fix(data): replace infinite variable bounds with NA

[ANAMASGARD]

Description

Replaces misleading Infinity and -Infinity placeholders in the variables dataset’s min and max fields with
missing values (NA).

This preserves meaningful finite bounds. For example:

• plant_functional_type now has min = NA and max = NA;
• root_biomass retains min = 0 and now has max = NA.

The packaged dataset and Frictionless metadata were regenerated from the corrected source CSV.

Related Issue(s)

Closes #29

Type of Change

• Bug fix (non-breaking change which fixes an issue)
• Data update (changes to datasets)

Checklist

• I have run devtools::check() with no errors or warnings
• I have updated NEWS.md if applicable
• I have updated documentation if applicable
• I have added/updated tests if applicable

Data Changes (if applicable)

• Data rebuilt from source using data-raw/make-data.R
• datapackage.json updated
• Row counts verified

Verification

• Reproduced the original failure: 1,553 infinite placeholders in the source and packaged dataset.
• Verified the corrected source CSV and installed package contain no infinite bounds.
• Confirmed categorical bounds are NA and valid finite bounds, such as root_biomass მინ = 0, are preserved.
• devtools::test() passed: 21 passed, 0 failures/warnings/skips.
• devtools::check(error_on = "warning") passed.
• git diff --check passed.

---

Additional Notes

datapackage.json now declares variables.min and variables.max as numeric fields. Its generated created date was
updated during the data rebuild.

[dlebauer]

Thank you for updating these - a simple but useful fix.

And, thank you for updating the test. But, now that the schema requires these fields to be numeric, the test could use is.infinite. There isn't a huge chance that this would occur, but please change the regression test to use expect_all_false(is.infinite(variables$min) - note that the _all_ vectorizes the expectation and thus the need for any.

This also brings up a related question that should be punted to a new issue ... the python frictionless package would make a lot of this testing of column names, types, etc much easier with frictionless validate datapackage.json.

[dlebauer]

Looks great, thanks!