Add numberstring as an acceptable indicator_unit

R/knownVariables.r

@@ -113,7 +113,7 @@ expected_eda_combinations <- unique(paste(edas$english_devolved_area_code, edas$
 potential_ob_units_regex <- "(^(sch|prov|inst|estab|reg|la|local|rsc|pcon|lep|mca|oa|ward|mat).*(name|code|urn|ukprn|number|upin|id)$)|(^(laestab|estab|sch|school|schools|prov|provider|providers|inst|institution|institutions|name|code|urn|ukprn|number|upin|id|region|la|lad|rsc|pcon|lep|mca|oa|ward|mat)$)"
 
 # Indicator units =====================================================================================================
-acceptable_indicatorunits <- c("%", "pp", "£", "£m")
+acceptable_indicatorunits <- c("%", "pp", "£", "£m", "numberstring")
 
 # Harmonised values ===================================================================================================
 ethnicity_standard_values <- suppressMessages(read_csv("data/ethnicity.csv"))

manifest.json

@@ -3903,7 +3903,7 @@
       "checksum": "e5b9343c9a0e43d83e02b339946591d1"
     },
     ".Rprofile": {
-      "checksum": "48d983e0bfe75553a940019bee72a138"
+      "checksum": "f187865370477bda269a0c2c42ba77b4"
     },
     "azure-pipelines-dev.yml": {
       "checksum": "fc2ef843ff5024bcba25ff84eec05f4c"
@@ -3981,7 +3981,7 @@
       "checksum": "1c3a5b538aa71e2f377b4733e7c9a580"
     },
     "R/knownVariables.r": {
-      "checksum": "7248277e0e99b5aee4e66bf9e8c69963"
+      "checksum": "3c352f0113bdd8cf4262617436f09c6d"
     },
     "R/mainTests.r": {
       "checksum": "58b52819cc963c2cdcbe70024a0307b7"
@@ -4341,10 +4341,10 @@
       "checksum": "ed9d3ebd24026a2e795894679395dc10"
     },
     "tests/testthat/mainTests/indicator_unit_validation.csv": {
-      "checksum": "34b34be457d8e3d94c95857cc52d719c"
+      "checksum": "840270c5e0a6fe330046ad63fa3db265"
     },
     "tests/testthat/mainTests/indicator_unit_validation.meta.csv": {
-      "checksum": "4941902672323226dcadc1445db88891"
+      "checksum": "a6e4c62f6e986c7be03ce023471f4196"
     },
     "tests/testthat/mainTests/indicators_smushed.csv": {
       "checksum": "ed524ab3c650cbb27cb31e2d4625b3d9"
@@ -4562,6 +4562,12 @@
     "tests/testthat/otherData/financial_quarter.meta.csv": {
       "checksum": "882f2fce79e2aad3555a576d3f665997"
     },
+    "tests/testthat/otherData/indicator_units_should_pass.csv": {
+      "checksum": "48f2e6c646ff7288862e9cf86c91ec66"
+    },
+    "tests/testthat/otherData/indicator_units_should_pass.meta.csv": {
+      "checksum": "623560ff6bd6fb4cde9947dc43e1f808"
+    },
     "tests/testthat/otherData/lad_within_la.csv": {
       "checksum": "013596ebab17236f2efee8fe70f7c0b7"
     },
@@ -4905,7 +4911,7 @@
       "checksum": "41a423a4bc68e5ba6c20a11f06092471"
     },
     "tests/testthat/test-function-edge_cases.R": {
-      "checksum": "f28bebce557004db15917ee71e2a4fab"
+      "checksum": "967f63745faee40e71b3f5c74a2006e1"
     },
     "tests/testthat/test-function-fileValidation.R": {
       "checksum": "302dd04b308471644c1a6574c3844c81"

tests/testthat/mainTests/indicator_unit_validation.meta.csv

@@ -1,9 +1,3 @@
 col_name,col_type,label,indicator_grouping,indicator_unit,indicator_dp,filter_hint,filter_grouping_column
-num_schools,Indicator,Number of schools,Absence fields,,0,,
-enrolments,Indicator,Number of pupil enrolments,Absence fields,,0,,
-sess_overall_percent,Indicator,Overall absence rate,Absence fields,%,0,,
-sess_authorised_percent,Indicator,Authorised absence rate,Absence fields,£m,1,,
-sess_unauthorised_percent,Indicator,Unauthorised absence rate,Absence fields,%,2,,
-enrolments_pa_10_exact,Indicator,Number of persistent absentees,Absence fields,$,0,,
-enrolments_pa_10_exact_percent,Indicator,Percentage of persistent absentees,Absence fields,%,3,,
-school_type,Filter,School type,,,,Filter by school type,school_phase
+number_persistent_absentees,Indicator,Number of persistent absentees,Absence fields,$,0,,
+perc_persistent_absentees,Indicator,Percentage of persistent absentees,Absence fields,%,3,,

tests/testthat/otherData/indicator_units_should_pass.csv

@@ -0,0 +1,4 @@
+time_period,time_identifier,geographic_level,country_code,country_name,region_code,region_name,school_phase,school_type,num_schools,enrolments,sess_overall_percent,sess_authorised_percent,sess_unauthorised_percent,enrolments_pa_10_exact,enrolments_pa_10_exact_percent,example_id
+201718,Academic year,Regional,E92000001,England,E12000001,North East,Combined,State-funded primary and secondary,1033,317616,4.62038,3.12503,1.49536,39300,12.37343,19950808
+201718,Academic year,Regional,E92000001,England,E12000001,North East,Individual,State-funded primary,858,175079,3.90145,2.7663,1.13516,18073,10.32277,19950808
+201718,Academic year,Regional,E92000001,England,E12000001,North East,Individual,State-funded secondary,175,142537,5.51279,3.57032,1.94247,21227,14.89227,19950808

tests/testthat/otherData/indicator_units_should_pass.meta.csv

@@ -0,0 +1,10 @@
+col_name,col_type,label,indicator_grouping,indicator_unit,indicator_dp,filter_hint,filter_grouping_column
+num_schools,Indicator,Number of schools,Absence fields,,0,,
+enrolments,Indicator,Number of pupil enrolments,Absence fields,,0,,
+sess_overall_percent,Indicator,Overall absence rate,Absence fields,%,0,,
+sess_authorised_percent,Indicator,Authorised absence rate,Absence fields,£m,1,,
+sess_unauthorised_percent,Indicator,Unauthorised absence rate,Absence fields,£,2,,
+enrolments_pa_10_exact,Indicator,Number of persistent absentees,Absence fields,pp,0,,
+enrolments_pa_10_exact_percent,Indicator,Percentage of persistent absentees,Absence fields,%,3,,
+example_id,Indicator,Example ID,Other,numberstring,,,
+school_type,Filter,School type,,,,Filter by school type,school_phase

tests/testthat/test-function-edge_cases.R

@@ -212,3 +212,9 @@ test_that("Can handle incorrect provider cols", {
 test_that("Can handle missing region_name", {
   expect_no_error(screeningOutput <- testOther("../../tests/testthat/otherData/missing_region_name.csv"))
 })
+
+test_that("all valid indicator units do pass", {
+  screeningOutput <- testOther("../../tests/testthat/otherData/indicator_units_should_pass.csv")
+
+  expect_equal(screeningOutput$results %>% filter(test == "indicator_unit_validation") %>% pull(result) %>% unlist(use.names = FALSE), "PASS")
+})