1## Create Value Map2value_dict = {True: 'Correct', False: 'Incorrect'}3 4## Check Data Types5print(type(iris_target_test))6print(type(iris_target_predictions))7 8## Clean Data9iris_target_test = iris_target_test['species']10iris_target_predictions = pd.Series(iris_target_predictions)11iris_target_test = iris_target_test.reset_index()['species']12iris_target_predictions.name = 'species'13 14### Validate Data Types15print(type(iris_target_test))16print(type(iris_target_predictions))17 18#### Create a dataframe with all of the information we will need for our two vizualizations19viz_frame = iris_feature_test.reset_index()[['sepal_length', 'sepal_width']]20viz_frame['outcome'] = (iris_target_test == iris_target_predictions).map(value_dict)21viz_frame['species'] = iris_target_test22 23##### Validate viz_frame24viz_frame.head(3)
1<class 'pandas.core.frame.DataFrame'>2<class 'numpy.ndarray'>3<class 'pandas.core.series.Series'>4<class 'pandas.core.series.Series'>