yfR: Downloads and Organizes Financial Data from Yahoo Finance #523

msperlin · 2022-03-30T19:13:17Z

Date accepted: 2022-06-21

Submitting Author Name: Marcelo Perlin
Submitting Author Github Handle: @msperlin
Other Package Authors Github handles: (comma separated, delete if none)
Repository: https://github.com/msperlin/yfR
Version submitted: 0.0.1
Submission type: Standard
Editor: @melvidoni
Reviewers: @s3alfisc, @thisisnic

Due date for @s3alfisc: 2022-05-29

Due date for @thisisnic: 2022-06-13

Archive: TBD
Version accepted: TBD
Language: en

Paste the full DESCRIPTION file inside a code block below:

Package: yfR
Title: Downloads and Organizes Financial Data from Yahoo Finance
Version: 0.0.1
Authors@R: person("Marcelo", "Perlin", email = "[email protected]", role = c("aut", "cre"))
Description: Facilitates download of financial data from Yahoo Finance <https://finance.yahoo.com/>, 
 a vast repository of stock price data across multiple financial exchanges. The package offers a local caching system
 and support for parallel computation.
URL: https://github.com/msperlin/yfR
BugReports: https://github.com/msperlin/yfR/issues
Depends:
    R (>= 4.1)
Imports: stringr, curl, tidyr, 
    lubridate, furrr, purrr, future, tibble, zoo,
    cli, readr, rvest, dplyr, quantmod
License: MIT + file LICENSE
LazyData: true
RoxygenNote: 7.1.2
Suggests: 
    knitr,
    rmarkdown,
    testthat (>= 3.0.0),
    ggplot2,
    covr
VignetteBuilder: knitr
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):

Package yfR retrieves and organizes data from Yahoo Finance, a large repository for stock price data.

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

Target audience are students, researchers and industry practioneers in the field of Finance and Economics.

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

Package yfR is the second and backwards-incompatible version of BatchGetSymbols, also developed by me. My plan is to first deprecate BatchGetSymbols and later remove it from CRAN and archive it in Github.

Moreover, there are other packages, such as quantmod, that downloads data from Yahoo Finance, but none with similar features to yfR and BatchGetSymbols.

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

Yes.

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.
Explain reasons for any pkgcheck items which your package is unable to pass.

Unfortinately, I was not able to run pkgcheck locally as I was unable to install (or make) dependency ctags in my Linux Mint 20.3 machine. Nonetheless, I read through and followed all guidelines available in the manual.

Technical checks

Confirm each of the following by checking the box.

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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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ropensci-review-bot · 2022-03-30T19:13:18Z

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ropensci-review-bot · 2022-03-30T19:26:33Z

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ropensci-review-bot · 2022-03-31T09:29:24Z

Checks for yfR (v0.0.1)

git hash: c345549c

✔️ Package name is available
✔️ 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 no continuous integration checks.
✔️ Package coverage is 87.8%.
✔️ 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 8 files) and
1 authors
1 vignette
no internal data file
14 imported packages
6 exported functions (median 16 lines of code)
34 non-exported functions in R (median 12 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

All parameters are explained as tooltips in the locally-rendered HTML version of this report generated by the checks_to_markdown() function

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	8	50.7
files_vignettes	3	92.4
files_tests	5	81.7
loc_R	779	61.1
loc_vignettes	160	41.2
loc_tests	184	53.0
num_vignettes	1	64.8
n_fns_r	40	49.3
n_fns_r_exported	6	29.1
n_fns_r_not_exported	34	56.6
n_fns_per_file_r	3	45.9
num_params_per_fn	2	11.9
loc_per_fn_r	14	45.4
loc_per_fn_r_exp	16	38.0
loc_per_fn_r_not_exp	12	42.0
rel_whitespace_R	29	73.7
rel_whitespace_vignettes	65	65.5
rel_whitespace_tests	56	72.7
doclines_per_fn_exp	20	13.8
doclines_per_fn_not_exp	0	0.0	TRUE
fn_call_network_size	37	59.9

1a. Network visualisation

Click to see the interactive network visualisation of calls between objects in package

2. `goodpractice` and other checks

Details of goodpractice and other checks (click to open)

