fixed row/col orientation for 2D arrays #1834
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Pytables createArray function uses the opposite convention to pandas for row/col. Using the numpy transpose .T corrects for this without copying the data and keeping the orientation of 1D arrays intact.
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Is solution for #1824 |
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my apologies, it appears I was a little premature with this pull request as the files it writes can't be read again. Should I close this request or edit it in-place as/when the problem is resolved? |
the transposed attribute keeps track of whether the data has been transposed, allowing it to be correctly read by _read_array. Some minor rearrangement of _read_array was necessary to reduce duplicate code.
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earlier problems are fixed by adding a new _v_attr signalling the transpose has been applied. It's not that pretty, but it's logical and appears to work. |
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Thanks. I think the |
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Yes it should do, because it defaults to false if it's not found. |
wesm
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Sep 9, 2012
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Pytables uses the opposite convention to pandas for row/col. Using the numpy transpose .T corrects for this without copying the data and keeping the orientation of 1D arrays intact.