qualR: An R package to download Sao Paulo and Rio de Janeiro air pollution data

[quishqa]

Date accepted: 2022-03-08
Submitting Author Name: Mario Gavidia-Calderón
Submitting Author Github Handle: @quishqa
Other Package Authors Github handles: @Schuch666, @mftandra
Repository: https://github.com/quishqa/qualR
Version submitted:0.9.5
Submission type: Standard
Editor: @ldecicco-USGS
Reviewers: @beatrizmilz, @kauedesousa

Due date for @beatrizmilz: 2021-12-01

Due date for @kauedesousa: 2021-12-02
Archive: TBD
Version accepted: TBD

---

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

Package: qualR
Title: An R package to download Sao Paulo and Rio de Janeiro air pollution data
Version: 0.9.5
Authors@R: c(
    person(given = "Mario",
           family = "Gavidia-Calderón",
           role = c("aut", "cre"),
           email = "[email protected]",
           comment = c(ORCID = "0000-0002-7371-1116")),
    person(given = "Maria de Fatima",
           family = "Andrade",
           role = c("ctb", "ths"),
           email = "[email protected]",
           comment = c(ORCID = "0000-0001-5351-8311")),
    person(given = "Daniel",
           family = "Schuch",
           role = c("aut","ctb"),
           email = "[email protected]",
           comment = c(ORCID = "0000-0001-5977-4519")))
Description: A package to download information from CETESB QUALAR and
    MonitorAr systems. It contains function to download different parameters, a set of
    criteria pollutants and the most frequent meteorological parameters used in
    air quality data analysis and air quality model evaluation.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.1.1
Imports: 
    XML,
    httr,
    jsonlite
URL: https://github.com/quishqa/qualR
BugReports: https://github.com/quishqa/qualR/issues
Suggests:
    covr,
    testthat (>= 3.0.0)
Depends: 
    R (>= 3.5.0)
Config/testthat/edition: 3

Scope

• Please indicate which category or categories from our package fit policies this package falls under: (Please check an appropriate box below. If you are unsure, we suggest you make a pre-submission inquiry.):

  • data retrieval
  • data extraction
  • data munging
  • data deposition
  • workflow automation
  • version control
  • citation management and bibliometrics
  • scientific software wrappers
  • field and lab reproducibility tools
  • database software bindings
  • geospatial data
  • text analysis

• Explain how and why the package falls under these categories (briefly, 1-2 sentences):
  Sao Paulo data is available through CETESB QUALAR System which limits the download to one parameter for one air quality station for one year, Rio de Janeiro is available through data.rio.API which is not so user-friendly. qualR downloads multiple parameters for different air quality stations and produces completed ready-to-use data frames (missing hours are padded out with NA) with a date column in POSIXct type that allows temporal aggregation and compatibility with openair package.

• Who is the target audience and what are scientific applications of this package?
  Any researchers that work with air quality and weather data of Sao Paulo and Rio de Janeiro: Meteorologists, Epidemiologists, Environmental engineers, postgraduates students that work in air quality modeling and field measurements campaigns, also stakeholders and the community. This packages facilitates the retrival of Sao Paulo and Rio de Janeiro air quality data, facilitates exploratory data analysis, and enhance code reproducibility.

• Are there other R packages that accomplish the same thing? If so, how does yours differ or meet our criteria for best-in-category?
  koffing retrieves Sao Paulo State air quality data. qualR offers more functionalities (i.e. allows retrieve many parameters from one air quality station, accepts pollutants abbreviations and air quality station names in functions parameters, etc), and returns complete datasets ready to use (no missing hours, concentration in numeric format). qualR also include Rio de Janeiro city and the location of each air quality stations. qualR is more user friendly and it is actively maintainded.

• (If applicable) Does your package comply with our guidance around Ethics, Data Privacy and Human Subjects Research?

• If you made a pre-submission inquiry, please paste the link to the corresponding issue, forum post, or other discussion, or @tag the editor you contacted.

Technical checks

Confirm each of the following by checking the box.

