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# Data Set with 500 Isolates - WHONET Example

Source: `R/data.R`
`WHONET.Rd`

This example data set has the exact same structure as an export file from WHONET. Such files can be used with this package, as this example data set shows. The antimicrobial results are from our example_isolates data set. All patient names were created using online surname generators and are only in place for practice purposes.

## Usage

    WHONET

## Format

A tibble with 500 observations and 53 variables:

- `Identification number`
  ID of the sample

- `Specimen number`
  ID of the specimen

- `Organism`
  Name of the microorganism. Before analysis, you should transform this to a valid microbial class, using `as.mo()`.

- `Country`
  Country of origin

- `Laboratory`
  Name of laboratory

- `Last name`
  Fictitious last name of patient

- `First name`
  Fictitious initial of patient

- `Sex`
  Fictitious gender of patient

- `Age`
  Fictitious age of patient

- `Age category`
  Age group, can also be looked up using `age_groups()`

- `Date of admission`
  Date of hospital admission

- `Specimen date`
  Date when specimen was received at laboratory

- `Specimen type`
  Specimen type or group

- `Specimen type (Numeric)`
  Translation of `"Specimen type"`

- `Reason`
  Reason of request with Differential Diagnosis

- `Isolate number`
  ID of isolate

- `Organism type`
  Type of microorganism, can also be looked up using `mo_type()`

- `Serotype`
  Serotype of microorganism

- `Beta-lactamase`
  Microorganism produces beta-lactamase?

- `ESBL`
  Microorganism produces extended spectrum beta-lactamase?

- `Carbapenemase`
  Microorganism produces carbapenemase?

- `MRSA screening test`
  Microorganism is possible MRSA?

- `Inducible clindamycin resistance`
  Clindamycin can be induced?

- `Comment`
  Other comments

- `Date of data entry`
  Date this data was entered in WHONET

- `AMP_ND10:CIP_EE`
  28 different antimicrobials. You can lookup the abbreviations in the antimicrobials data set, or use e.g. `ab_name("AMP")` to get the official name immediately. Before analysis, you should transform this to a valid antimicrobial class, using `as.sir()`.

## Download Our Reference Data

All reference data sets in the AMR package - including information on microorganisms, antimicrobials, and clinical breakpoints - are freely available for download in multiple formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, and Stata.

For maximum compatibility, we also provide machine-readable, tab-separated plain text files suitable for use in any software, including laboratory information systems.

Visit our website for direct download links, or explore the actual files in our GitHub repository.

## Examples

    WHONET
    #> # A tibble: 500 × 53
    #>    `Identification number` `Specimen number` Organism Country         Laboratory
    #>    <chr>                               <int> <chr>    <chr>           <chr>
    #>  1 fe41d7bafa                           1748 SPN      Belgium         National …
    #>  2 91f175ec37                           1767 eco      The Netherlands National …
    #>  3 cc4015056e                           1343 eco      The Netherlands National …
    #>  4 e864b692f5                           1894 MAP      Denmark         National …
    #>  5 3d051fe345                           1739 PVU      Belgium         National …
    #>  6 c80762a08d                           1846 103      The Netherlands National …
    #>  7 8022d3727c                           1628 103      Denmark         National …
    #>  8 f3dc5f553d                           1493 eco      The Netherlands National …
    #>  9 15add38f6c                           1847 eco      France          National …
    #> 10 fd41248def                           1458 eco      Germany         National …
    #> # ℹ 490 more rows
    #> # ℹ 48 more variables: `Last name` <chr>, `First name` <chr>, Sex <chr>,
    #> #   Age <dbl>, `Age category` <chr>, `Date of admission` <date>,
    #> #   `Specimen date` <date>, `Specimen type` <chr>,
    #> #   `Specimen type (Numeric)` <dbl>, Reason <chr>, `Isolate number` <int>,
    #> #   `Organism type` <chr>, Serotype <chr>, `Beta-lactamase` <lgl>, ESBL <lgl>,
    #> #   Carbapenemase <lgl>, `MRSA screening test` <lgl>, …