Building Data-Driven Applications with Danfo.js: A practical guide to data analysis and machine learning using JavaScript
- Length: 476 pages
- Edition: 1
- Language: English
- Publisher: Packt Publishing
- Publication Date: 2021-09-24
- ISBN-10: 1801070857
- ISBN-13: 9781801070850
- Sales Rank: #3229876 (See Top 100 Books)
Get hands-on with building data-driven applications using Danfo.js in combination with other data analysis tools and techniques
Key Features
- Build microservices to perform data transformation and ML model serving in JavaScript
- Explore what Danfo.js is and how it helps with data analysis and data visualization
- Combine Danfo.js and TensorFlow.js for machine learning
Book Description
Most data analysts use Python and pandas for data processing for the convenience and performance these libraries provide. However, JavaScript developers have always wanted to use machine learning in the browser as well. This book focuses on how Danfo.js brings data processing, analysis, and ML tools to JavaScript developers and how to make the most of this library to build data-driven applications.
Starting with an overview of modern JavaScript, you’ll cover data analysis and transformation with Danfo.js and Dnotebook. The book then shows you how to load different datasets, combine and analyze them by performing operations such as handling missing values and string manipulations. You’ll also get to grips with data plotting, visualization, aggregation, and group operations by combining Danfo.js with Plotly. As you advance, you’ll create a no-code data analysis and handling system and create-react-app, react-table, react-chart, Draggable.js, and tailwindcss, and understand how to use TensorFlow.js and Danfo.js to build a recommendation system. Finally, you’ll build a Twitter analytics dashboard powered by Danfo.js, Next.js, node-nlp, and Twit.js.
By the end of this app development book, you’ll be able to build and embed data analytics, visualization, and ML capabilities into any JavaScript app in server-side Node.js or the browser.
What you will learn
- Perform data experimentation and analysis with Danfo.js and Dnotebook
- Build machine learning applications using Danfo.js integrated with TensorFlow.js
- Connect Danfo.js with popular database applications to aid data analysis
- Create a no-code data analysis and handling system using internal libraries
- Develop a recommendation system with Danfo.js and TensorFlow.js
- Build a Twitter analytics dashboard for sentiment analysis and other types of data insights
Who this book is for
This book is for data analysts, data scientists, and JavaScript developers who want to create data-driven applications in the JavaScript/Node.js environment. Intermediate-level knowledge of JavaScript programming and data science using pandas is expected.
Table of Contents
- An Overview of Modern JavaScript
- Dnotebook – An Interactive Computing Environment for JavaScript
- Getting Started with Danfo.js
- Data Analysis, Wrangling, and Transformation
- Data Visualization with Plotly.js
- Data Visualization with Danfo.js
- Data Aggregation and Group Operations
- Creating a No-Code Data Analysis/Handling System
- Basics of Machine Learning
- Introduction to TensorFlow.js
- Building a Recommendation System with Danfo.js and TensorFlow.js
- Building a Twitter Analysis Dashboard
- Appendix: Essential JavaScript Concepts
Building Data-Driven Applications with Danfo.js Contributors About the authors About the reviewers Preface Who this book is for What this book covers To get the most out of this book Download the example code files Download the color images Conventions used Get in touch Share Your Thoughts Section 1: The Basics Chapter 1: An Overview of Modern JavaScript Technical requirements Understanding the difference between let and var var allows the redeclaration of variables var is not a blocked scope Destructuring Spread syntax Spreading or unpacking an iterable into an array Creating new objects from existing ones Function arguments Overview of scopes and closures Scope Closure Understanding Array and Object methods Array methods Objects Understanding the this property Arrow functions Promises and async/await Cleaning callbacks with promises async/await Object-oriented programming and JavaScript classes Classes Inheritance Setting up a modern JavaScript environment with transpilers Babel Webpack Unit testing with Mocha and Chai Setting up a test environment Summary Section 2: Data Analysis and Manipulation with Danfo.js and Dnotebook Chapter 2: Dnotebook - An Interactive Computing Environment for JavaScript Technical requirements Introduction to Dnotebook Setup and installation of Dnotebook Basic concepts behind interactive computing in Dnotebook Cells Code cells Markdown cells Persistence/state Writing interactive code Loading external packages Loading CSV files Getting a div container for plots Gotchas when using a for loop Working with Markdown cells Creating a Markdown cell Adding images Headings Lists Saving notebooks Summary Chapter 3: Getting Started with Danfo.js