• I have read the guide for authors and rOpenSci packaging guide.

This package:

• does not violate the Terms of Service of any service it interacts with.
• has a CRAN and OSI accepted license.
• contains a README with instructions for installing the development version.
• includes documentation with examples for all functions, created with roxygen2.
• contains a vignette with examples of its essential functions and uses.
• has a test suite.
• has continuous integration, including reporting of test coverage using services such as Travis CI, Coveralls and/or CodeCov.

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Editor check started

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[ropensci-review-bot]

Checks for qualR (v0.9.5)

git hash: 6ca2ad12

• ✔️ Package name is available
• ✔️ has a 'CITATION' file.
• ✔️ has a 'codemeta.json' file.
• ✖️ does not have a 'contributing' file.
• ✔️ uses 'roxygen2'.
• ✔️ 'DESCRIPTION' has a URL field.
• ✔️ 'DESCRIPTION' has a BugReports field.
• ✖️ Package has at no HTML vignettes
• ✖️ These functions do not have examples: [cetesb_aqs.Rd].
• ✔️ Package has continuous integration checks.
• ✔️ Package coverage is 100%.
• ✔️ R CMD check found no errors.
• ✔️ R CMD check found no warnings.

Important: All failing checks above must be addressed prior to proceeding

Package License: MIT + file LICENSE

---

1. Statistical Properties

This package features some noteworthy statistical properties which may need to be clarified by a handling editor prior to progressing.

Details of statistical properties (click to open)

The package has:

• code in R (100% in 12 files) and
• 2 authors
• no vignette
• 4 internal data files
• 3 imported packages
• 9 exported functions (median 35 lines of code)
• 13 non-exported functions in R (median 33 lines of code)

---

Statistical properties of package structure as distributional percentiles in relation to all current CRAN packages
The following terminology is used:

• loc = "Lines of Code"
• fn = "function"
• exp/not_exp = exported / not exported

The final measure (fn_call_network_size) is the total number of calls between functions (in R), or more abstract relationships between code objects in other languages. Values are flagged as "noteworthy" when they lie in the upper or lower 5th percentile.

measure	value	percentile	noteworthy
files_R	12	62.6
files_vignettes	0	0.0	TRUE
files_tests	9	87.3
loc_R	495	44.0
loc_tests	61	26.1
num_vignettes	0	0.0	TRUE
data_size_total	4165	65.9
data_size_median	667	61.4
n_fns_r	22	22.5
n_fns_r_exported	9	38.9
n_fns_r_not_exported	13	19.3
n_fns_per_file_r	1	8.3
num_params_per_fn	7	85.6
loc_per_fn_r	34	88.5
loc_per_fn_r_exp	35	70.3
loc_per_fn_r_not_exp	33	89.7
rel_whitespace_R	24	54.8
rel_whitespace_tests	41	75.1
doclines_per_fn_exp	41	51.1
doclines_per_fn_not_exp	0	0.0	TRUE
fn_call_network_size	34	53.0

---

1a. Network visualisation

Interactive network visualisation of calls between objects in package can be viewed by clicking here

---

2. goodpractice and other checks

Details of goodpractice and other checks (click to open)

3a. Continuous Integration Badges

[]( )

---

3b. goodpractice results

R CMD check with rcmdcheck

R CMD check generated the following note:

1. checking data for non-ASCII characters ... NOTE
   Note: found 40 marked UTF-8 strings

R CMD check generated the following check_fail:

1. rcmdcheck_non_ascii_characters_in_data

Test coverage with covr

Package coverage: 100

Cyclocomplexity with cyclocomp

No functions have cyclocomplexity >= 15

Static code analyses with lintr

lintr found the following 54 potential issues:

message	number of times
Avoid changing the working directory, or restore it in on.exit	2
Lines should not be more than 80 characters.	52

---

Package Versions

package	version
pkgstats	0.0.2.16
pkgcheck	0.0.2.86

---

Editor-in-Chief Instructions:

Processing may not proceed until the items marked with ✖️ have been resolved.

