From cc6ce0a9382d705be7b5336af08ca0a13df7a812 Mon Sep 17 00:00:00 2001 From: "Matthijs S. Berends" Date: Wed, 1 Jul 2020 11:23:05 +0200 Subject: [PATCH] (v1.2.0.9020) ab_from_text() improvement --- DESCRIPTION | 2 +- NEWS.md | 24 +-------- R/ab_from_text.R | 2 +- docs/404.html | 2 +- docs/LICENSE-text.html | 2 +- docs/articles/index.html | 2 +- docs/authors.html | 2 +- docs/index.html | 2 +- docs/news/index.html | 108 ++++++++++++++++---------------------- docs/pkgdown.yml | 2 +- docs/reference/index.html | 2 +- 11 files changed, 55 insertions(+), 95 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index a5bebb8b..5b9a5db4 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,5 +1,5 @@ Package: AMR -Version: 1.2.0.9019 +Version: 1.2.0.9020 Date: 2020-07-01 Title: Antimicrobial Resistance Analysis Authors@R: c( diff --git a/NEWS.md b/NEWS.md index 707f9ef4..fe6f206e 100755 --- a/NEWS.md +++ b/NEWS.md @@ -1,19 +1,8 @@ -# AMR 1.2.0.9019 +# AMR 1.2.0.9020 ## Last updated: 01-Jul-2020 ### New -* Function `ab_from_text()` to retrieve antimicrobial drugs from clinical texts in e.g. health care records, which also corrects for misspelling since it uses `as.ab()` internally: - ```r - ab_from_text(c("28/03/2020 regular amoxiciliin 500mg po tds", - "15/04/2020 started on ciprofloxi-thingy and tobra today")) - #> [[1]] - #> Class - #> [1] AMX - #> - #> [[2]] - #> Class - #> [1] CIP TOB - ``` +* Function `ab_from_text()` to retrieve antimicrobial drug names, doses and forms of administration from clinical texts in e.g. health care records, which also corrects for misspelling since it uses `as.ab()` internally * [Tidyverse selections](https://tidyselect.r-lib.org/reference/language.html) for antibiotic classes, that help to select the columns of antibiotics that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations. They can be used in any function that allows Tidyverse selections, like `dplyr::select()` and `tidyr::pivot_longer()`: ```r library(dplyr) @@ -22,15 +11,6 @@ example_isolates %>% select(carbapenems()) #> Selecting carbapenems: `IPM` (imipenem), `MEM` (meropenem) - - tibble(J01CA01 = "S") %>% - select(penicillins()) - #> Selecting beta-lactams/penicillins: `J01CA01` (ampicillin) - - # select an antibiotic class manually with `ab_class()` - example_isolates %>% - select(ab_class("mycobact")) - #> Selecting antimycobacterials: `RIF` (rifampicin) ``` * Added `mo_domain()` as an alias to `mo_kingdom()` * Added function `filter_penicillins()` to filter isolates on a specific result in any column with a name in the antimicrobial 'penicillins' class (more specific: ATC subgroup *Beta-lactam antibacterials, penicillins*) diff --git a/R/ab_from_text.R b/R/ab_from_text.R index ad9470b2..361d2dc1 100644 --- a/R/ab_from_text.R +++ b/R/ab_from_text.R @@ -94,7 +94,7 @@ ab_from_text <- function(text, stop_if(length(type) != 1, "`type` must be of length 1") text <- tolower(as.character(text)) - text_split_all <- strsplit(text, "[ ;.,:/\\|-]") + text_split_all <- strsplit(text, "[ ;.,:\\|]") if (type %like% "(drug|ab|anti)") { diff --git a/docs/404.html b/docs/404.html index 3745aceb..7c1a9d9c 100644 --- a/docs/404.html +++ b/docs/404.html @@ -81,7 +81,7 @@ AMR (for R) - 1.2.0.9019 + 1.2.0.9020 diff --git a/docs/LICENSE-text.html b/docs/LICENSE-text.html index 41d1ce2c..728d1fdb 100644 --- a/docs/LICENSE-text.html +++ b/docs/LICENSE-text.html @@ -81,7 +81,7 @@ AMR (for R) - 1.2.0.9019 + 1.2.0.9020 diff --git a/docs/articles/index.html b/docs/articles/index.html index 705f3b1d..2c322f41 100644 --- a/docs/articles/index.html +++ b/docs/articles/index.html @@ -81,7 +81,7 @@ AMR (for R) - 1.2.0.9019 + 1.2.0.9020 diff --git a/docs/authors.html b/docs/authors.html index 0e00f051..bbce3c5a 100644 --- a/docs/authors.html +++ b/docs/authors.html @@ -81,7 +81,7 @@ AMR (for R) - 1.2.0.9019 + 1.2.0.9020 diff --git a/docs/index.html b/docs/index.html index b13f4661..f5cc0d82 100644 --- a/docs/index.html +++ b/docs/index.html @@ -43,7 +43,7 @@ AMR (for R) - 1.2.0.9019 + 1.2.0.9020 diff --git a/docs/news/index.html b/docs/news/index.html index 8d4e71c5..64691736 100644 --- a/docs/news/index.html +++ b/docs/news/index.html @@ -81,7 +81,7 @@ AMR (for R) - 1.2.0.9019 + 1.2.0.9020 @@ -229,9 +229,9 @@ Source: NEWS.md -
-

