This is an example how to add labels to the results table.
library(presentresults)
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# load dataset and kobo
results_table <- presentresults_MSNA2024_results_table
kobo_survey <- presentresults_MSNA2024_kobotool_template$kobo_survey
kobo_choices <- presentresults_MSNA2024_kobotool_template$kobo_choicesNote that the kobotools have additions, new indicators were added to the tools
kobo_survey |>
tail() |>
select(type, name, `label::english`)
#> # A tibble: 6 × 3
#> type name `label::english`
#> <chr> <chr> <chr>
#> 1 select_one l_1_to_5 comp_prot Sectoral composite - Protection
#> 2 select_one l_1_to_5 comp_edu Sectoral composite - Education
#> 3 select_one l_1_to_5 comp_foodsec Sectoral composite - Food security
#> 4 select_one l_1_to_5 comp_wash Sectoral composite - WASH
#> 5 select_one l_1_to_5 comp_snfi Sectoral composite - Shelter
#> 6 select_one l_1_to_5 msni Multi-Sectoral Needs Index (MSNI)kobo_choices |>
tail() |>
select(list_name, name, `label::english`)
#> # A tibble: 6 × 3
#> list_name name `label::english`
#> <chr> <chr> <chr>
#> 1 <NA> <NA> <NA>
#> 2 l_1_to_5 1 1
#> 3 l_1_to_5 2 2
#> 4 l_1_to_5 3 3
#> 5 l_1_to_5 4 4
#> 6 l_1_to_5 5 4+First you should review the kobotool to see if there is any duplicated label, names, etc. This will cause issues later one. I am passing the results table so I only look at the variables presents in the results, not everything.
review_kobo_labels_results <- review_kobo_labels(kobo_survey,
kobo_choices,
results_table = results_table
)
review_kobo_labels_results
#> # A tibble: 9 × 5
#> comments name list_name `label::english` n
#> <chr> <chr> <chr> <chr> <int>
#> 1 Kobo survey sheet has duplicated label… <NA> <NA> How often did t… 3
#> 2 Kobo choices sheet has duplicated name… none l_snfi_s… <NA> 2
#> 3 Kobo choices sheet has duplicated name… surf… l_wash_d… <NA> 2
#> 4 Kobo choices sheet has duplicated labe… <NA> l_admin1 To be updated b… 2
#> 5 Kobo choices sheet has duplicated labe… <NA> l_admin2 To be updated b… 3
#> 6 Kobo choices sheet has duplicated labe… <NA> l_admin3 To be updated b… 4
#> 7 Kobo choices sheet has duplicated labe… <NA> l_admin4 To be updated b… 4
#> 8 Kobo choices sheet has duplicated labe… <NA> l_cluste… To be updated b… 4
#> 9 Kobo choices sheet has duplicated labe… <NA> l_edu_le… To be updated b… 5In this case we have the HHS frequency question repeated, I will add which one they are referring to.
kobo_survey_fixed <- kobo_survey
kobo_survey_fixed[
which(kobo_survey_fixed[["label::english"]] == "How often did this happen in the past [4 weeks/30 days]?"),
"label::english"
] <- paste(
"How often did this happen in the past [4 weeks/30 days]? ---",
c(
"In the past 4 weeks (30 days), was there ever no food to eat of any kind in your house because of lack of resources to get food?",
"In the past 4 weeks (30 days), did you or any household member go to sleep at night hungry because there was not enough food?",
"In the past 4 weeks (30 days), did you or any household member go a whole day or night without eating anything at all because there was not enough food?"
)
)Then I will deal in the choices sheet. There are 2 flags: - Kobo
choices sheet has duplicated names in the same list_name.
- Kobo choices sheet has duplicated labels in the same list_name.
For the duplicated names in the same list name, these were added with the composite indicators. I will just keep one.
kobo_choices_fixed <- kobo_choices |>
filter(!`label::english` %in% c(
"No shelter (sleeping in the open)",
"Surface water (river, dam, lake, pond, stream, canal, irrigation channel)"
))
duplicated_listname_label <- review_kobo_labels_results |> filter(comments == "Kobo choices sheet has duplicated labels in the same list_name.")For the duplicated labels, these are because of the template. I will just add a number based on their order.
kobo_choices_fixed <- kobo_choices_fixed |>
group_by(list_name) |>
mutate(`label::english` = case_when(
list_name %in% duplicated_listname_label$list_name ~ paste(`label::english`, row_number()),
TRUE ~ `label::english`
)) |>
ungroup()I can review again.
review_kobo_labels(kobo_survey_fixed, kobo_choices_fixed, results_table = results_table)
#> # A tibble: 0 × 5
#> # ℹ 5 variables: comments <chr>, name <chr>, list_name <chr>,
#> # label::english <chr>, n <int>I can now create a dictionary that will be used to create labels.
label_dictionary <- create_label_dictionary(kobo_survey_fixed, kobo_choices_fixed, results_table = results_table)I can then add the labels to the results table.
results_table_labeled <- add_label_columns_to_results_table(
results_table,
label_dictionary
)
#> Joining with `by = join_by(analysis_type)`
#> Joining with `by = join_by(analysis_key)`
results_table_labeled |>
head()
#> # A tibble: 6 × 22
#> analysis_type analysis_var analysis_var_value group_var group_var_value stat
#> <chr> <chr> <chr> <chr> <chr> <dbl>
#> 1 prop_select_o… snfi_fds_ca… 1 admin1 PCODE1 0.286
#> 2 prop_select_o… snfi_fds_ca… 2 admin1 PCODE1 0.143
#> 3 prop_select_o… snfi_fds_ca… 3 admin1 PCODE1 0.429
#> 4 prop_select_o… snfi_fds_ca… 4 admin1 PCODE1 0.143
#> 5 prop_select_o… snfi_fds_ca… 1 admin1 PCODE2 0.267
#> 6 prop_select_o… snfi_fds_ca… 2 admin1 PCODE2 0.267
#> # ℹ 16 more variables: stat_low <dbl>, stat_upp <dbl>, n <dbl>, n_total <dbl>,
#> # n_w <dbl>, n_w_total <dbl>, analysis_key <chr>, theme <chr>, module <chr>,
#> # indicator <chr>, label_analysis_var <chr>, label_analysis_var_value <chr>,
#> # label_group_var <chr>, label_group_var_value <chr>,
#> # label_analysis_type <chr>, label_analysis_key <chr>