Presubmission inquiry: datefixR: Fix Really Messy Dates

[nathansam]

Submitting Author Name: Nathan Constantine-Cooke Submitting Author Github Handle: !--author1-->@nathansam<!--end-author1-- Repository: https://github.com/nathansam/datefixR Submission type: Pre-submission Language: en

---

• Paste the full DESCRIPTION file inside a code block below:

Package: datefixR
Title: Fix Really Messy Dates
Version: 0.1.4.9000
Authors@R: person("Nathan",
                  "Constantine-Cooke",
                  email = "nathan.constantine-cooke@ed.ac.uk",
                  role = c("aut", "cre"),
                  comment = c(ORCID = "0000-0002-4437-8713"))
Description: Fixes messy dates in data frames such as those entered via text
  boxes. Standardizes / - and whitespace separation, month abbreviations, and
  year first or day first by converting to R's built-in Date class. Imputes
  missing date or month using user-provided values.  
License: GPL (>= 3)
Depends: R (>= 4.0.0)
Imports: stringr
Language: en-US
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.1.2
URL: https://www.constantine-cooke.com/datefixR/ https://github.com/nathansam/datefixR
BugReports: https://github.com/nathansam/datefixR/issues
Suggests: 
    rmarkdown,
    knitr,
    testthat (>= 3.0.0)
Config/testthat/edition: 3
VignetteBuilder: knitr

Scope

• Please indicate which category or categories from our package fit policies or statistical package categories this package falls under. (Please check an appropriate box below):

  Data Lifecycle Packages

  • [ ] data retrieval

  • [ ] data extraction

  • [ ] database access

  • [x] data munging

  • [ ] data deposition

  • [ ] workflow automation

  • [ ] version control

  • [ ] citation management and bibliometrics

  • [ ] scientific software wrappers

  • [ ] database software bindings

  • [ ] geospatial data

  • [ ] text data

    Statistical Packages

  • [ ] Bayesian and Monte Carlo Routines

  • [ ] Dimensionality Reduction, Clustering, and Unsupervised Learning

  • [ ] Machine Learning

  • [ ] Regression and Supervised Learning

  • [ ] Exploratory Data Analysis (EDA) and Summary Statistics

  • [ ] Spatial Analyses

  • [ ] Time Series Analyses

• Explain how and why the package falls under these categories (briefly, 1-2 sentences). Please note any areas you are unsure of:

datefixR takes date data in which has been stored in many different formats (01/01/2001, 5 April 2020, Dec 2015 etc.) and converts them to R's Date type.

• If submitting a statistical package, have you already incorporated documentation of standards into your code via the srr package?

NA

• Who is the target audience and what are scientific applications of this package?

Any researchers using data entered via a questionnaire which (unfortunately) asked for a date as free-text. Given the nature of this data generation, this mainly affects those who work with human subjects.

• Are there other R packages that accomplish the same thing? If so, how does yours differ or meet our criteria for best-in-category?

lubridate::guess_formats() can be used to guess a date format and lubridate::parse_date_time() calls this function when it attempts to parse a vector into a POSIXct date-time object. However:

1. When a date fails to parse in {lubridate} then the user is simply told how many dates failed to parse. In {datefixR} the user is told the ID (assumed to be the first column by default but can be user-specified) corresponding to the date which failed to parse and reports the considered date: making it much easier to figure out which dates supplied failed to parse and why.
2. When imputing a missing day or month, there is no user-control over this behaviour. For example, when imputing a missing month, the user may wish to impute July, the middle of the year, instead of January. However, January will always be imputed in {lubridate}. In {datefixR}, this behaviour can be controlled by the month.impute argument.
3. These functions require all possible date formats to be specified in the orders argument, which may result in a date format not being considered if the user forgets to list one of the possible formats. By contrast, {datefixR} only needs a format to be specified if month-first is to be preferred over day-first when guessing a date.

linelist::guess_dates() appears to have performed a somewhat similar role. However, this function did not leave the experimental lifecycle phase and the package itself is no longer available on CRAN.

• Any other questions or issues we should be aware of?:

The package is on CRAN with no reverse dependencies.

[jooolia]

Dear @nathansam, Thank you for your pre-submission. Thanks for mentioning linelist::guess_dates(), could you also expand this section and discuss lubridate::guess_formats()? Thanks, Julia

[nathansam]

Thanks @jooolia, Sorry, I should have mentioned that before! I have now added a section on lubridate's date guessing functions above.

[jooolia]

Dear @nathansam, We have determined that this package is in-scope for rOpenSci and we will welcome your full submission. Please add information about the other packages with similar (but not the same) functionality in your Readme. Another editor also mentioned {anytime} as another package worth describing in comparison to yours. Thanks, Julia

[nathansam]

That is great news, thank you! My thanks to you and the rest of the team. I will of course do a full submission ASAP.