[query] Add to_pandas(types={}) argument to specify user-supplied pandas dtypes #12735
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Amazing! I'll look into this this week. Thank you Masa! |
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@patrick-schultz I added some tests and fixed behavior as a result. I think this is a valuable change, but since I've edited it directly seems like someone else should do review as well. |
patrick-schultz
approved these changes
Mar 1, 2023
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This PR fixes #11738. Now users can specify arbitrary type conversation between Hail and Pandas dtypes via:
This maps
col1andcol2toint32andnp.float64, respectively, and allhl.tstringfields toobject.One design question might be whether to have separate arguments for column name and Hail type specifications or not. Any thoughts? cc: @danking
Also, I don't think the current type check would work for
np.float64-like numpy dtype specifications...