3b. `goodpractice` results

`R CMD check` with rcmdcheck

rcmdcheck found no errors, warnings, or notes

Test coverage with covr

Package coverage: 87.78

Cyclocomplexity with cyclocomp

The following functions have cyclocomplexity >= 15:

function	cyclocomplexity
yf_get	23
yf_get_single_ticker	22

Static code analyses with lintr

lintr found the following 2 potential issues:

message	number of times
Avoid library() and require() calls in packages	2

Package Versions

package	version
pkgstats	0.0.3.96
pkgcheck	0.0.2.276

Editor-in-Chief Instructions:

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

mpadge · 2022-03-31T09:36:17Z

@jooolia The faling check is just because the README does not have a CI badge. @msperlin Could you please add an R CMD check badge to your readme? (We check for CI via badges rather than workflow results, because we do accept submissions from arbitrary code-hosting platforms, not just GitHub.) Thanks!

msperlin · 2022-03-31T11:02:54Z

Good morning.

Sure, I just added the R-CMD badge.

jooolia · 2022-04-01T12:03:28Z

@ropensci-review-bot check package

ropensci-review-bot · 2022-04-01T12:03:29Z

Thanks, about to send the query.

ropensci-review-bot · 2022-04-01T12:03:32Z

🚀

Editor check started

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ropensci-review-bot · 2022-04-01T12:15:28Z

Oops, something went wrong with our automatic package checks. Our developers have been notified and package checks will appear here as soon as we've resolved the issue. Sorry for any inconvenience.

ropensci-review-bot · 2022-04-01T13:31:05Z

Checks for yfR (v0.0.1)

git hash: 1ee2f6f5

✔️ Package name is available
✔️ 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 87.8%.
✔️ R CMD check found no errors.
✔️ R CMD check found no warnings.

Package License: MIT + file LICENSE

1. Package Dependencies

Details of Package Dependency Usage (click to open)

The table below tallies all function calls to all packages ('ncalls'), both internal (r-base + recommended, along with the package itself), and external (imported and suggested packages). 'NA' values indicate packages to which no identified calls to R functions could be found. Note that these results are generated by an automated code-tagging system which may not be entirely accurate.

type	package	ncalls
internal	base	69
internal	yfR	17
internal	utils	3
imports	dplyr	11
imports	purrr	5
imports	readr	5
imports	stringr	4
imports	rvest	3
imports	tidyr	2
imports	lubridate	2
imports	furrr	2
imports	future	2
imports	tibble	1
imports	zoo	1
imports	quantmod	1
imports	curl	NA
imports	cli	NA
suggests	knitr	NA
suggests	rmarkdown	NA
suggests	testthat	NA
suggests	ggplot2	NA
suggests	covr	NA
linking_to	NA	NA

Click below for tallies of functions used in each package. Locations of each call within this package may be generated locally by running 's <- pkgstats::pkgstats(<path/to/repo>)', and examining the 'external_calls' table.

base

c (6), file.path (5), as.Date (4), min (4), paste0 (4), data.frame (3), file.exists (3), length (3), list (3), seq (3), as.character (2), as.numeric (2), for (2), max (2), names (2), options (2), rep (2), switch (2), tempdir (2), as.POSIXct (1), class (1), file (1), is.na (1), lapply (1), list.files (1), order (1), seq_along (1), setdiff (1), sum (1), Sys.Date (1), Sys.getenv (1), which (1)

yfR

fix_ticker_name (2), get_morale_boost (2), set_cli_msg (2), yf_get_available_indices (2), calc_ret (1), date_to_unix (1), fct_format_wide (1), unix_to_date (1), yf_get (1), yf_get_available_collections (1), yf_get_ibov_stocks (1), yf_get_index_comp (1), yf_get_single_ticker (1)

dplyr

first (3), bind_rows (2), tibble (2), filter (1), lag (1), mutate (1), rename (1)

purrr

map (2), map_chr (2), pmap (1)

readr

read_rds (4), write_rds (1)

stringr

fixed (1), str_c (1), str_detect (1), str_split (1)

rvest

html_nodes (2), html_table (1)

utils

data (2), capture.output (1)

furrr

furrr_options (2)

future

availableCores (1), plan (1)

lubridate

wday (2)

tidyr

all_of (1), pivot_wider (1)

quantmod

getSymbols (1)

tibble

tibble (1)

zoo

index (1)

2. 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 8 files) and
1 authors
1 vignette
no internal data file
14 imported packages
6 exported functions (median 16 lines of code)
34 non-exported functions in R (median 12 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

All parameters are explained as tooltips in the locally-rendered HTML version of this report generated by the checks_to_markdown() function