[quishqa]

@ropensci-review-bot help

[ropensci-review-bot]

Hello @quishqa, here are the things you can ask me to do:

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# Show our Code of Conduct
@ropensci-review-bot code of conduct

[quishqa]

Hi!
All items marked as ✖️ have been resolved. We are working on fixing goodpractice checks.

[ldecicco-USGS]

@ropensci-review-bot check package

[ropensci-review-bot]

Thanks, about to send the query.

[ropensci-review-bot]

🚀

Editor check started

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[ropensci-review-bot]

Checks for qualR (v0.9.5)

git hash: ca28ae7b

• ✔️ Package name is available
• ✔️ has a 'CITATION' file.
• ✔️ has a 'codemeta.json' file.
• ✔️ has a 'contributing' file.
• ✔️ uses 'roxygen2'.
• ✔️ 'DESCRIPTION' has a URL field.
• ✔️ 'DESCRIPTION' has a BugReports field.
• ✔️ Package has at least one HTML vignette
• ✔️ All functions have examples.
• ✔️ Package has continuous integration checks.
• ✔️ Package coverage is 100%.
• ✔️ R CMD check found no errors.
• ✔️ R CMD check found no warnings.

Package License: MIT + file LICENSE

---

1. Statistical Properties

This package features some noteworthy statistical properties which may need to be clarified by a handling editor prior to progressing.

Details of statistical properties (click to open)

The package has:

• code in R (100% in 12 files) and
• 2 authors
• 1 vignette
• 4 internal data files
• 3 imported packages
• 9 exported functions (median 35 lines of code)
• 13 non-exported functions in R (median 33 lines of code)

---

Statistical properties of package structure as distributional percentiles in relation to all current CRAN packages
The following terminology is used:

• loc = "Lines of Code"
• fn = "function"
• exp/not_exp = exported / not exported

The final measure (fn_call_network_size) is the total number of calls between functions (in R), or more abstract relationships between code objects in other languages. Values are flagged as "noteworthy" when they lie in the upper or lower 5th percentile.

measure	value	percentile	noteworthy
files_R	12	62.6
files_vignettes	0	0.0	TRUE
files_tests	9	87.3
loc_R	509	45.0
loc_tests	65	27.3
num_vignettes	1	60.7
data_size_total	4165	65.9
data_size_median	667	61.4
n_fns_r	22	22.5
n_fns_r_exported	9	38.9
n_fns_r_not_exported	13	19.3
n_fns_per_file_r	1	8.3
num_params_per_fn	7	85.6
loc_per_fn_r	34	88.5
loc_per_fn_r_exp	35	70.3
loc_per_fn_r_not_exp	33	89.7
rel_whitespace_R	23	54.8
rel_whitespace_tests	38	75.1
doclines_per_fn_exp	42	52.5
doclines_per_fn_not_exp	0	0.0	TRUE
fn_call_network_size	34	53.0

---

1a. Network visualisation

Interactive network visualisation of calls between objects in package can be viewed by clicking here

---

2. goodpractice and other checks

Details of goodpractice and other checks (click to open)

3a. Continuous Integration Badges

[]( )

---

3b. goodpractice results

R CMD check with rcmdcheck

R CMD check generated the following note:

1. checking data for non-ASCII characters ... NOTE
   Note: found 40 marked UTF-8 strings

R CMD check generated the following check_fail:

1. rcmdcheck_non_ascii_characters_in_data

Test coverage with covr

Package coverage: 100

Cyclocomplexity with cyclocomp

No functions have cyclocomplexity >= 15

Static code analyses with lintr

lintr found the following 4 potential issues:

message	number of times
Avoid changing the working directory, or restore it in on.exit	4

---

Package Versions

package	version
pkgstats	0.0.2.16
pkgcheck	0.0.2.86

---

Editor-in-Chief Instructions:

This package is in top shape and may be passed on to a handling editor

[ldecicco-USGS]

Thanks @quishqa ! The package is looking great. I'll be taking the editor role.

