Comments (3)
Read csv using pandas function and convert in a second thep
Might actually be worth, the API surface of pd.read_csv
is huge and next thing we probably want to read from database or something, which pandas can do, but we don't have a function. So, I'd say: just use pandas' reading functions, then convert_long_dataframe_if
.
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I do that all the time. At some point we might remove the csv reading functions as they can basically never be used
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Yeah, I think reading the interchange format with a specific function has value, but in general so-called CSVs are super diverse. Probably it was not realistic to expect them to be sufficiently well-formed to read them with one function. /-:
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Related Issues (20)
- QA: test against development versions of upstream libraries
- improved nan treatment on summing HOT 1
- sparse data HOT 15
- scmdata compatibility
- Test fail with current packages HOT 2
- Add convert_to_gwp() to a dataset
- Order of attrs fields not stable in interchange format HOT 2
- pint and np.nan again
- fully type everything and add py.typed marker HOT 1
- CSG: next steps HOT 1
- Unit handling in xarray fails for Python 3.12
- Setup allows installation of unsupported Python version 3.12
- logging verbosity
- Abandon `sec_cats`
- extrapolation and other numerical / unary operations
- Support filtering for `entity` in Dataset.pr.loc
- Fix docs for aggregation
- Generalize `pr.set` HOT 1
- Harmonize parameter naming for selections/filters HOT 1
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