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	8	50.7
files_vignettes	3	92.4
files_tests	5	81.7
loc_R	779	61.1
loc_vignettes	160	41.2
loc_tests	184	53.0
num_vignettes	1	64.8
n_fns_r	40	49.3
n_fns_r_exported	6	29.1
n_fns_r_not_exported	34	56.6
n_fns_per_file_r	3	45.9
num_params_per_fn	2	11.9
loc_per_fn_r	14	45.4
loc_per_fn_r_exp	16	38.0
loc_per_fn_r_not_exp	12	42.0
rel_whitespace_R	29	73.7
rel_whitespace_vignettes	65	65.5
rel_whitespace_tests	56	72.7
doclines_per_fn_exp	20	13.8
doclines_per_fn_not_exp	0	0.0	TRUE
fn_call_network_size	37	59.9

2a. Network visualisation

Click to see the interactive network visualisation of calls between objects in package

3. `goodpractice` and other checks

Details of goodpractice and other checks (click to open)

3a. Continuous Integration Badges

GitHub Workflow Results

name	conclusion	sha	date
pages build and deployment	success	1ee2f6	2022-03-31
pkgdown	success	51af0f	2022-03-30
R-CMD-check	success	1ee2f6	2022-03-31
render-rmarkdown	failure	f3dbe5	2022-03-30
test-coverage	success	1ee2f6	2022-03-31

3b. `goodpractice` results

`R CMD check` with rcmdcheck

rcmdcheck found no errors, warnings, or notes

Test coverage with covr

Package coverage: 87.78

Cyclocomplexity with cyclocomp

The following functions have cyclocomplexity >= 15:

function	cyclocomplexity
yf_get	23
yf_get_single_ticker	22

Static code analyses with lintr

lintr found the following 2 potential issues:

message	number of times
Avoid library() and require() calls in packages	2

Package Versions

package	version
pkgstats	0.0.4.4
pkgcheck	0.0.3.6

Editor-in-Chief Instructions:

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

jooolia · 2022-04-01T20:06:19Z

Dear @msperlin,
Thank you for your submission. The package has passed all of the automated package checks and the test coverage is good.
Could you expand a bit more on how this package differs from quantmod and tidyquant?
Thanks, Julia

msperlin · 2022-04-02T11:05:03Z

Good morning Julia,

The main goal of yfR is to help user download large ammounts of data from Yahoo Finance (YF).

Packages quantmod and tidyquant also offers a function for downloading price data from YF, but only that. Besides importing data, yfR offers the following functionalities:

Organization and clean up of data
- Users can set a threshold for what is "bad" data with respect to matching dates to a benchmark dataset (SP500 is usually used);
- Users can also ask for "complete data", where all missing dates are set as NA for later substitution;
- Log or arithmetic returns, much used in research, are also calculated by default;
- User can aggregate the data to weekly, monthly or yearly, always keeping the same data structure.
smarter downloads
- A local (and smart) session-persistent caching system is implemented. This means that, within a session, the data is never downloaded twice and only missing portions of data are downloaded;
- Support for parallel computing. Users can easily set up concurrent R sessions for faster download of data.
Practicality
- yfR innovates with a "collection" system, where one can easily import a collection of tickers such as the SP500 composition in a single function call.

jooolia · 2022-04-03T19:03:29Z

Thank you @msperlin, I am discussing with the other editors and will get back to you. Thanks, Julia

jooolia · 2022-04-29T08:26:14Z

Thanks for your patience @msperlin. The fit seems to be good for us and I am now looking for a handling editor.
Thanks, Julia

msperlin · 2022-04-29T10:57:45Z

Great, thanks @jooolia.

jooolia · 2022-05-01T20:31:48Z

@ropensci-review-bot assign @melvidoni as editor

ropensci-review-bot · 2022-05-01T20:31:50Z

Assigned! @melvidoni is now the editor

melvidoni · 2022-05-01T20:54:31Z

@ropensci-review-bot seeking reviewers

ropensci-review-bot · 2022-05-01T20:54:31Z

Please add this badge to the README of your package repository:

[![Status at rOpenSci Software Peer Review](https://badges.ropensci.org/523_status.svg)](https://github.com/ropensci/software-review/issues/523)

Furthermore, if your package does not have a NEWS.md file yet, please create one to capture the changes made during the review process. See https://devguide.ropensci.org/releasing.html#news

msperlin · 2022-05-02T11:02:45Z

Thanks. The badge is added in dc712f4abac246604721ed7f2926f9794e4e7f99 and the news file already exists.

msperlin · 2022-06-07T14:20:51Z

Dear @thisisnic, please find my replies below.