-AMR 1.2.0.9019 Unreleased +
+

+AMR 1.2.0.9020 Unreleased

@@ -241,35 +241,15 @@

New

    -
  • -

    Function ab_from_text() to retrieve antimicrobial drugs from clinical texts in e.g. health care records, which also corrects for misspelling since it uses as.ab() internally:

    -
    ab_from_text(c("28/03/2020 regular amoxiciliin 500mg po tds",
-               "15/04/2020 started on ciprofloxi-thingy and tobra today"))
-#> [[1]]
-#> Class <ab>
-#> [1] AMX
-#> 
-#> [[2]]
-#> Class <ab>
-#> [1] CIP TOB
    -
    • +

  • Function ab_from_text() to retrieve antimicrobial drug names, doses and forms of administration from clinical texts in e.g. health care records, which also corrects for misspelling since it uses as.ab() internally

  • Tidyverse selections for antibiotic classes, that help to select the columns of antibiotics that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations. They can be used in any function that allows Tidyverse selections, like dplyr::select() and tidyr::pivot_longer():

    -
    library(dplyr)
+
    library(dplyr)
 
 # Columns 'IPM' and 'MEM' are in the example_isolates data set
 example_isolates %>%
   select(carbapenems())
-#> Selecting carbapenems: `IPM` (imipenem), `MEM` (meropenem)
-
-tibble(J01CA01 = "S") %>%
-  select(penicillins())
-#> Selecting beta-lactams/penicillins: `J01CA01` (ampicillin)
-
-# select an antibiotic class manually with `ab_class()`
-example_isolates %>%
-  select(ab_class("mycobact"))
-#> Selecting antimycobacterials: `RIF` (rifampicin)
    
+#> Selecting carbapenems: `IPM` (imipenem), `MEM` (meropenem)

  • Added mo_domain() as an alias to mo_kingdom()

  • Added function filter_penicillins() to filter isolates on a specific result in any column with a name in the antimicrobial ‘penicillins’ class (more specific: ATC subgroup Beta-lactam antibacterials, penicillins)

    • @@ -416,7 +396,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/

  • Fixed important floating point error for some MIC comparisons in EUCAST 2020 guideline

  • Interpretation from MIC values (and disk zones) to R/SI can now be used with mutate_at() of the dplyr package:

    -
    yourdata %>%
+
    yourdata %>%
   mutate_at(vars(antibiotic1:antibiotic25), as.rsi, mo = "E. coli")
 
 yourdata %>%
@@ -443,7 +423,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
      
 
    • 
 
      Support for LOINC codes in the antibiotics data set. Use ab_loinc() to retrieve LOINC codes, or use a LOINC code for input in any ab_* function:
      
-
      ab_loinc("ampicillin")
+
      ab_loinc("ampicillin")
 #> [1] "21066-6" "3355-5"  "33562-0" "33919-2" "43883-8" "43884-6" "87604-5"
 ab_name("21066-6")
 #> [1] "Ampicillin"
@@ -452,7 +432,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
      • 
 
    • 
 
      Support for SNOMED CT codes in the microorganisms data set. Use mo_snomed() to retrieve SNOMED codes, or use a SNOMED code for input in any mo_* function:
      
-
      mo_snomed("S. aureus")
+
      mo_snomed("S. aureus")
 #> [1] 115329001   3092008 113961008
 mo_name(115329001)
 #> [1] "Staphylococcus aureus"
@@ -515,9 +495,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
        
 
      • 
 
        If you were dependent on the old Enterobacteriaceae family e.g. by using in your code:
        
-
        if (mo_family(somebugs) == "Enterobacteriaceae") ...
        
+
        if (mo_family(somebugs) == "Enterobacteriaceae") ...
        
 
        then please adjust this to:
        
-
        if (mo_order(somebugs) == "Enterobacterales") ...
        
+
        if (mo_order(somebugs) == "Enterobacterales") ...
        
 
        • 
 
      
 
      • 
@@ -529,7 +509,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
        
 
      • 
 
        Functions susceptibility() and resistance() as aliases of proportion_SI() and proportion_R(), respectively. These functions were added to make it more clear that “I” should be considered susceptible and not resistant.
        
-
        library(dplyr)
+
        library(dplyr)
 example_isolates %>%
   group_by(bug = mo_name(mo)) %>%
   summarise(amoxicillin = resistance(AMX),
@@ -556,7 +536,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
      • More intelligent way of coping with some consonants like “l” and “r”
        • 
 
      • 
 
        Added a score (a certainty percentage) to mo_uncertainties(), that is calculated using the Levenshtein distance:
        
-
        as.mo(c("Stafylococcus aureus",
+
        as.mo(c("Stafylococcus aureus",
         "staphylokok aureuz"))
 #> Warning: 
 #> Results of two values were guessed with uncertainty. Use mo_uncertainties() to review them.
@@ -613,12 +593,12 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
          
 
        • 
 
          Determination of first isolates now excludes all ‘unknown’ microorganisms at default, i.e. microbial code "UNKNOWN". They can be included with the new parameter include_unknown:
          
-
          first_isolate(..., include_unknown = TRUE)
          
+
          first_isolate(..., include_unknown = TRUE)
          
 
          For WHONET users, this means that all records/isolates with organism code "con" (contamination) will be excluded at default, since as.mo("con") = "UNKNOWN". The function always shows a note with the number of ‘unknown’ microorganisms that were included or excluded.
          
 
          • 
 
        • 
 
          For code consistency, classes ab and mo will now be preserved in any subsetting or assignment. For the sake of data integrity, this means that invalid assignments will now result in NA:
          
-
          # how it works in base R:
+
          # how it works in base R:
 x <- factor("A")
 x[1] <- "B"
 #> Warning message:
@@ -641,7 +621,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
            
 
          • 
 
            Function bug_drug_combinations() to quickly get a data.frame with the results of all bug-drug combinations in a data set. The column containing microorganism codes is guessed automatically and its input is transformed with mo_shortname() at default:
            
-
            x <- bug_drug_combinations(example_isolates)
+
            x <- bug_drug_combinations(example_isolates)
 #> NOTE: Using column `mo` as input for `col_mo`.
 x[1:4, ]
 #>             mo  ab S I R total
@@ -662,11 +642,11 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 #> 4 Gram-negative AMX 227  0 405   632
 #> NOTE: Use 'format()' on this result to get a publicable/printable format.
            
