You're reading from Time Series Analysis with Python Cookbook Practical recipes for exploratory data analysis, data preparation, forecasting, and model evaluation

Product type Paperback

Published in Apr 2025

Publisher

ISBN-13 9781805124283

Length 98 pages

Edition 2nd Edition

Languages

Python

Concepts

Data Analysis

Author (1):

Tarek A. Atwan

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Table of Contents (13) Chapters

1. Time Series Analysis with Python Cookbook, Second Edition: Practical recipes for exploratory data analysis, data preparation, forecasting, and model evaluation FREE CHAPTER

2. Getting Started with Time Series Analysis

3. Reading Time Series Data from Files

4. Reading Time Series Data from Databases

5. Persisting Time Series Data to Files

6. Persisting Time Series Data to Databases

7. Working with Date and Time in Python

8. Handling Missing Data

9. Outlier Detection Using Statistical Methods

10. Exploratory Data Analysis and Diagnosis

11. Building Univariate Time Series Models Using Statistical Methods

12. Additional Statistical Modeling Techniques for Time Series

13. Outlier Detection Using Unsupervised Machine Learning

Detecting outliers using a modified z-score

In the Detecting outliers using a z-score recipe, you experienced how simple and intuitive the method is. But it has one major drawback: it assumes your data is normally distributed.

But, what if your data is not normally distributed? Luckily, there is a modified version of the z-score to work with non-normal data. The main difference between the regular z-score and the modified z-score is that we replace the mean with the median:

Where

(tilde x) is the median of the dataset, and MAD is the median absolute deviation of the dataset:

The 0.6745 value is the standard deviation unit that corresponds to the 75th percentile (Q3) in a Gaussian distribution and is used as a normalization factor. In other words, it is used to approximate the standard deviation. This way, the units you obtain from this method are measured in standard deviation, similar to how you would interpret the regular z-score.

You can obtain this value using SciPy&apos...

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You're reading from Time Series Analysis with Python Cookbook Practical recipes for exploratory data analysis, data preparation, forecasting, and model evaluation

Table of Contents (13) Chapters

Detecting outliers using a modified z-score

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You're reading from Time Series Analysis with Python Cookbook Practical recipes for exploratory data analysis, data preparation, forecasting, and model evaluation

Table of Contents (13) Chapters

Detecting outliers using a modified z-score

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