Technical requirements Why you need Danfo.js Installing Danfo.js Introducing Series and DataFrames Series DataFrames Essential functions and methods in Danfo.js loc and iloc indexing Sorting Filtering Arithmetic operations Logical operations Data loading and working with different file formats Transforming a DataFrame into another file format Summary Chapter 4: Data Analysis, Wrangling, and Transformation Technical requirements Transforming data Replacing missing values Removing duplicates Data transformation with the map function Data transformation with the apply function Filtering and querying Random sampling Encoding DataFrames and Series Combining datasets DataFrame merge Data concatenation Series data accessors Calculating statistics Calculating statistics by axis Summary Chapter 5: Data Visualization with Plotly.js Technical requirements A brief primer on Plotly.js Using Plotly.js via a script tag Fundamentals of Plotly.js Data format Configuration options for plots Plotly layout Creating basic charts with Plotly.js Creating statistical charts with Plotly.js Creating histogram plots with Plotly.js Creating box plots with Plotly.js Creating violin plots with Plotly.js Summary Chapter 6: Data Visualization with Danfo.js Technical requirements Setting up Danfo.js for plotting Adding Danfo.js to your code Downloading a dataset for plotting Creating line charts with Danfo.js Creating scatter plots with Danfo.js Creating box and violin plots with Danfo.js Making box and violin plots for a Series Box and violin plots for multiple columns Box and violin plots with specific x and y values Creating histograms with Danfo.js Creating a histogram from a Series Creating a histogram from multiple columns Creating bar charts with Danfo.js Creating a bar chart from a Series Creating a bar chart from multiple columns Summary Chapter 7: Data Aggregation and Group Operations Technical requirements Grouping data Single-column grouping Double-column grouping Iterating through grouped data Iterating through single- and double-column grouped data Using the .apply method Data aggregation of grouped data Data aggregation on single-column grouping Data aggregation on double-column grouping A simple application of groupby on real data Summary Section 3: Building Data-Driven Applications Chapter 8: Creating a No-Code Data Analysis/Handling System Technical requirements Setting up the project environment Structuring and designing the app App layout and the DataTable component Implementing DataTable components File upload and state management Creating different DataFrame operation components Implementing the Describe component Implementing the Query component Implementing the Df2df component Implementing the Arithmetic component Implementing the chart component Implementing the ChartPlane component Implementing the ChartViz component Integrating ChartViz and ChartPlane into App.js Summary Chapter 9: Basics of Machine Learning Technical requirements Introduction to machine learning A simple analogy of a machine learning system Why machine learning works Objective functions Evaluation metrics Machine learning problems/tasks Supervised learning Unsupervised learning Machine learning in JavaScript Applications of machine learning Resources to understand machine learning in depth Summary Chapter 10: Introduction to TensorFlow.js Technical requirements What is TensorFlow.js? Installing and using TensorFlow.js Setting up TensorFlow.js in the browser Installing TensorFlow.js in Node.js Tensors and basic operations on tensors Creating tensors Operating on tensors Building a simple regression model with TensorFlow.js Setting up your environment locally Retrieving and processing the training dataset Creating models with TensorFlow.js Creating a simple three-layer regression model Training the model with the processed dataset Making predictions with the trained model Summary Chapter 11: Building a Recommendation System with Danfo.js and TensorFlow.js Technical requirements What is a recommendation system? Collaborative filtering approach Hybrid filtering approach The neural network approach to creating a recommendation system Building a movie recommendation system Setting up your project directory Retrieving and processing the training dataset Building the recommendation model Training and saving the recommendation model Making movie recommendations with the saved model Summary Chapter 12: Building a Twitter Analysis Dashboard Technical requirements Setting up the project environment Building the backend Building the Twitter API Building the text sentiment API Building the frontend Creating the Search component Creating the ValueCounts component Creating a plot component for sentiment analysis Creating a Table component Summary Chapter 13: Appendix: Essential JavaScript Concepts Technical requirements Quick overview of JavaScript Understanding the fundamentals of JavaScript Declaring variables Data types Conditional branching and loops JavaScript functions Summary Why subscribe? 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