 
            You can format this to a printable format, ready for reporting or exporting to e.g. Excel with the base R format() function:
            
-
            format(x, combine_IR = FALSE)
            
+
            format(x, combine_IR = FALSE)
            
 
            • 
 
          • 
 
            Additional way to calculate co-resistance, i.e. when using multiple antimicrobials as input for portion_* functions or count_* functions. This can be used to determine the empiric susceptibility of a combination therapy. A new parameter only_all_tested (which defaults to FALSE) replaces the old also_single_tested and can be used to select one of the two methods to count isolates and calculate portions. The difference can be seen in this example table (which is also on the portion and count help pages), where the %SI is being determined:
            
-
            # --------------------------------------------------------------------
+
            # --------------------------------------------------------------------
 #                     only_all_tested = FALSE  only_all_tested = TRUE
 #                     -----------------------  -----------------------
 #  Drug A    Drug B   include as  include as   include as  include as
@@ -686,7 +666,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
            • 
 
          • 
 
            tibble printing support for classes rsi, mic, disk, ab mo. When using tibbles containing antimicrobial columns, values S will print in green, values I will print in yellow and values R will print in red. Microbial IDs (class mo) will emphasise on the genus and species, not on the kingdom.
            
-
            # (run this on your own console, as this page does not support colour printing)
+
            # (run this on your own console, as this page does not support colour printing)
 library(dplyr)
 example_isolates %>%
   select(mo:AMC) %>%
@@ -767,7 +747,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
              
 
            • 
 
              Function rsi_df() to transform a data.frame to a data set containing only the microbial interpretation (S, I, R), the antibiotic, the percentage of S/I/R and the number of available isolates. This is a convenient combination of the existing functions count_df() and portion_df() to immediately show resistance percentages and number of available isolates:
              
-
              septic_patients %>%
+
              septic_patients %>%
   select(AMX, CIP) %>%
   rsi_df()
 #      antibiotic  interpretation      value  isolates
@@ -792,7 +772,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
            • UPEC (Uropathogenic E. coli)
              • 
 
            
 
            All these lead to the microbial ID of E. coli:
            
-
            as.mo("UPEC")
+
            as.mo("UPEC")
 # B_ESCHR_COL
 mo_name("UPEC")
 # "Escherichia coli"
@@ -899,7 +879,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
          • when all values are unique it now shows a message instead of a warning
            • 
 
          • 
 
            support for boxplots:
            
-
            septic_patients %>%
+
            septic_patients %>%
   freq(age) %>%
   boxplot()
 # grouped boxplots:
@@ -990,7 +970,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
            • 
 
          • 
 
            New filters for antimicrobial classes. Use these functions to filter isolates on results in one of more antibiotics from a specific class:
            
-
            filter_aminoglycosides()
+
            filter_aminoglycosides()
 filter_carbapenems()
 filter_cephalosporins()
 filter_1st_cephalosporins()
@@ -1002,14 +982,14 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 filter_macrolides()
 filter_tetracyclines()
            
 
            The antibiotics data set will be searched, after which the input data will be checked for column names with a value in any abbreviations, codes or official names found in the antibiotics data set. For example:
            
-
            septic_patients %>% filter_glycopeptides(result = "R")
+
            septic_patients %>% filter_glycopeptides(result = "R")
 # Filtering on glycopeptide antibacterials: any of `vanc` or `teic` is R
 septic_patients %>% filter_glycopeptides(result = "R", scope = "all")
 # Filtering on glycopeptide antibacterials: all of `vanc` and `teic` is R
            
 
            • 
 
          • 
 
            All ab_* functions are deprecated and replaced by atc_* functions:
            
-
            ab_property -> atc_property()
+
            ab_property -> atc_property()
 ab_name -> atc_name()
 ab_official -> atc_official()
 ab_trivial_nl -> atc_trivial_nl()
@@ -1028,17 +1008,17 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
          • New function age_groups() to split ages into custom or predefined groups (like children or elderly). This allows for easier demographic antimicrobial resistance analysis per age group.
            • 
 
          • 
 
            New function ggplot_rsi_predict() as well as the base R plot() function can now be used for resistance prediction calculated with resistance_predict():
            
-
            x <- resistance_predict(septic_patients, col_ab = "amox")
+
            x <- resistance_predict(septic_patients, col_ab = "amox")
 plot(x)
 ggplot_rsi_predict(x)
            
 
            • 
 
          • 
 
            Functions filter_first_isolate() and filter_first_weighted_isolate() to shorten and fasten filtering on data sets with antimicrobial results, e.g.:
            
