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

Writing time series data to InfluxDB

When working with large time series data, such as a sensor or Internet of Things (IoT) data, you will need a more efficient way to store and query such data for further analytics. This is where time series databases shine, as they are built exclusively to work with complex and very large time series datasets.

In this recipe, we will work with InfluxDB as an example of how to write to a time series database.

Getting ready

You should refer to the recipe “Reading data from a time series database” in Chapter 3 “Reading Time Series Data from Databases” as a refresher on the different ways to connect to InfluxDB.

You will be using the ExtraSensory dataset, a mobile sensory dataset made available by the University of California, San Diego: Vaizman, Y., Ellis, K., and Lanckriet, G. "Recognizing Detailed Human Context In-the-Wild from Smartphones and Smartwatches". IEEE Pervasive Computing, vol. 16, no. 4, October-December...