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Adds drop column transformer component #827

Merged
merged 13 commits into from
Jun 4, 2020
Merged

Adds drop column transformer component #827

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a0e8ecc
init
angela97lin Jun 1, 2020
9f31d41
add numpy support and tests
angela97lin Jun 1, 2020
7498ec7
add test for component in pipeline
angela97lin Jun 1, 2020
883e97e
lint and changelog
angela97lin Jun 2, 2020
b4202cb
address first round of comments
angela97lin Jun 3, 2020
dd3885f
add tests
angela97lin Jun 3, 2020
742f511
update to precompute
angela97lin Jun 3, 2020
c90a8be
refactor
angela97lin Jun 3, 2020
ff2d9b7
lint
angela97lin Jun 3, 2020
4292bb4
update test via pr comments
angela97lin Jun 4, 2020
7570948
Merge branch 'master' into 774_drop_component
angela97lin Jun 4, 2020
0e93d45
update tests to reinitalize
angela97lin Jun 4, 2020
ac117dd
Merge branch '774_drop_component' of github.com:FeatureLabs/evalml in…
angela97lin Jun 4, 2020
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10 changes: 6 additions & 4 deletions evalml/pipelines/components/transformers/drop_columns.py
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Original file line number Diff line number Diff line change
Expand Up @@ -22,8 +22,9 @@ def fit(self, X, y=None):
cols = self.parameters["columns"] or []
if not isinstance(X, pd.DataFrame):
X = pd.DataFrame(X)
if not set(cols).issubset(X.columns):
raise ValueError("Columns {} not found in input data".format(', '.join(f"'{col_name}'" for col_name in list(set(cols) - set(X.columns)))))
missing_cols = set(cols) - set(X.columns)
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if len(missing_cols) > 0:
raise ValueError("Columns {} not found in input data".format(', '.join(f"'{col_name}'" for col_name in missing_cols)))
return self

def transform(self, X, y=None):
Expand All @@ -39,6 +40,7 @@ def transform(self, X, y=None):
cols = self.parameters["columns"] or []
if not isinstance(X, pd.DataFrame):
X = pd.DataFrame(X)
if not set(cols).issubset(X.columns):
raise ValueError("Column(s) {} not found in input data".format(', '.join(f"'{col_name}'" for col_name in list(set(cols) - set(X.columns)))))
missing_cols = set(cols) - set(X.columns)
if len(missing_cols) > 0:
raise ValueError("Columns {} not found in input data".format(', '.join(f"'{col_name}'" for col_name in missing_cols)))
return X.drop(columns=cols, axis=1)