@ropensci-review-bot assign @ldecicco-USGS as editor

[ldecicco-USGS]

@ropensci-review-bot assign @ldecicco-USGS as editor

[ropensci-review-bot]

Assigned! @ldecicco-USGS is now the editor

[ldecicco-USGS]

Hi @quishqa , I'm still asking around for reviewers (I've reached out to a few that have declined because they are busy). I just wanted to let you know it's taking a bit longer than usual, sorry about that.

[quishqa]

Hi @ldecicco-USGS , thanks for the update. We're looking forward to the review.

[ldecicco-USGS]

@ropensci-review-bot assign @beatrizmilz as reviewer

[ldecicco-USGS]

@ropensci-review-bot add @beatrizmilz to reviewers

[ropensci-review-bot]

@beatrizmilz added to the reviewers list. Review due date is 2021-12-01. Thanks @beatrizmilz for accepting to review! Please refer to our reviewer guide.

[ropensci-review-bot]

@beatrizmilz: If you haven't done so, please fill this form for us to update our reviewers records.

[ldecicco-USGS]

@ropensci-review-bot add @kauedesousa to reviewers

[ropensci-review-bot]

@kauedesousa added to the reviewers list. Review due date is 2021-12-02. Thanks @kauedesousa for accepting to review! Please refer to our reviewer guide.

[kauedesousa]

Dear @ldecicco-USGS and @quishqa here goes my comments on the package. This is a nice one. Congrats!!

Package Review

• Briefly describe any working relationship you have (had) with the package authors.
• As the reviewer I confirm that there are no conflicts of interest for me to review this work (if you are unsure whether you are in conflict, please speak to your editor before starting your review).

Documentation

The package includes all the following forms of documentation:

• A statement of need: clearly stating problems the software is designed to solve and its target audience in README
• Installation instructions: for the development version of package and any non-standard dependencies in README
• Vignette(s): demonstrating major functionality that runs successfully locally
• Function Documentation: for all exported functions
• Examples: (that run successfully locally) for all exported functions
• Community guidelines: including contribution guidelines in the README or CONTRIBUTING, and DESCRIPTION with URL, BugReports and Maintainer (which may be autogenerated via Authors@R).

Functionality

• Installation: Installation succeeds as documented.
• Functionality: Any functional claims of the software been confirmed.
• Performance: Any performance claims of the software been confirmed.
• Automated tests: Unit tests cover essential functions of the package and a reasonable range of inputs and conditions. All tests pass on the local machine.
• Packaging guidelines: The package conforms to the rOpenSci packaging guidelines.

Estimated hours spent reviewing: 5

• Should the author(s) deem it appropriate, I agree to be acknowledged as a package reviewer ("rev" role) in the package DESCRIPTION file.

---

Review Comments

• Datasets monitor_ar_aqs and monitor_ar_param don't match with the general naming used for the functions. I suggest that you rename these files to match with your naming logic. You may rename like, ArStation and ArParameters
• Same for the CETESB data sets
• Part of your functions (for CETESB) need a previous account with CETESB, and you only mention that by the end of your vignette. You need to mention that on the description of the functions CetesbRetrieveMet() and the other related.
• Your vignette don't run smoothly because you call the package openair with :: without explicitly mentioning it with library(openair). You should call the package with library().
• In line 114 of /R/CetesbRetrieve.R you start with an if() and then a else with another if(). I think that these statements are very difficult to understand and to fix. Maybe you can use only if()s and stress on the possible outcomes that the call may return to you.
• You test if the functions are returning the right dimensions of your expected data frame. But you don't test whether the outcome is the correct data. Maybe you can download a small data set from the server and put it in the sysdata.rda and validate it with the output of your functions.
• Fix the typo in line 16 of file /R/CetesbRetrieveMet.R
• I recommend to put the paper files in /inst/paper so your main directory is more organized. Same for the png files.
• Remove README.Rmd and keep only README.md
• /data-raw/ could be placed inside /data/
• Remove LICENSE.md
• In the DESCRIPTION file, put the links for ETESB QUALAR and MonitorAr systems if any inside a <>, like this https://cetesb.sp.gov.br/ar/qualar/ is very likely that CRAN will ask you to do that.
• Make a file called qualR.R in the \R directory, it makes a nice description of your package. There are some complex versions like this https://github.com/ropensci/rgbif/blob/master/R/rgbif-package.r or simplified versions like this https://github.com/ropensci/chirps/blob/master/R/chirps.R
• The package is nice and delivers what is promissed. Congrats!!

