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Diffstat (limited to 'resources/tools/presentation/utils.py')
| -rw-r--r-- | resources/tools/presentation/utils.py | 29 |
1 files changed, 20 insertions, 9 deletions
diff --git a/resources/tools/presentation/utils.py b/resources/tools/presentation/utils.py index 2fbf70cadc..a15742a21f 100644 --- a/resources/tools/presentation/utils.py +++ b/resources/tools/presentation/utils.py @@ -81,15 +81,26 @@ def remove_outliers(input_list, outlier_const=1.5, window=14): :rtype: list of floats """ - input_series = pd.Series() - for index, value in enumerate(input_list): - item_pd = pd.Series([value, ], index=[index, ]) - input_series.append(item_pd) - output_series, _ = split_outliers(input_series, outlier_const=outlier_const, - window=window) - output_list = [y for x, y in output_series.items() if not np.isnan(y)] - - return output_list + data = np.array(input_list) + 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 + + # input_series = pd.Series() + # for index, value in enumerate(input_list): + # item_pd = pd.Series([value, ], index=[index, ]) + # input_series.append(item_pd) + # output_series, _ = split_outliers(input_series, outlier_const=outlier_const, + # window=window) + # output_list = [y for x, y in output_series.items() if not np.isnan(y)] + # + # return output_list def split_outliers(input_series, outlier_const=1.5, window=14): |