| # Copyright 2024 The Chromium Authors |
| # Use of this source code is governed by a BSD-style license that can be |
| # found in the LICENSE file. |
| """Find the outliers using IQR formula.""" |
| |
| import numpy as np |
| |
| |
| def calculate_iqr_outliers(use_case_results: list): |
| """ |
| Calculate Inter quartile Range (IQR) and identify outliers in a dataset. |
| |
| This function takes a list of numerical values and calculates the first |
| and third quartiles to find the IQR and the outliers. |
| |
| Args: |
| use_case_results (list): A list of numerical values for which to |
| calculate IQR and identify outliers. |
| |
| Returns: |
| dict: A dictionary containing the following key-value pairs: |
| - "Q1": The first quartile. |
| - "Q3": The third quartile. |
| - "IQR": The Inter quartile Range. |
| - "Lower Bound": The lower bound for identifying outliers. |
| - "Upper Bound": The upper bound for identifying outliers. |
| """ |
| |
| data_array = np.array(use_case_results) |
| sorted_data = np.sort(data_array) |
| q1_index = int(0.25 * (len(sorted_data))) |
| q3_index = int(0.75 * (len(sorted_data))) |
| |
| if len(sorted_data) % 2 == 0: |
| q1 = (sorted_data[q1_index] + sorted_data[q1_index - 1]) / 2 |
| q3 = (sorted_data[q3_index] + sorted_data[q3_index - 1]) / 2 |
| else: |
| q1 = sorted_data[q1_index] |
| q3 = sorted_data[q3_index] |
| |
| # Calculate the IQR value |
| iqr = q3 - q1 |
| |
| # Calculate lower and upper bounds for outliers |
| lower_bound = q1 - (1.5 * iqr) |
| upper_bound = q3 + 1.5 * iqr |
| outliers = (data_array < lower_bound) | (data_array > upper_bound) |
| |
| return { |
| "Q1": q1, |
| "Q3": q3, |
| "IQR": iqr, |
| "Lower Bound": lower_bound, |
| "Upper Bound": upper_bound, |
| "Outliers": data_array[outliers].tolist(), |
| } |
| |
| |
| if __name__ == "__main__": |
| # Example |
| use_case_sample_result = [11, 31, 21, 19, 8, 54, 35, 26, 23, 13, 29, 17] |
| result = calculate_iqr_outliers(use_case_sample_result) |
