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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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Toc

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

Introducing Series and DataFrames

Danfo.js exposes two main data structures, Series and DataFrames, to which all data manipulation can be done easily. DataFrames and Series provide a general representation for different types of data, hence the same data handling process can be applied to datasets with different formats.

In this section, we will look at different means of creating Series and DataFrames. We will see how to handle data in DataFrame and Series format. We will also look into different DataFrame and Series methods for data handling.

We will start this section by looking at how to handle data in a Series data structure.

Series

A Series provides an entry point to handling one-dimensional data, such as a single array with a sequence of values of the same data type.

In this section, we will get familiar with Series data structures with the following Series methods:

 *  table() and print() method:let sdata= new dfd.Series([1,3,5,7,9,11])
table( sdata...
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