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Remove copy_dataframe parameter, update requirements with release of Woodwork v0.0.6 #1478

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merged 6 commits into from Nov 30, 2020
Merged

Remove copy_dataframe parameter, update requirements with release of Woodwork v0.0.6 #1478

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bdddd95
remove copy_dataframe
angela97lin Nov 30, 2020
fc36f18
cleanup
angela97lin Nov 30, 2020
91bbbc1
Merge branch 'main' into ange_remove_copy_dataframe
angela97lin Nov 30, 2020
5cbd658
fix typo
angela97lin Nov 30, 2020
ffbf3b0
Merge branch 'ange_remove_copy_dataframe' of github.com:alteryx/evalm…
angela97lin Nov 30, 2020
038cf38
fix test
angela97lin Nov 30, 2020
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2 changes: 1 addition & 1 deletion core-requirements.txt
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Expand Up @@ -10,6 +10,6 @@ psutil>=5.6.3
requirements-parser>=0.2.0
shap>=0.35.0
texttable>=1.6.2
woodwork>=0.0.5
woodwork>=0.0.6
featuretools>=0.20.0
nlp-primitives>=1.1.0
1 change: 1 addition & 0 deletions docs/source/release_notes.rst
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Expand Up @@ -5,6 +5,7 @@ Release Notes
* Enhancements
* Fixes
* Updated ``Woodwork`` to >=0.0.5 in ``core-requirements.txt`` :pr:`1473`
* Removed ``copy_dataframe`` parameter for ``Woodwork``, updated ``Woodwork`` to >=0.0.6 in ``core-requirements.txt`` :pr:`1478`
* Updated ``detect_problem_type`` to use ``pandas.api.is_numeric_dtype`` :pr:`1476`
* Changes
* Changed ``make clean`` to delete coverage reports as a convenience for developers :pr:`1464`
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6 changes: 3 additions & 3 deletions evalml/tests/automl_tests/test_automl.py
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Expand Up @@ -1767,7 +1767,7 @@ def test_automl_woodwork_user_types_preserved(mock_binary_fit, mock_binary_score
X['num col'] = pd.Series(new_col)
X['text col'] = pd.Series([f"{num}" for num in range(len(new_col))])
X = ww.DataTable(X, semantic_tags={'cat col': 'category', 'num col': 'numeric'},
logical_types={'cat col': 'Categorical', 'num col': 'WholeNumber', 'text col': 'NaturalLanguage'})
logical_types={'cat col': 'Categorical', 'num col': 'Integer', 'text col': 'NaturalLanguage'})
automl = AutoMLSearch(problem_type=problem_type, max_batches=5)
automl.search(X, y)
for arg in mock_fit.call_args[0]:
Expand All @@ -1776,7 +1776,7 @@ def test_automl_woodwork_user_types_preserved(mock_binary_fit, mock_binary_score
assert arg.semantic_tags['cat col'] == {'category'}
assert arg.logical_types['cat col'] == ww.logical_types.Categorical
assert arg.semantic_tags['num col'] == {'numeric'}
assert arg.logical_types['num col'] == ww.logical_types.WholeNumber
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WholeNumber was removed

assert arg.logical_types['num col'] == ww.logical_types.Integer
assert arg.semantic_tags['text col'] == set()
assert arg.logical_types['text col'] == ww.logical_types.NaturalLanguage
for arg in mock_score.call_args[0]:
Expand All @@ -1785,7 +1785,7 @@ def test_automl_woodwork_user_types_preserved(mock_binary_fit, mock_binary_score
assert arg.semantic_tags['cat col'] == {'category'}
assert arg.logical_types['cat col'] == ww.logical_types.Categorical
assert arg.semantic_tags['num col'] == {'numeric'}
assert arg.logical_types['num col'] == ww.logical_types.WholeNumber
assert arg.logical_types['num col'] == ww.logical_types.Integer
assert arg.semantic_tags['text col'] == set()
assert arg.logical_types['text col'] == ww.logical_types.NaturalLanguage

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4 changes: 3 additions & 1 deletion evalml/utils/gen_utils.py
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Expand Up @@ -300,9 +300,11 @@ def _convert_to_woodwork_structure(data):
ww_data = pd.DataFrame(ww_data)

# Convert pandas data structures to Woodwork data structures
ww_data = ww_data.copy()
if isinstance(ww_data, pd.Series):
return ww.DataColumn(ww_data)
return ww.DataTable(ww_data, copy_dataframe=True)

return ww.DataTable(ww_data)
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Hmm, so is DataTable copying implicitly now? The docs for the constructor just say "create datatable"

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EDIT: Oops, didn't read your comment thoroughly. It doesn't copies implicitly.

See description for alteryx/woodwork#398!

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Thanks @angela97lin ! Filed alteryx/woodwork#420



def _convert_woodwork_types_wrapper(pd_data):
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