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Caniuse has it's own groups, but it also ingests data from mdn/browser-compat-data (BCD), though I don't think it's included in the caniuse repo. Is it possible to see what the results are for arbitrary BCD features?
I think the answer is no, but it's not clear to me what I'd need to do to get from here to there. What keys from the caniuse JSON files are required to run the analysis for a given feature?
I'm asking because, I want to produce something like https://github.com/dfabulich/baseline-calculator/blob/main/survival-input-data.csv but for features which caniuse hasn't grouped. Since features are selected for creation on caniuse by Alexis, I want to find out if that set of features is biased relative to unrelated, ungrouped BCD features with similar keystone dates.
(My hypothesis is that caniuse features would have longer times to high usage levels than unrelated, ungrouped BCD features since developers and Alexis are probably less likely to take notice of narrower, younger, and more interopable features.)
The text was updated successfully, but these errors were encountered:
Caniuse has it's own groups, but it also ingests data from mdn/browser-compat-data (BCD), though I don't think it's included in the caniuse repo. Is it possible to see what the results are for arbitrary BCD features?
I think the answer is no, but it's not clear to me what I'd need to do to get from here to there. What keys from the caniuse JSON files are required to run the analysis for a given feature?
I'm asking because, I want to produce something like https://github.com/dfabulich/baseline-calculator/blob/main/survival-input-data.csv but for features which caniuse hasn't grouped. Since features are selected for creation on caniuse by Alexis, I want to find out if that set of features is biased relative to unrelated, ungrouped BCD features with similar keystone dates.
(My hypothesis is that caniuse features would have longer times to high usage levels than unrelated, ungrouped BCD features since developers and Alexis are probably less likely to take notice of narrower, younger, and more interopable features.)
The text was updated successfully, but these errors were encountered: