+def remove_outliers(input_data, outlier_const):
+ """
+
+ :param input_data: Data from which the outliers will be removed.
+ :param outlier_const: Outlier constant.
+ :type input_data: list
+ :type outlier_const: float
+ :returns: The input list without outliers.
+ :rtype: list
+ """
+
+ data = np.array(input_data)
+ upper_quartile = np.percentile(data, 75)
+ lower_quartile = np.percentile(data, 25)
+ iqr = (upper_quartile - lower_quartile) * outlier_const
+ quartile_set = (lower_quartile - iqr, upper_quartile + iqr)
+ result_lst = list()
+ for y in data.tolist():
+ if quartile_set[0] <= y <= quartile_set[1]:
+ result_lst.append(y)
+ return result_lst
+
+