Session info

─ Session info  🍰  👨‍⚕️  📱   ────────────────────────────────────────────────────────────────────────────────────────
 hash: shortcake, man health worker, mobile phone

 setting  value
 version  R version 4.1.0 (2021-05-18)
 os       macOS 12.0.1
 system   x86_64, darwin17.0
 ui       RStudio
 language (EN)
 collate  en_US.UTF-8
 ctype    en_US.UTF-8
 tz       Europe/Oslo
 date     2021-12-14
 rstudio  1.4.1716 Juliet Rose (desktop)
 pandoc   2.9.1.1 @ /usr/local/bin/pandoc

─ Packages ──────────────────────────────────────────────────────────────────────────────────────────────────────────
 package     * version  date (UTC) lib source
 cachem        1.0.6    2021-08-19 [1] CRAN (R 4.1.0)
 callr         3.7.0    2021-04-20 [1] CRAN (R 4.1.0)
 cli           3.1.0    2021-10-27 [1] CRAN (R 4.1.0)
 crayon        1.4.2    2021-10-29 [1] CRAN (R 4.1.0)
 curl          4.3.2    2021-06-23 [1] CRAN (R 4.1.0)
 desc          1.4.0    2021-09-28 [1] CRAN (R 4.1.0)
 devtools    * 2.4.2    2021-06-07 [1] CRAN (R 4.1.0)
 ellipsis      0.3.2    2021-04-29 [1] CRAN (R 4.1.0)
 fastmap       1.1.0    2021-01-25 [1] CRAN (R 4.1.0)
 fs            1.5.0    2020-07-31 [1] CRAN (R 4.1.0)
 glue          1.4.2    2020-08-27 [1] CRAN (R 4.1.0)
 httr          1.4.2    2020-07-20 [1] CRAN (R 4.1.0)
 jsonlite      1.7.2    2020-12-09 [1] CRAN (R 4.1.0)
 knitr         1.36     2021-09-29 [1] CRAN (R 4.1.0)
 lifecycle     1.0.1    2021-09-24 [1] CRAN (R 4.1.0)
 magrittr      2.0.1    2020-11-17 [1] CRAN (R 4.1.0)
 memoise       2.0.0    2021-01-26 [1] CRAN (R 4.1.0)
 pkgbuild      1.2.0    2020-12-15 [1] CRAN (R 4.1.0)
 pkgload       1.2.3    2021-10-13 [1] CRAN (R 4.1.0)
 prettyunits   1.1.1    2020-01-24 [1] CRAN (R 4.1.0)
 processx      3.5.2    2021-04-30 [1] CRAN (R 4.1.0)
 ps            1.6.0    2021-02-28 [1] CRAN (R 4.1.0)
 purrr         0.3.4    2020-04-17 [1] CRAN (R 4.1.0)
 qualR       * 0.9.5    2021-12-14 [1] Github (quishqa/qualR@dc15bd0)
 R6            2.5.1    2021-08-19 [1] CRAN (R 4.1.0)
 remotes       2.4.1    2021-09-29 [1] CRAN (R 4.1.0)
 rlang         0.4.12   2021-10-18 [1] CRAN (R 4.1.0)
 roxygen2    * 7.1.2    2021-09-08 [1] CRAN (R 4.1.0)
 rprojroot     2.0.2    2020-11-15 [1] CRAN (R 4.1.0)
 rstudioapi    0.13     2020-11-12 [1] CRAN (R 4.1.0)
 sessioninfo   1.2.1    2021-11-02 [1] CRAN (R 4.1.0)
 stringi       1.7.5    2021-10-04 [1] CRAN (R 4.1.0)
 stringr       1.4.0    2019-02-10 [1] CRAN (R 4.1.0)
 testthat    * 3.1.0    2021-10-04 [1] CRAN (R 4.1.0)
 usethis     * 2.1.3    2021-10-27 [1] CRAN (R 4.1.0)
 withr         2.4.2    2021-04-18 [1] CRAN (R 4.1.0)
 xfun          0.27     2021-10-18 [1] CRAN (R 4.1.0)
 XML           3.99-0.8 2021-09-17 [1] CRAN (R 4.1.0)
 xml2          1.3.2    2020-04-23 [1] CRAN (R 4.1.0)