Again, thanks for the time reviewing my package. I've made many changes based on your comments. All changes are in the main branch.

Review Comments

Overall, I think this is an excellent package and I especially appreciate that it both retrieves the data and puts it into tidy format - as someone who's taught workshops in the past, this kind of thing is really helpful!

Thanks! I'm glad you enjoyed using it.

As @s3alfisc did such a good job of covering areas around design and possible extensions, I thought I'd instead focus on code review, and areas that I might tweak to ensure the code is as maintainable as possible. A lot of the comments below are stylistic, or just questions, and so feel free to take or leave as many of them as you wish.

The only point which I think definitely does need addressing is mentioned in the comment above which references an issue opened on the repo - adding a minimum version of quantmod to the DESCRIPTION file, as otherwise the examples shown in the vignette fail to run correctly.

Yes, this is fixed in the latest commit 2749f6fbdad562fe6f963e409470916d58f6fdb2.

This is my first review, so I hope this is as expected, and if there are any areas which I've missed or focussed on too much, I'm happy to receive feedback on that.

Comments on yf_get.R

This is well documented. There are places where I might choose to shorten parameter names to make them more easily memorable, but this is a personal preference rather than a recommendation. The code is skimmable, the comments help guide me through what's happening, variable names are intuitive, and error messages are informative.

Thanks.

A few typos: "cant" instead of "can't".

Fixed.

Some error messages have the text "ERROR" in them - I'd recommend removing these, as this is duplicating the in-built error text, e.g. it outputs as Error: ERROR: cant change class of last_date to 'Date'

Fixed.

I see some code which edits a dplyr option: options(dplyr.summarise.inform = FALSE) and later resets it: options(dplyr.summarise.inform = TRUE). Could it perhaps be useful to the user if you were to check if it is already set or set to a different value, and use a call to on.exit() to reset it to its previous value later on, to prevent changing their chosen setting without them knowing? [Edited to add: you can also do this via withr::local_options()]

You're right. I changed the code so that the user choice is always respected.

There is some commented out code in yf_get.R (lines 270 - 273) - can this be removed?

Done.

This function does a lot of things, and I might consider abstracting out some of the logic into smaller helper functions in future to make it easier to test in a more modular way. However, I don't think this is a problem here, as the code is well commented and flows in a logical order.

I agree. It is becoming a long code. I'll keep that in mind.

Comments on collections.R

Again, well commented and well documented, which is great.

Thanks!

It looks like yf_get_available_collections() just calls yf_get_available_indices() and returns the results - could you instead define it more simply, e.g. yf_get_available_collections() <- yf_get_available_indices()? And, what's the reason for having both? (This function changed slightly between when I first reviewed this and later came back to it, but I think the question is still relevant)

The idea is for later to have collections that are not indices. This is way I broke it into separate functions.

yf_collection_get() - it says it returns a "dataframe" - perhaps this could be either "data frame" (the concept) or "data.frame" (the object type) for more clarity?

Done.

Quick question - any reason this file doesn't have the yf prefix, but the other ones do? Not important, just curious.

My mistake. Its fixed.

Another tiny comment - I wonder if yf_get_collection() might feel like a better fit with the other function names than yf_collection_get()?

I followed the convention of using "object""verb" when naming functions. In fact, I just realized I used the wrong convention in some functions.
For consistency, I changed all names to the "object""verb" pattern except yf_get(), which I feel is short, concise and intuitive.

Comments on yf_convert_to_wide.R

Chunk of whitespace within the definition of fct_format_wide() which could be removed.

Done.

Comments on yf_get_clean_data.R

Some commented out code here - can this be removed?

Done.

Comments on yf_get_single_ticker.R

Love the use of the cli package to add messages to really help the user see what's going on.

Thanks. I really like it too.

Comments on "getting started" vignette

In the plot comparing the daily/weekly/monthly/yearly data, I might consider removing geom_point() and just using geom_line() as during a naive look at the plot, I wondered what the thickness of the lines meant before realising that the points had blurred together. I might also use breaks on the x axis with a higher frequency than five years.

