You're reading from Learn Grafana 10.x A beginner's guide to practical data analytics, interactive dashboards, and observability

Product type Paperback

Published in Dec 2023

Publisher Packt

ISBN-13 9781803231082

Length 542 pages

Edition 2nd Edition

Languages

Python

Tools

Grafana

Concepts

Data Visualization

Author (1):

Eric Salituro

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Table of Contents (23) Chapters

Preface

1. Part 1 – Getting Started with Grafana

2. Chapter 1: Introducing Data Visualization with Grafana FREE CHAPTER

3. Chapter 2: Touring the Grafana Interface

4. Chapter 3: Diving into Grafana's Time Series Visualization

5. Part 2 – Real-World Grafana

6. Chapter 4: Connecting Grafana to a Prometheus Data Source

7. Chapter 5: Extracting and Visualizing Data with InfluxDB and Grafana

8. Chapter 6: Shaping Data with Grafana Transformations

9. Chapter 7: Surveying Key Grafana Visualizations

10. Chapter 8: Surveying Additional Grafana Visualizations

11. Chapter 9: Creating Insightful Dashboards

12. Chapter 10: Working with Advanced Dashboard Features and Elasticsearch

13. Chapter 11: Streaming Real-Time IoT Data from Telegraf Agent to Grafana Live

14. Chapter 12: Monitoring Data Streams with Grafana Alerts

15. Chapter 13: Exploring Log Data with Grafana’s Loki

16. Part 3 – Managing Grafana

17. Chapter 14: Organizing Dashboards and Folders

18. Chapter 15: Managing Permissions for Users, Teams, and Organizations

19. Chapter 16: Authenticating Grafana Logins Using LDAP or OAuth 2 Providers

20. Chapter 17: Cloud Monitoring AWS, Azure, and GCP

21. Index

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Shaping Data with Grafana Transformations

Now that you understand how to connect data source queries to visualizations, we’re going to take a step back and look at one of the key features in Grafana’s visualization pipeline: the DataFrame. A DataFrame is an object that contains data received from a data source query and provides the source data for visualization.

In this chapter, we will learn more about DataFrames, their role in how Grafana visualizes data, and how to manipulate them using Grafana’s transformation operators. We will cover the following topics:

About Grafana DataFrames and transformations
Exploring the various transformation functions
Expanding analysis with a transformation
Chaining transformations into a visualization pipeline

First, we will answer the question of what a Grafana DataFrame is, its role, and how transformation operators affect it. Next, we will look at the most useful of the transformation operators...