 [1] /Library/Frameworks/R.framework/Versions/4.1/Resources/library

[quishqa]

Thanks a lot @kauedesousa for your review will solve the observations in the next days.

[ldecicco-USGS]

Thanks again @kauedesousa and @beatrizmilz for the great reviews. @quishqa , and updates on the responses?

[quishqa]

Hi everybody! We hope to have everything ready before the 28th.

[quishqa]

Sorry for the (very) late reply. Thanks a lot to @ldecicco-USGS and to @beatrizmilz and @kauedesousa for the
very exhaustive review. Now the package is definitely better and we also learned a lot
about building packages in R.

Here are the answers to each observation following the commit where we fix them.

Response to @beatrizmilz

• Consistent naming styles: it would be better to choose a language (English), and a coding style (ex. snake case) and use them in all function names, arguments, and names of columns in the datasets returned.

Response: Now all function names are snake case and the names of columns are the most common in atmospheric sciences.
See ropensci/qualR@10f2dde
And ropensci/qualR@388c779

• The tests can be improved. Consider also using GitHub Actions to perform an automated check.

Response: We updated the tests to check also number of rows, to check if output is written, to check if variables (a pollutant) mean is inside a range, and to check the class of each columns.
See ropensci/qualR@85cc521
And
ropensci/qualR@036a8e1

• Files in the root directory: some of the files do not seem fit to be stored there (such as the files related to the paper), and some need to be ignored in the build of the package. I wrote in more detail in the report.

Response: Paper folder moved to inst/paper ropensci/qualR@2d03ff4
Also we updated our .Rbuildignore file see: ropensci/qualR@43df95a

• The spell-check found some typos that could be corrected.

Response: Corrected in ropensci/qualR@57d14d0

• I wrote in the report some ideas for the vignettes, but they are only suggestions to make it easier for people to use the data.

Response: We are not used to work with tidyverse. Nervertheless we add one example in the vignette. See ropensci/qualR@4a78c93

• Modifying directories using setwd() is not something recommended in the book R Packages

Response: By adding the csv_path argument we don't need to used setwd() anymore. See ropensci/qualR@f7f8055
and ropensci/qualR@b0d7665

Other recommendations from full report

• Add rOpenSci Review badge

Response: Added in ropensci/qualR@e6af4d1

• The CITATION file exists. There are releases on GitHUb, but I did not find any reference to Zenodo. Reference. There is 0 results searching for qualR on Zenodo: https://zenodo.org/search?page=1&size=20&q=qualR . Read more how to do it and have a DOI for your package on the GitHub documentation.

Response: DOI created in ropensci/qualR@9e4d7f0

• Code of conduct: in the book, is recommended to use a code of conduct (CoC), and I did not find that information in the README.

Response: Created in ropensci/qualR@bcce5b5

• R/sysdata.rda should be used to internal datasets.

Response: Yes these dataset is for internal use. It has the name of stations with and without diacritics. Using Tatui is the same as using Tatuí

• Please review the links in the vignette, there is broken links (such as CETESB QUALAR System, data.rio).

