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

View More author details

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

Plotting time series data using pandas

Visualization is a crucial aspect of data analysis, becoming even more significant when dealing with time series data. In previous chapters and recipes, you have encountered numerous instances where plotting the data was essential to highlight specific points or to draw conclusions about the time series. Visualizing our time series data enables us to easily identify patterns, trends, outliers, and other critical information at a glance. Furthermore, data visualization facilitates communication across different groups and can help bridge the gap between various stakeholders (such as business professionals and data scientists) by providing a common platform for communication and fostering constructive dialogue.

In time series analysis, as well as in machine learning at large, we prioritize visualizing our data during exploratory data analysis (EDA) to gain a comprehensive understanding of the data we’re working with. We also depend on visualization...