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How to use the tsfresh.feature_extraction.feature_calculators.count_below_mean function in tsfresh

To help you get started, we’ve selected a few tsfresh examples, based on popular ways it is used in public projects.

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Tencent / Metis / time_series_detector / feature / statistical_features.py View on Github

def time_series_count_below_mean(x):
    """
    Returns the number of values in x that are lower than the mean of x

    :param x: the time series to calculate the feature of
    :type x: pandas.Series
    :return: the value of this feature
    :return type: float
    """
    return ts_feature_calculators.count_below_mean(x)

FeatureLabs / featuretools-tsfresh-primitives / featuretools_tsfresh_primitives / primitives / count_below_mean.py View on Github

def get_function(self):
        return count_below_mean