Response: Corrected in ropensci/qualR@f3d4d2a

• MonitorArRetrievePol(), MonitorArRetrieveMet() and CetesbRetrieveMetPol() - The names of the columns of the dataset returned are in a good pattern (all in English and snake case). The column classes I think it would be better if the numeric variables (such as the air parameters) returned numeric/double (now some of them are lgl because there is only NA’s).

Response: Columns names from returned dataset standarized. See ropensci/qualR@388c779 .
Now numeric variables are returned as numeric even when there is only NA. See ropensci/qualR@cb808be

• Console messages - It is not recommended to use cat() to communicate with the user of the functions

Response: Now we use message(). See ropensci/qualR@0c90cfd

• IDEA - When the function is storing the csv with to_csv = TRUE, it would be nice to have an argument to write the path where the csv will be saved.

Response: Accepted in ropensci/qualR@f7f8055. It helped to avoid using setwd() on tests.

• IDEA - I think it would be nice to be able to search more than one station in the functions.

Response: We put a way to do it in the README section in https://github.com/quishqa/qualR#a-variable-from-all-cetesb-aqs

• All the tests passed. There are only a few tests. I recommend the authors to write more expectations with expect_*(), such as: expect the class of the result, the class of the columns in the dataset.

Response: Now we evaluate classes. See ropensci/qualR@85cc521

• There is a test are not testing anything related to the package: In test-CetesbRetrieveParam.R, the only expectation is expect_equal(2 * 2, 4).

Response: Corrected in ropensci/qualR@85cc521

• There is no GitHub action to check the package consistently.

Response: Added in ropensci/qualR@60592c9

Response to @kauedesousa

• Datasets monitor_ar_aqs and monitor_ar_param don't match with the general naming used for the functions. I suggest that you rename these files to match with your naming logic. You may rename like, ArStation and ArParameters

Response: Now we changed all function names using snake case. See ropensci/qualR@10f2dde

• Same for the CETESB data sets

Response: Now returned datasets have the most common names in atmospheric sciences. See ropensci/qualR@388c779

• Your vignette don't run smoothly because you call the package openair with :: without explicitly mentioning it with library(openair). You should call the package with library().

Response: Added in ropensci/qualR@f3d4d2a

• In line 114 of /R/CetesbRetrieve.R you start with an if() and then a else with another if(). I think that these statements are very difficult to understand and to fix. Maybe you can use only if()s and stress on the possible outcomes that the call may return to you.

Response: Fixed in ropensci/qualR@985714f

• You test if the functions are returning the right dimensions of your expected data frame. But you don't test whether the outcome is the correct data. Maybe you can download a small data set from the server and put it in the sysdata.rda and validate it with the output of your functions.

Response: We updated the tests to check also number of rows, to check if output is written, to check if variables (a pollutant) mean is inside a range, and to check the class of each columns.
See ropensci/qualR@85cc521
And
ropensci/qualR@036a8e1

• Fix the typo in line 16 of file /R/CetesbRetrieveMet.R

Response: Corrected in ropensci/qualR@57d14d0

• I recommend to put the paper files in /inst/paper so your main directory is more organized. Same for the png files.

Response: Moved in ropensci/qualR@2d03ff4

• Remove README.Rmd and keep only README.md

Response: Removed in ropensci/qualR@b32c6ff

• /data-raw/ could be placed inside /data/

Response: That folder was created when using the function usethis::use_data_raw() during the package development.

• Remove LICENSE.md

Response: We still have doubts about which one we should remove LICENSE.md has more information.

• In the DESCRIPTION file, put the links for ETESB QUALAR and MonitorAr systems if any inside a <>, like this https://cetesb.sp.gov.br/ar/qualar/ is very likely that CRAN will ask you to do that.

Response: Added in ropensci/qualR@406cfc6

• Make a file called qualR.R in the \R directory, it makes a nice description of your package.

