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Hi @Macabe222, are you still working on this, or is it ready for review? No problem either way just trying to make sure that it gets triaged. |
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Yes this one is read for review @cherman2 |
colinvwood
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Jan 20, 2026
colinvwood
reviewed
Jan 20, 2026
colinvwood
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Jan 20, 2026
colinvwood
reviewed
Jan 20, 2026
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| def tabulate_feature_frequencies(table: biom.Table) -> qiime2.Metadata: | ||
| def tabulate_feature_frequencies(table: biom.Table, format: bool = False) \ |
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remove all these interface changes
colinvwood
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Jan 20, 2026
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Let's remove all the interface changes so we don't have to deal with that headache and instead just convert all numeric-parseable columns in the metadata to numeric columns
Macabe222
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colinvwood
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Feb 2, 2026
colinvwood
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Feb 5, 2026
| metadata_df = metadata.to_dataframe() | ||
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| # Make sure numeric columns are represented correctly | ||
| types = {} |
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I don't think we need this anymore
colinvwood
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Feb 5, 2026
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| # Make sure numeric columns are represented correctly | ||
| types = {} | ||
| numeric_frame = pd.DataFrame() |
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we don't need a separate dataframe, just update the columns in place
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Adds functionality to automatically detect numeric columns that have been converted to strings by actions such as
tabulate-feature-frequenciesand convert them back to numeric metadata columns, allowing them to be properly sorted in thetabulate-seqsvisualizer.Resolves #344