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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About Grafana DataFrames and transformations

While it is easy to imagine that Grafana simply takes the results of one or more data source queries, and somehow feeds them to the panel visualization of your choice, the reality is a bit more complex than that.

Every query result from the Query tab is managed separately as an independent data series by Grafana. That way, you have full control over each series and how it may be displayed in a panel visualization.

Next, each of those datasets is packaged into a single object Grafana referred to as a DataFrame. If you are at all familiar with Excel or Google spreadsheets from the financial world, or pandas or Spark from the data science world, you already have experience with the concept.

A Grafana DataFrame is, like similar objects, a rows and columns (technically an array of arrays) data structure, with each row a combination of one or more columnar fields. Because the DataFrame is a consistent data structure, it can easily be...