSE    character <NA>  NA         NA
    #>  5 Shee… A110      110     1 FALSE    date      <NA>  NA         NA
    #>  6 Shee… A111      111     1 FALSE    date      <NA>  NA         NA
    #>  7 Shee… A112      112     1 FALSE    character <NA>  NA         NA
    #>  8 Shee… A113      113     1 FALSE    numeric   <NA>  NA         10
    #>  9 Shee… A114      114     1 FALSE    numeric   <NA>  NA         -1
    #> 10 Shee… A115      115     1 FALSE    numeric   <NA>  NA          0
    #> # … with 83 more rows, and 12 more variables: date <dttm>, character <chr>,
    #> #   character_formatted <list>, formula <chr>, is_array <lgl>,
    #> #   formula_ref <chr>, formula_group <int>, comment <chr>, height <dbl>,
    #> #   width <dbl>, style_format <chr>, local_format_id <int>

    inner_join(rules, cells, by = c("sheet" = "sheet", "ref" = "address"))
    #> # A tibble: 9 x 33
    #>   sheet ref   type  operator formula1 formula2 allow_blank show_input_mess…
    #>   <chr> <chr> <chr> <chr>    <chr>    <chr>    <lgl>       <lgl>
    #> 1 Shee… A106  whole between  0        9        TRUE        TRUE
    #> 2 Shee… A108  list  <NA>     $B$108   <NA>     TRUE        TRUE
    #> 3 Shee… A110  date  between  2017-01… 2017-01… TRUE        TRUE
    #> 4 Shee… A111  time  between  00:00:00 09:00:00 TRUE        TRUE
    #> 5 Shee… A112  text… between  0        9        TRUE        TRUE
    #> 6 Shee… A114  whole notBetw… 0        9        TRUE        TRUE
    #> 7 Shee… A107  deci… notBetw… 0        9        FALSE       FALSE
    #> 8 Shee… A113  cust… <NA>     A113<=L… <NA>     TRUE        TRUE
    #> 9 Shee… A109  list  <NA>     $B$108   <NA>     TRUE        TRUE
    #> # … with 25 more variables: prompt_title <chr>, prompt_body <chr>,
    #> #   show_error_message <lgl>, error_title <chr>, error_body <chr>,
    #> #   error_symbol <chr>, row <int>, col <int>, is_blank <lgl>, data_type <chr>,
    #> #   error <chr>, logical <lgl>, numeric <dbl>, date <dttm>, character <chr>,
    #> #   character_formatted <list>, formula <chr>, is_array <lgl>,
    #> #   formula_ref <chr>, formula_group <int>, comment <chr>, height <dbl>,
    #> #   width <dbl>, style_format <chr>, local_format_id <int>

Notice that only 9 cells were joined, even though 15 rules were defined. Surely at least 15 cells ought to be joined? The reason why they are not is that the cells for the other 6 rules don’t exist – rules can be defined for cells that have no value, and cells with no value are not returned by `xlsx_cells()`, otherwise all 17179869184 cells in a worksheet must be returned.

A more subtle reason for certain cells not to have joined successfully is that the `ref` column of the rules sometimes refers to more than one cell, and can even refer to several, non-contiguous ranges of cells. Specifically, the seventh rule’s `ref` column has `A115,A121:A122`.

Special treatment is needed here. Ideally, some kind of join function would be defined that can compare indidual cells with ranges. But I haven’t written one, so what follows is a workaround. First, the two ranges of cells must be `unnested` into `A115` and `A121:122`. Then the range `A121:122` must be ‘unranged’ into `A121` and `A122`.

    unrange <- function(x) {
      limits <- cellranger::as.cell_limits(x)
      rows <- seq(limits$ul[1], limits$lr[1])
      cols <- seq(limits$ul[2], limits$lr[2])
      rowcol <- expand.grid(rows, cols)
      cell_addrs <- cellranger::cell_addr(rowcol[[1]], rowcol[[2]])
      cellranger::to_string(cell_addrs, fo = "A1", strict = FALSE)
    }

    unnest_ref <- function(x, ref) {
      UseMethod("unnest_ref")
    }

    unnest_ref.default <- function(x, ref_col = ref) {
      stopifnot(is.character(x), length(x) == 1L)
      refs <- unlist(strsplit(x, ",", fixed = TRUE))
      unlist(lapply(refs, unrange))
    }

    unrange("A121:A122")
    #> [1] "A121" "A122"
    unnest_ref("A115,A121:A122")
    #> [1] "A115" "A121" "A122"

The `unnest_ref()` function can also be defined for whole data frames, unnesting them by a column of references.

    unnest_ref.data.frame <- function(x, ref_col) {
      ref <- rlang::enquo(ref_col)
      x[[rlang::quo_name(ref)]] <- lapply(x[[rlang::quo_name(ref)]], unnest_ref)
      tidyr::unnest(x, rlang::UQ(ref))
    }

    (nested_rule <- slice(rules, 7))
    #> # A tibble: 1 x 14
    #>   sheet ref   type  operator formula1 formula2 allow_blank show_input_mess…
    #>   <chr> <chr> <chr> <chr>    <chr>    <chr>    <lgl>       <lgl>
    #> 1 Shee… A115… whole equal    0        <NA>     TRUE        TRUE
    #> # … with 6 more variables: prompt_title <chr>, prompt_body <chr>,
    #> #   show_error_message <lgl>, error_title <chr>, error_body <chr>,
    #> #   error_symbol <chr>
    unnest_ref(nested_rule, ref)
    #> Warning: Prefixing `UQ()` with the rlang namespace is deprecated as of rlang 0.3.0.
    #> Please use the non-prefixed form or `!!` instead.
    #>
    #>   # Bad:
    #>   rlang::expr(mean(rlang::UQ(var) * 100))
    #>
    #>   # Ok:
    #>   rlang::expr(mean(UQ(var) * 100))
    #>
    #>   # Good:
    #>   rlang::expr(mean(!!var * 100))
    #>
    #> This warning is displayed once per session.
    #> # A tibble: 3 x 14
    #>   sheet ref   type  operator formula1 formula2 allow_blank show_input_mess…
    #>   <chr> <chr> <chr> <chr>    <chr>    <chr>    <lgl>       <lgl>
    #> 1 Shee… A115  whole equal    0        <NA>     TRUE        TRUE
    #> 2 Shee… A121  whole equal    0        <NA>     TRUE        TRUE
    #> 3 Shee… A122  whole equal    0        <NA>     TRUE        TRUE
    #> # … with 6 more variables: prompt_title <chr>, prompt_body <chr>,
    #> #   show_error_message <lgl>, error_title <chr>, error_body <chr>,
    #> #   error_symbol <chr>

Finally the new data frame of rules can be joined to a data frame of cells in any of the usual ways, via the `sheet` and `ref` columns.

Problems with this approach occur with rules that are defined over large ranges of cells: the ‘unnesting’ of those ranges results in very long vectors of individual cell addresses, or (worse) huge data frames of rules. Such cases are commonplace, because rules are often defined for entire columns of a spreadsheet, and a column has 1048576 rows.