Agreed. To fix it, I increased the time time period and removed the geom_point() layer.

melvidoni · 2022-06-16T22:56:49Z

@thisisnic and @s3alfisc what are your thoughts on the changes?
Do let me know if you are satisfied with these changes, or if there is anything else outstanding.

s3alfisc · 2022-06-17T12:39:55Z

Hi @melvidoni, I will try to take a closer look at @msperlin's comments this weekend / early next week =)

thisisnic · 2022-06-20T08:49:01Z

Thanks for the reminder there @melvidoni - I am happy with the changes made.

melvidoni · 2022-06-20T21:07:58Z

Thanks @thisisnic! We will wait until after the weekend for @s3alfisc's comments then!

s3alfisc · 2022-06-21T20:32:05Z

Hi all, I am very happy with the changes. The package looks and works great! In particular, I am super happy about how the documentation has evolved! :)

melvidoni · 2022-06-21T21:10:24Z

@ropensci-review-bot approve yfR

ropensci-review-bot · 2022-06-21T21:10:27Z

Approved! Thanks @msperlin for submitting and @s3alfisc, @thisisnic for your reviews! 😁

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Welcome aboard! We'd love to host a post about your package - either a short introduction to it with an example for a technical audience or a longer post with some narrative about its development or something you learned, and an example of its use for a broader readership. If you are interested, consult the blog guide, and tag @ropensci/blog-editors in your reply. She will get in touch about timing and can answer any questions.

We maintain an online book with our best practice and tips, this chapter starts the 3d section that's about guidance for after onboarding (with advice on releases, package marketing, GitHub grooming); the guide also feature CRAN gotchas. Please tell us what could be improved.

Last but not least, you can volunteer as a reviewer via filling a short form.

msperlin · 2022-06-22T11:03:43Z

Thanks @s3alfisc, @thisisnic! Realy appreciate the feedback.

I'll make all changes and report here soon.

msperlin · 2022-06-22T11:09:42Z

@ropensci-review-bot finalize transfer of yfR

ropensci-review-bot · 2022-06-22T11:09:45Z

Transfer completed.
The yfR team is now owner of the repository and the author has been invited to the team

msperlin · 2022-06-22T11:37:16Z

@s3alfisc, @thisisnic Can I include you both as reviewers in the DESCRIPTION file?

thisisnic · 2022-06-22T12:11:02Z

Of course, @msperlin , thanks!

msperlin · 2022-06-22T12:29:53Z

@melvidoni I've made all required changes. Please let me know if anything else is needed.
I'm also interested in a blog post @ropensci/blog-editors

s3alfisc · 2022-06-22T14:01:38Z

Same with me @msperlin, and thanks! :)

melvidoni · 2022-06-26T20:28:31Z

@melvidoni I've made all required changes. Please let me know if anything else is needed. I'm also interested in a blog post @ropensci/blog-editors

Excellent, thanks. Please, tick all the boxes in the corresponding post if you can.

msperlin · 2022-06-27T11:38:22Z

@melvidoni I've made all required changes. Please let me know if anything else is needed. I'm also interested in a blog post @ropensci/blog-editors

Excellent, thanks. Please, tick all the boxes in the corresponding post if you can.

@melvidoni
I can't tick the boxes in the original post. Should I write a new reply?

melvidoni · 2022-06-27T20:55:58Z

No worries, then it's fine @msperlin

msperlin · 2022-06-27T20:57:52Z

I'm planning to submit to CRAN tomorrow. Is that Ok? (sorry but I did not see any guideline about when to submit to cran)

melvidoni · 2022-06-27T21:04:34Z

It should be okay.

steffilazerte · 2022-06-30T14:28:20Z

Hi @msperlin,

We'd love to have a blog post about yfR, thank you for offering!

We publish two types of articles, blog posts and technotes. Let us know which type of article you'd like to write and when you think you might have it ready by, and we'll pencil in a publication date that will give us time for a quick review (the date can always change if things go faster or slower than expected).

We have a guide for blog authors (https://blogguide.ropensci.org/) and when you're ready and have a pull request, just set me as the reviewer or ping me and I'll come by to give you some feedback.