-
            septic_patients %>% filter_first_isolate(...)
+
            septic_patients %>% filter_first_isolate(...)
 # or
 filter_first_isolate(septic_patients, ...)
            
 
            is equal to:
            
-
            septic_patients %>%
+
            septic_patients %>%
   mutate(only_firsts = first_isolate(septic_patients, ...)) %>%
   filter(only_firsts == TRUE) %>%
   select(-only_firsts)
            
@@ -1069,7 +1049,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
              
 
            • 
 
              Now handles incorrect spelling, like i instead of y and f instead of ph:
              
-
              # mo_fullname() uses as.mo() internally
+
              # mo_fullname() uses as.mo() internally
 
 mo_fullname("Sthafilokockus aaureuz")
 #> [1] "Staphylococcus aureus"
@@ -1079,7 +1059,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
              • 
 
            • 
 
              Uncertainty of the algorithm is now divided into four levels, 0 to 3, where the default allow_uncertain = TRUE is equal to uncertainty level 2. Run ?as.mo for more info about these levels.
              
-
              # equal:
+
              # equal:
 as.mo(..., allow_uncertain = TRUE)
 as.mo(..., allow_uncertain = 2)
 
@@ -1092,7 +1072,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
            • All microbial IDs that found are now saved to a local file ~/.Rhistory_mo. Use the new function clean_mo_history() to delete this file, which resets the algorithms.
              • 
 
            • 
 
              Incoercible results will now be considered ‘unknown’, MO code UNKNOWN. On foreign systems, properties of these will be translated to all languages already previously supported: German, Dutch, French, Italian, Spanish and Portuguese:
              
-
              mo_genus("qwerty", language = "es")
+
              mo_genus("qwerty", language = "es")
 # Warning: 
 # one unique value (^= 100.0%) could not be coerced and is considered 'unknown': "qwerty". Use mo_failures() to review it.
 #> [1] "(género desconocido)"
              
@@ -1140,7 +1120,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                
 
              • 
 
                Support for tidyverse quasiquotation! Now you can create frequency tables of function outcomes:
                
-
                # Determine genus of microorganisms (mo) in `septic_patients` data set:
+
                # Determine genus of microorganisms (mo) in `septic_patients` data set:
 # OLD WAY
 septic_patients %>%
   mutate(genus = mo_genus(mo)) %>%
@@ -1223,7 +1203,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
              • Fewer than 3 characters as input for as.mo will return NA
                • 
 
              • 
 
                Function as.mo (and all mo_* wrappers) now supports genus abbreviations with “species” attached
                
-
                as.mo("E. species")        # B_ESCHR
+
                as.mo("E. species")        # B_ESCHR
 mo_fullname("E. spp.")     # "Escherichia species"
 as.mo("S. spp")            # B_STPHY
 mo_fullname("S. species")  # "Staphylococcus species"
                
@@ -1238,13 +1218,13 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                  
 
                • 
 
                  Support for grouping variables, test with:
                  
-
                  septic_patients %>%
+
                  septic_patients %>%
   group_by(hospital_id) %>%
   freq(gender)
                  
 
                  • 
 
                • 
 
                  Support for (un)selecting columns:
                  
-
                  septic_patients %>%
+
                  septic_patients %>%
   freq(hospital_id) %>%
   select(-count, -cum_count) # only get item, percent, cum_percent
                  
 
                  • 
@@ -1322,7 +1302,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
 
                
 
                They also come with support for German, Dutch, French, Italian, Spanish and Portuguese:
                
-
                mo_gramstain("E. coli")
+
                mo_gramstain("E. coli")
 # [1] "Gram negative"
 mo_gramstain("E. coli", language = "de") # German
 # [1] "Gramnegativ"
@@ -1331,7 +1311,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 mo_fullname("S. group A", language = "pt") # Portuguese
 # [1] "Streptococcus grupo A"
                
 
                Furthermore, former taxonomic names will give a note about the current taxonomic name:
                
