33851dea0f6c75ca1e685037393ea7160506b53a,auto_ml/predictor.py,Predictor,_prepare_for_training,#Predictor#Any#,207

Before Change

            for idx, val in enumerate(y):
                try:
                    float_val = float(val)
                    if pd.notnull(float_val):
                        y_floats.append(float_val)
                    else:
                        indices_to_delete.append(idx)

After Change

            print("And here is the number of missing (nan, None, etc.) values for this column:")
            print(bad_rows.shape[0])
            print("We will remove these values, and continue with training on the cleaned dataset")
        X_df = X_df.dropna(subset=[self.output_column])


        // Remove the output column from the dataset, and store it into the y varaible
        y = list(X_df.pop(self.output_column))

Instances