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Building Data-Driven Applications with Danfo.js

Building Data-Driven Applications with Danfo.js

By : Odegua, Oni
3.8 (4)
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Building Data-Driven Applications with Danfo.js

Building Data-Driven Applications with Danfo.js

3.8 (4)
By: Odegua, Oni

Overview of this book

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.
Table of Contents (18 chapters)
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1
Section 1: The Basics
3
Section 2: Data Analysis and Manipulation with Danfo.js and Dnotebook
10
Section 3: Building Data-Driven Applications

Creating histograms with Danfo.js

A histogram, as we explained earlier, is a representation of the spread of data. The hist function exposed by the plot namespace can be used to make histograms from DataFrames or Series, as we'll demonstrate in the following section.

Creating a histogram from a Series

In order to create a histogram from a Series, you can call the hist function on the Series, or if plotting on a DataFrame, you can subset the DataFrame with the column name, as shown in the following example:

var layout = {
   title: "Histogram on a Series data",
}
var config = { 
  layout 
} 
new_df["AAPL.Open"].plot(this_div()).hist(config)

Running the preceding code cell gives the following output:

Figure 6.16 – Histogram on Series data

Next, we'll make a histogram for more than one column in a DataFrame at a time.

Creating a histogram from multiple columns

If you want to make...

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