Response: Created in ropensci/qualR@30b61db

[beatrizmilz]

Hi @quishqa ! I'm happy to know that the review was usefull. Congratulations for the extensive work!
Seems like the website was not fully updated. Some of the pages on the reference are returning error 404, in the case when the function names were changed: https://quishqa.github.io/qualR/reference/cetesb_retrieve_param.html
Probably using pkgdown::build_site() would fix it :)

[quishqa]

Thanks for noticing this. It's weird because the manual from the datasets are OK but only the functions (which the names were changed) are presenting this error. I already do pkgdown::build_site() . Locally it works but on the deployed web it does not work. I'm going to do a little more research.

[quishqa]

Dear all, the returning 404 error was fixed in ropensci/qualR@6e4ce0d

[beatrizmilz]

Hi Mario! I checked here and the website is working :) Congratulations.

Congratulations for the extensive work.

About the vignette, I'm glad that you added an example with ggplot2! ggplot2 is an great package to create visualizations, and enables us to create elegant graphs with the data that qualR returns.

About the other suggestions and comments that I wrote, seems like they all have been considered. devtools::check() passed as well.

Tests

I still think that the tests could be improved. I wrote some comments and I hope they can be helpfull if you want to expand the testing in the package:

• As @kauedesousa have said, is good to test whether the outcome is the correct data. One function that you can try is expect_snapshot(): in the first time you use it, it will save the expected outcome and will check in the future if the results are still the expected, comparing with what was saved.

• It seems to me that not all functions have tests consistently: some of the functions have more extensive tests and others tests only the number of rows and columns for example. Having good tests in all functions helps to find bugs in the future.

• Also, I think is a good idea to improve the name of the tests, because if it breaks, is easier to understand which is in the check log (some of them are test_that("multiplication works", {). As said in R Packages book, "The main thing is that the message associated with the test should be informative so that you can quickly narrow down the source of the problem." (reference). But this should be a quick fix.

• I really like this chapter about tests in the R Packages book!

---

Again, congratulations Mario!

[quishqa]

Thanks again for the feedback! We updated the test for all the functions we evaluated dims. values and classes,
see ropensci/qualR@29eb915
and ropensci/qualR@3d3aaf3

Also, we updated the test messages in ropensci/qualR@0a6b148

[kauedesousa]

I think the updates address our comments. It looks fine with me.

[quishqa]

Dear @ldecicco-USGS , @beatrizmilz , and @kauedesousa , What is the status of the review? do you need any extra information or correction?

[ldecicco-USGS]

Sorry about that. Everything looks great! I'm heading out of town for the weekend, but will kick off the approval process on Monday assuming @beatrizmilz and @kauedesousa don't have any objections.

[kauedesousa]

No objection. I recommend the approval. I just wonder why you didn't submit it with a paper for JOSS. Anyways, thanks for opportunity to review the R package.

[beatrizmilz]

I also recommend the approval!

[ldecicco-USGS]

@ropensci-review-bot approve qualR

[ropensci-review-bot]

Approved! Thanks @quishqa for submitting and @beatrizmilz, @kauedesousa for your reviews! 😁

To-dos:

• Transfer the repo to rOpenSci's "ropensci" GitHub organization under "Settings" in your repo. I have invited you to a team that should allow you to do so.
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[maelle]

@quishqa I've just noticed this hasn't been transferred yet, do you need any help?

[quishqa]

Hi @maelle, actually we do. To do the first task we only need to follow this, right? And we don't know where we need to do the @ropensci-review-bot finalize transfer of <package-name> comment?

Thanks!

[maelle]

Yes regarding the repo transfer!

Then the comment @ropensci-review-bot finalize transfer of qualR needs to be put here in an issue comment.

Thank you and have a good week-end!

[quishqa]

@ropensci-review-bot finalize transfer of qualR

[ropensci-review-bot]

Transfer completed. The qualR team is now owner of the repository

[quishqa]

Hi @beatrizmilz and @kauedesousa , is it ok for you if we can add you to the DESCRIPTION file? We'll feel very honored.

[kauedesousa]

that is ok with me @quishqa

[beatrizmilz]

It is ok with me too @quishqa !