ENH: drop function now has errors keyword for non-existing column handling #6736
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| @@ -6762,6 +6762,26 @@ def test_drop_names(self): | |||
| self.assertEqual(obj.columns.name, 'second') | |||
| self.assertEqual(list(df.columns), ['d', 'e', 'f']) | |||
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| self.assertRaises(ValueError, df.drop, ['g']) | |||
| self.assertRaises(ValueError, df.drop, ['g'], 1) | |||
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let's give at least one of these an errors='raise' argument (and add it to an existing test that doesn't raise) just for completeness.
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This all looks fine to me - thanks for the patch. We might want to reduce the number of test cases (just because we don't necessarily need to duplicate), but aside from that, quite good. - somebody else want to take a look too? I may be a bit rusty :P |
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Looks all good to me. But let's wait for #6599. :) |
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@sinhrks this idea is ok, can you rebase |
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@jreback Yes, rebased. |
| @@ -2226,7 +2228,9 @@ def drop(self, labels): | |||
| indexer = self.get_indexer(labels) | |||
| mask = indexer == -1 | |||
| if mask.any(): | |||
| raise ValueError('labels %s not contained in axis' % labels[mask]) | |||
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hmm, shouldn't this raise a KeyError? @jorisvandenbossche @shoyer to be consistent with say .loc and other indexers? @hayd
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This is kind of a gray area to me. We're not doing actual indexing here. I would probably stick with ValueError, especially to remain consistent with the existing implementation.
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have to think about this |
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@sinhrks can you rebase this. |
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Sure, rebased. |
ENH: drop function now has errors keyword for non-existing column handling
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@sinhrks thanks! |
Closes #5300.
Currently
dropraisesValueErrorwhen non-existing label is passed. I think it is useful ifdrophas an option to suppress error and drop existing labels only.For example, I sometimes process lots of files which has slightly different columns, and want to
dropif data has unnecessary columns. Previously, I have to prepare differentdroparguments checking columns existing each data.