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The bulk of the dataframe interchange protocol was done in gh-38. There were still a number of TODOs however, and more will likely pop up once we have multiple implementations so we can actually turn one type of dataframe into another type. This is the tracking issue for those TODOs and issues:
Categorical dtypes: we should allow having null as a category; it should not have a specified meaning, it's just another category that should (e.g.) roundtrip correctly. See conversation in 8 Apr meeting.
Categorical dtypes: should they be a dtype in themselves, or should they be a part of the dtype tuple? Currently dtype is (kind, bitwidth, format_str, endianness), with categorical being a value of the kind enum. Is making a 5th element in the dtype, with that element being another dtype 4-tuple, thereby allowing for nesting, sensible?
Add a metadata attribute that can be used to store library-specific things. For example, Vaex should be able to store expressions for its virtual columns there. See PR PR: Add metadata attribute to DataFrame and Column #43
Add a flag to throw an exception if the export cannot be zero-copy. (e.g. for pandas, possible due to block manager where rows are contiguous and columns are not - add a test for that). See PR PR: Add allow_copy flag to interchange protocol #44
What can be reused between implementations in different libraries, and can/should we have a reference implementation? --> question needs answering somewhere.
The bulk of the dataframe interchange protocol was done in gh-38. There were still a number of TODOs however, and more will likely pop up once we have multiple implementations so we can actually turn one type of dataframe into another type. This is the tracking issue for those TODOs and issues:
null
as a category; it should not have a specified meaning, it's just another category that should (e.g.) roundtrip correctly. See conversation in 8 Apr meeting.(kind, bitwidth, format_str, endianness)
, with categorical being a value of thekind
enum. Is making a 5th element in the dtype, with that element being another dtype 4-tuple, thereby allowing for nesting, sensible?metadata
attribute that can be used to store library-specific things. For example, Vaex should be able to store expressions for its virtual columns there. See PR PR: Add metadata attribute to DataFrame and Column #43allow_copy
flag to interchange protocol #44offsets
and adata
buffer, see Add a prototype of the dataframe interchange protocol #38 (comment)). _See PR Add variable-length string support #45from_dataframe
protocol? See Signature for a standardfrom_dataframe
constructor function #42 and meeting of 20 May.owner
attribute is perhaps needed. See meeting minutes 4 March, How to consume a single buffer & connection to array interchange #39, and comments on this PR.The text was updated successfully, but these errors were encountered: