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Building Data-Driven Applications with Danfo.js

You're reading from   Building Data-Driven Applications with Danfo.js A practical guide to data analysis and machine learning using JavaScript

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Product type Paperback
Published in Sep 2021
Publisher Packt
ISBN-13 9781801070850
Length 476 pages
Edition 1st Edition
Languages
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Authors (2):
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Stephen Oni Stephen Oni
Author Profile Icon Stephen Oni
Stephen Oni
Rising Odegua Rising Odegua
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Rising Odegua
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Table of Contents (18) Chapters Close

Preface 1. Section 1: The Basics
2. Chapter 1: An Overview of Modern JavaScript FREE CHAPTER 3. Section 2: Data Analysis and Manipulation with Danfo.js and Dnotebook
4. Chapter 2: Dnotebook - An Interactive Computing Environment for JavaScript 5. Chapter 3: Getting Started with Danfo.js 6. Chapter 4: Data Analysis, Wrangling, and Transformation 7. Chapter 5: Data Visualization with Plotly.js 8. Chapter 6: Data Visualization with Danfo.js 9. Chapter 7: Data Aggregation and Group Operations 10. Section 3: Building Data-Driven Applications
11. Chapter 8: Creating a No-Code Data Analysis/Handling System 12. Chapter 9: Basics of Machine Learning 13. Chapter 10: Introduction to TensorFlow.js 14. Chapter 11: Building a Recommendation System with Danfo.js and TensorFlow.js 15. Chapter 12: Building a Twitter Analysis Dashboard 16. Chapter 13: Appendix: Essential JavaScript Concepts 17. Other Books You May Enjoy

Combining datasets

DataFrames and Series can be combined using built-in functions in Danfo.js. Methods such as danfo.merge and danfo.concat exist that, depending on the configurations, can help you combine datasets in different forms using familiar database-like joins.

In this section, we'll briefly talk about these join types, starting with the merge function.

DataFrame merge

The merge operation is similar to the database Join operation in that it performs join operations on columns or indexes found in the object. The signature of the merge operation is as follows:

danfo.merge({left, right, on, how}) 

Let's understand what each parameter entails:

  • left: The left-hand side DataFrame/Series you want to merge to.
  • right: The right-hand side DataFrame/Series you want to merge to.
  • on: The name(s) of the column(s) to join. These column(s) must be found in both the left and right DataFrames.
  • how: The how parameter specifies how the merge should...
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