old_contents: #  Copyright 2015 Google Inc. All Rights Reserved.
  #
  #  Licensed under the Apache License, Version 2.0 (the "License");
  #  you may not use this file except in compliance with the License.
  #  You may obtain a copy of the License at
  #
  #   http://www.apache.org/licenses/LICENSE-2.0
  #
  #  Unless required by applicable law or agreed to in writing, software
  #  distributed under the License is distributed on an "AS IS" BASIS,
  #  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  #  See the License for the specific language governing permissions and
  #  limitations under the License.
  
  import random
  
  from sklearn import datasets
  from sklearn.metrics import accuracy_score, mean_squared_error, log_loss
  
  import tensorflow as tf
  from tensorflow.python.platform import googletest
  
  from skflow.io import *
  import skflow
  
  class BaseTest(googletest.TestCase):
      def test_pandas_data_classification(self):
          if HAS_PANDAS:
              random.seed(42)
              iris = datasets.load_iris()
              data = DataFrame(iris.data)
              labels = DataFrame(iris.target)
              classifier = skflow.TensorFlowLinearClassifier(n_classes=3)
              classifier.fit(data, labels)
              score = accuracy_score(classifier.predict(data), labels)
              self.assertGreater(score, 0.5, "Failed with score = {0}".format(score))
  
  if __name__ == '__main__':
      tf.test.main()
  
new_contents: #  Copyright 2015 Google Inc. All Rights Reserved.
  #
  #  Licensed under the Apache License, Version 2.0 (the "License");
  #  you may not use this file except in compliance with the License.
  #  You may obtain a copy of the License at
  #
  #   http://www.apache.org/licenses/LICENSE-2.0
  #
  #  Unless required by applicable law or agreed to in writing, software
  #  distributed under the License is distributed on an "AS IS" BASIS,
  #  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  #  See the License for the specific language governing permissions and
  #  limitations under the License.
  
  import random
  
  from sklearn import datasets
  from sklearn.metrics import accuracy_score
  
  import tensorflow as tf
  from tensorflow.python.platform import googletest
  
  from skflow.io import *
  import skflow
  
  class BaseTest(googletest.TestCase):
      def test_pandas_data_classification(self):
          if HAS_PANDAS:
              random.seed(42)
              iris = datasets.load_iris()
              data = DataFrame(iris.data)
              labels = DataFrame(iris.target)
              classifier = skflow.TensorFlowLinearClassifier(n_classes=3)
              classifier.fit(data, labels)
              score = accuracy_score(classifier.predict(data), labels)
              self.assertGreater(score, 0.5, "Failed with score = {0}".format(score))
          else:
              print("No pandas installed. test_pandas_data_classification skipped.")
  
  if __name__ == '__main__':
      tf.test.main()
  
subject: Print when pandas not installed and removed unnecessary imports