-
                mo_gramstain("Esc blattae")
+
                mo_gramstain("Esc blattae")
 # Note: 'Escherichia blattae' (Burgess et al., 1973) was renamed 'Shimwellia blattae' (Priest and Barker, 2010)
 # [1] "Gram negative"
                
 
                • 
@@ -1344,14 +1324,14 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
              • Function is.rsi.eligible to check for columns that have valid antimicrobial results, but do not have the rsi class yet. Transform the columns of your raw data with: data %>% mutate_if(is.rsi.eligible, as.rsi)
                • 
 
              • 
 
                Functions as.mo and is.mo as replacements for as.bactid and is.bactid (since the microoganisms data set not only contains bacteria). These last two functions are deprecated and will be removed in a future release. The as.mo function determines microbial IDs using intelligent rules:
                
-
                as.mo("E. coli")
+
                as.mo("E. coli")
 # [1] B_ESCHR_COL
 as.mo("MRSA")
 # [1] B_STPHY_AUR
 as.mo("S group A")
 # [1] B_STRPTC_GRA
                
 
                And with great speed too - on a quite regular Linux server from 2007 it takes us less than 0.02 seconds to transform 25,000 items:
                
-
                thousands_of_E_colis <- rep("E. coli", 25000)
+
                thousands_of_E_colis <- rep("E. coli", 25000)
 microbenchmark::microbenchmark(as.mo(thousands_of_E_colis), unit = "s")
 # Unit: seconds
 #         min       median         max  neval
@@ -1383,7 +1363,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
              • Added three antimicrobial agents to the antibiotics data set: Terbinafine (D01BA02), Rifaximin (A07AA11) and Isoconazole (D01AC05)
                • 
 
              • 
 
                Added 163 trade names to the antibiotics data set, it now contains 298 different trade names in total, e.g.:
                
-
                ab_official("Bactroban")
+
                ab_official("Bactroban")
 # [1] "Mupirocin"
 ab_name(c("Bactroban", "Amoxil", "Zithromax", "Floxapen"))
 # [1] "Mupirocin" "Amoxicillin" "Azithromycin" "Flucloxacillin"
@@ -1398,7 +1378,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
              • Added parameters minimum and as_percent to portion_df
                • 
 
              • 
 
                Support for quasiquotation in the functions series count_* and portions_*, and n_rsi. This allows to check for more than 2 vectors or columns.
                
-
                septic_patients %>% select(amox, cipr) %>% count_IR()
+
                septic_patients %>% select(amox, cipr) %>% count_IR()
 # which is the same as:
 septic_patients %>% count_IR(amox, cipr)
 
@@ -1416,10 +1396,10 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
              • Added longest en shortest character length in the frequency table (freq) header of class character
                • 
 
              • 
 
                Support for types (classes) list and matrix for freq
                
-
                my_matrix = with(septic_patients, matrix(c(age, gender), ncol = 2))
+
                my_matrix = with(septic_patients, matrix(c(age, gender), ncol = 2))
 freq(my_matrix)
                
 
                For lists, subsetting is possible:
                
-
                my_list = list(age = septic_patients$age, gender = septic_patients$gender)
+
                my_list = list(age = septic_patients$age, gender = septic_patients$gender)
 my_list %>% freq(age)
 my_list %>% freq(gender)
                
 
                • 
diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
index c6600eb1..b1ea80a2 100644
--- a/docs/pkgdown.yml
+++ b/docs/pkgdown.yml
@@ -10,7 +10,7 @@ articles:
   WHONET: WHONET.html
   benchmarks: benchmarks.html
   resistance_predict: resistance_predict.html
-last_built: 2020-07-01T09:03Z
+last_built: 2020-07-01T09:22Z
 urls:
   reference: https://msberends.gitlab.io/AMR/reference
   article: https://msberends.gitlab.io/AMR/articles
diff --git a/docs/reference/index.html b/docs/reference/index.html
index 9f5a5abe..f9258253 100644
--- a/docs/reference/index.html
+++ b/docs/reference/index.html
@@ -81,7 +81,7 @@
       
       
         AMR (for R)
-        1.2.0.9019
+        1.2.0.9020