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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
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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

Setting up Danfo.js for plotting

By default, Danfo.js provides some basic chart types. These charts can be called on any DataFrame or Series object and, if the correct arguments are passed, it will display the corresponding chart.

At the time of writing, Danfo.js comes with the following charts:

  • Line charts
  • Box and violin plots
  • Tables
  • Pie charts
  • Scatter plots
  • Bar charts
  • Histograms

These charts are exposed via the plot function. That is, if you have a DataFrame or Series object, calling the plot function on them exposes these charts.

The plot method requires a div ID where the plot is to be shown. For example, assuming df is a DataFrame, we can call the plot function as shown in the following code snippet:

const df = new DataFrame({...})
df.plot("my_div_id").<chart type>

The chart type can be line, bar, scatter, hist, pie, box, violin, or table.  

Each plot type will accept plot-specific arguments, but...

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