Let me know if you have any questions, thanks!

msperlin · 2022-06-30T20:50:09Z

Thanks @steffilazerte. I'll have a look on the material you posted. But, I will need some time, maybe a couple of weeks to write the post. I'll let you know.

steffilazerte · 2022-06-30T21:13:40Z

Perfectly reasonable 😁

msperlin · 2022-07-13T17:26:31Z

@steffilazerte I wrote a blog post. Just send you the PR and set your as reviewer.

jooolia self-assigned this Apr 1, 2022

jooolia added the 0/editorial-team-prep label Apr 1, 2022

msperlin mentioned this issue Apr 2, 2022

Backward compatibility with R 4.02 ropensci/yfR#4

Closed

jooolia removed their assignment May 1, 2022

ropensci-review-bot assigned melvidoni May 1, 2022

ropensci-review-bot added 1/editor-checks and removed 0/editorial-team-prep labels May 1, 2022

ropensci-review-bot added 2/seeking-reviewer(s) and removed 1/editor-checks labels May 1, 2022

ropensci-review-bot removed the 3/reviewer(s)-assigned label Jun 6, 2022

ropensci-review-bot added the 6/approved label Jun 21, 2022

ropensci-review-bot closed this as completed Jun 21, 2022

msperlin mentioned this issue Jun 22, 2022

Many changes after approval ropensci ropensci/yfR#13

Merged

msperlin mentioned this issue Jul 13, 2022

yfR blog post ropensci/roweb3#361

Closed

mpadge removed the 4/review(s)-in-awaiting-changes label Oct 4, 2022

yfR: Downloads and Organizes Financial Data from Yahoo Finance #523

yfR: Downloads and Organizes Financial Data from Yahoo Finance #523

Comments

msperlin commented Mar 30, 2022 • edited by ropensci-review-bot Loading

Archive: TBD Version accepted: TBD Language: en

Scope

Technical checks

Publication options

Code of conduct

ropensci-review-bot commented Mar 30, 2022

ropensci-review-bot commented Mar 30, 2022

ropensci-review-bot commented Mar 30, 2022

ropensci-review-bot commented Mar 31, 2022

Checks for yfR (v0.0.1)

1. Statistical Properties

1a. Network visualisation

2. goodpractice and other checks

3b. goodpractice results

R CMD check with rcmdcheck

Test coverage with covr

Cyclocomplexity with cyclocomp

Static code analyses with lintr

Editor-in-Chief Instructions:

mpadge commented Mar 31, 2022

msperlin commented Mar 31, 2022

jooolia commented Apr 1, 2022

ropensci-review-bot commented Apr 1, 2022

ropensci-review-bot commented Apr 1, 2022

ropensci-review-bot commented Apr 1, 2022

ropensci-review-bot commented Apr 1, 2022

Checks for yfR (v0.0.1)

1. Package Dependencies

2. Statistical Properties

2a. Network visualisation

3. goodpractice and other checks

3a. Continuous Integration Badges

3b. goodpractice results

R CMD check with rcmdcheck

Test coverage with covr

Cyclocomplexity with cyclocomp

Static code analyses with lintr

Editor-in-Chief Instructions:

jooolia commented Apr 1, 2022

msperlin commented Apr 2, 2022

jooolia commented Apr 3, 2022 • edited Loading

jooolia commented Apr 29, 2022

msperlin commented Apr 29, 2022

jooolia commented May 1, 2022

ropensci-review-bot commented May 1, 2022

melvidoni commented May 1, 2022

ropensci-review-bot commented May 1, 2022

msperlin commented May 2, 2022

msperlin commented Jun 7, 2022

Review Comments

Comments on yf_get.R

Comments on collections.R

Comments on yf_convert_to_wide.R

Comments on yf_get_clean_data.R

Comments on yf_get_single_ticker.R

Comments on "getting started" vignette

melvidoni commented Jun 16, 2022

s3alfisc commented Jun 17, 2022

thisisnic commented Jun 20, 2022

melvidoni commented Jun 20, 2022

s3alfisc commented Jun 21, 2022

melvidoni commented Jun 21, 2022

ropensci-review-bot commented Jun 21, 2022

msperlin commented Jun 22, 2022

msperlin commented Jun 22, 2022

ropensci-review-bot commented Jun 22, 2022

msperlin commented Jun 22, 2022

thisisnic commented Jun 22, 2022

msperlin commented Jun 22, 2022

s3alfisc commented Jun 22, 2022

melvidoni commented Jun 26, 2022

msperlin commented Jun 27, 2022

melvidoni commented Jun 27, 2022

msperlin commented Jun 27, 2022

melvidoni commented Jun 27, 2022

steffilazerte commented Jun 30, 2022

msperlin commented Mar 30, 2022 •

edited by ropensci-review-bot

Loading

Archive: TBD
Version accepted: TBD
Language: en

2. `goodpractice` and other checks

3b. `goodpractice` results

`R CMD check` with rcmdcheck

3. `goodpractice` and other checks

3b. `goodpractice` results

`R CMD check` with rcmdcheck

jooolia commented Apr 3, 2022 •

edited

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