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17 | 17 | from sklearn.pipeline import Pipeline
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18 | 18 | from sklearn.svm import SVC
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19 | 19 | from sklearn.feature_extraction.text import CountVectorizer
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20 |
| -from sklearn.preprocessing import Imputer, StandardScaler, OneHotEncoder, LabelBinarizer |
| 20 | +from sklearn.preprocessing import ( |
| 21 | + Imputer, StandardScaler, OneHotEncoder, LabelBinarizer) |
21 | 22 | from sklearn.feature_selection import SelectKBest, chi2
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22 | 23 | from sklearn.base import BaseEstimator, TransformerMixin
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23 | 24 | import sklearn.decomposition
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@@ -94,7 +95,9 @@ def test_complex_df(complex_dataframe):
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94 | 95 | Get a dataframe from a complex mapped dataframe
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95 | 96 | """
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96 | 97 | df = complex_dataframe
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97 |
| - mapper = DataFrameMapper([('target', None), ('feat1', None), ('feat2', None)], df_out=True) |
| 98 | + mapper = DataFrameMapper( |
| 99 | + [('target', None), ('feat1', None), ('feat2', None)], |
| 100 | + df_out=True) |
98 | 101 | transformed = mapper.fit_transform(df)
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99 | 102 | assert len(transformed) == len(complex_dataframe)
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100 | 103 | for c in df.columns:
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@@ -145,7 +148,9 @@ def test_pca(complex_dataframe):
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145 | 148 | Check multi in and out with PCA
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146 | 149 | """
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147 | 150 | df = complex_dataframe
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148 |
| - mapper = DataFrameMapper([(['feat1', 'feat2'], sklearn.decomposition.PCA(2))], df_out=True) |
| 151 | + mapper = DataFrameMapper( |
| 152 | + [(['feat1', 'feat2'], sklearn.decomposition.PCA(2))], |
| 153 | + df_out=True) |
149 | 154 | transformed = mapper.fit_transform(df)
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150 | 155 | cols = transformed.columns
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151 | 156 | assert len(cols) == 2
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