Add a high level test using the iris dataset

Author: calpaterson

tests/test_dataframe_mapper.py

@@ -0,0 +1,41 @@
+import pytest
+
+from pandas import DataFrame
+from sklearn.datasets import load_iris
+from sklearn.preprocessing import LabelBinarizer
+from sklearn.svm import SVC
+import numpy as np
+
+from sklearn_pandas import (
+    DataFrameMapper,
+    PassthroughTransformer,
+    cross_val_score,
+)
+
+@pytest.fixture
+def iris_dataframe():
+    iris = load_iris()
+    return DataFrame(
+        data={
+            iris.feature_names[0]: iris.data[:,0],
+            iris.feature_names[1]: iris.data[:,1],
+            iris.feature_names[2]: iris.data[:,2],
+            iris.feature_names[3]: iris.data[:,3],
+            "species": np.array([iris.target_names[e] for e in iris.target])
+        }
+    )
+
+def test_with_iris_dataframe(iris_dataframe):
+    pipeline = DataFrameMapper([
+        ("petal length (cm)", PassthroughTransformer()),
+        ("petal width (cm)", PassthroughTransformer()),
+        ("sepal length (cm)", PassthroughTransformer()),
+        ("sepal width (cm)", PassthroughTransformer()),
+        ("species", LabelBinarizer()),
+    ])
+    data = iris_dataframe.drop("species", axis=1)
+    labels = iris_dataframe["species"]
+    clf = SVC(kernel='linear', C=1)
+    scores = cross_val_score(clf, data, labels)
+    assert scores.mean > 0.96
+    assert (scores.std() * 2) < 0.04

tests/test_sklearn_pandas.py

@@ -14,5 +14,4 @@ commands =
          pip install pandas --no-index
          pip install scikit-learn --no-index
          python setup.py develop
-         py.test
-         python setup.py bdist_wheel
+         py.test