simplify module and fix LOQFL_COMB

[gogonzo]

alternative to #280

Simplified the code by replacing pivot_ calls with simple filter and select.

[github-actions]

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[kartikeyakirar]

Thanks, @gogonzo! This solution is simplified version and works well. I also tested it on the theory app.

[gogonzo]

I have read the CLA Document and I hereby sign the CLA

[github-actions]

Code Coverage Summary

Filename                                 Stmts    Miss  Cover    Missing
-------------------------------------  -------  ------  -------  ---------
R/tm_g_gh_boxplot.R                        353     353  0.00%    175-595
R/tm_g_gh_correlationplot.R                556     556  0.00%    227-892
R/tm_g_gh_density_distribution_plot.R      279     279  0.00%    135-464
R/tm_g_gh_lineplot.R                       566     566  0.00%    161-821
R/tm_g_gh_scatterplot.R                    246     246  0.00%    144-442
R/tm_g_gh_spaghettiplot.R                  316     316  0.00%    194-591
R/toggleable_slider.R                      155     155  0.00%    72-244
R/utils-arbitrary_lines.r                  126     126  0.00%    19-176
R/utils-data_constraints.r                 190     190  0.00%    2-257
R/utils-keep_range_slider_updated.r         23      23  0.00%    8-38
R/utils-maptrt.r                             9       9  0.00%    24-36
R/utils-templ_ui.r                          48      48  0.00%    2-73
R/utils.R                                   42      42  0.00%    12-99
R/zzz.R                                      2       2  0.00%    2-3
TOTAL                                     2911    2911  0.00%

Diff against main

Filename                       Stmts    Miss  Cover
---------------------------  -------  ------  --------
R/tm_g_gh_correlationplot.R       -8      -8  +100.00%
TOTAL                             -8      -8  +100.00%

Results for commit: 788ef81

Minimum allowed coverage is 80%

♻️ This comment has been updated with latest results

[kartikeyakirar]

LGTM

[m7pr]

Hey @gogonzo I think the replacement of merge with dplyr::full_join caused the issues mentioned in Theory app related to an unexpected 3rd footnote that produces messages about some values being NAs.

Check this out

> x <- data.frame(
+   code = c('a', 'b'),
+   value = c('val1', 'val2')
+ )
> 
> y <- data.frame(
+   code = c('a'),
+   value = 'val3'
+ )
> 
> dplyr::full_join(
+   x, 
+   y,
+   by = 'code'
+ )
  code value.x value.y
1    a    val1    val3
2    b    val2    <NA>
> 
> merge(x, y, by = 'code')
  code value.x value.y
1    a    val1    val3

dplyr::full_join results with more rows (where some observations are NAs) where merge deletes/filters those.

I think we should get back to merge to solve unexpected 3rd footnote mentioned in Theory app.