INNER CODE UNIT · Python

nan_count

ScottfreeLLC/AlphaPy · alphapy/analysis.py:241

                    nan_count = df[target].isnull().sum()
                    forecast_check = forecast_period - 1
                    if nan_count != forecast_check:
                        logger.info("%s has %d records with NaN targets", tag, nan_count)
                    # drop records with NaN values in target column
                    new_test = new_test.dropna(subset=[target])
                    # append selected records to the test frame
                    test_frame = test_frame.append(new_test)
                else:
                    logger.info("Testing frame %s has zero rows. Check prediction date.",
                                tag)
            else:
                logger.info("Training frame %s has zero rows. Check data source.", tag)

    # Write out the frames for input into the AlphaPy pipeline

    directory = SSEP.join([directory, 'input'])
    if predict_mode:

View source record →