The D3js has become a standard for data visualization. We have a lot of libraries for adding charts in Ionic and in these articles we’ll learn and demonstrate an example of D3js in Ionic. We can use Chart.js and angular2-highcharts. Chart.js is easy to use and allow us to build chart quickly as compared to D3. The D3 has a more learning curve as compared to other chart libraries. The D3 allows us to create more complex and provide more flexibility in creating data visualization on the web.
In this example, we will add examples of how to integrate the D3js chart in Ionic. Follow the following step.
Prerequisites:
To create and run an Ionic project, We need Nodejs and Ionic CLI already install in our system, if not then check how to install Nodejs and Ionic in Ubuntu. Ionic CLI allows us to create an Ionic project, generate application and library code, and perform a variety of ongoing development tasks such as testing, bundling, and deployment. To install the Ionic CLI, open a terminal, and run the following command:
npm install -g @ionic/cliCreate and configure the D3js in Ionic apps
With D3 version 4 is a collection of the modules and we can use each module independently, with minimum dependency. In this example of d3js in ionic, we are using the D3 whole module.
ionic start d3js blank
npm install d3 --saveAdd two more pages to our apps for ionic d3js example.
ionic generate page bar-chart
ionic generate page pie-chartStep 2: Set up the Char Template for d3js in Ionic
The D3 uses an SVG element of HTML to display a graphic on the web. We will be creating two different charts on two pages. First, we need to set up the data on which D3 is generating the chart. Create a new folder called data and add data.ts a file in the data folder. Add the following data in the src/data/data.ts file
export const StatsPieChart: any[] = [
{party: 'BJP', electionP: 56},
{party: 'INC', electionP: 18},
{party: 'AA', electionP: 10},
{party: 'CPI', electionP: 5},
{party: 'CPI-M', electionP: 5},
{party: 'BSP', electionP: 7},
{party: 'AITS', electionP: 10}
];
export interface Employee {
company: string;
frequency: number;
}
export const StatsBarChart: Employee[] = [
{company: 'Apple', frequency: 100000},
{company: 'IBM', frequency: 80000},
{company: 'HP', frequency: 20000},
{company: 'Facebook', frequency: 70000},
{company: 'TCS', frequency: 12000},
{company: 'Google', frequency: 110000},
{company: 'Wipro', frequency: 5000},
{company: 'EMC', frequency: 4000}
];Modify the app/bar-chart/bar-chart.page.html file
<ion-header>
<ion-toolbar>
<ion-title>{{ title }}</ion-title>
<ion-buttons slot="end">
<ion-button color="primary" routerLink="/pie-chart">Pie Chart
</ion-button>
</ion-buttons>
</ion-toolbar>
</ion-header>
<ion-content>
<h2>Bar Chart</h2>
<div id="barChart"></div>
<h5 text-center>Employee Statistic of Diff Company</h5>
</ion-content>Modify the app/pie-chart/pie-chart.page.html file
<ion-header>
<ion-toolbar>
<ion-title>{{ title }}</ion-title>
<ion-buttons slot="end">
<ion-button color="primary" routerLink="/bar-chart">Pie Chart
</ion-button>
</ion-buttons>
</ion-toolbar>
</ion-header>
<ion-content>
<div id="pieChart"></div>
<h5 text-center>Election Result of India 2019</h5>
</ion-content>Step 4: Creating a chart of d3js in our ionic app
Now we will generate the two charts, first, we will generate a bar chart. In the bar chart, we generate a bar chart on the number of employees in a popular IT company. This is just fake data, for example, we are using it.
Modify the following code in app/bar-chart/bar-chart.page.ts
import { Component, OnInit } from '@angular/core';
import { StatsBarChart } from '../../assets/data/data';
import * as d3 from 'd3-selection';
import * as d3Scale from 'd3-scale';
import * as d3Array from 'd3-array';
import * as d3Axis from 'd3-axis';
@Component({
selector: 'app-bar-chart',
templateUrl: './bar-chart.page.html',
styleUrls: ['./bar-chart.page.scss'],
})
export class BarChartPage implements OnInit {
title = 'D3 Barchart with Ionic 4';
width: number;
height: number;
margin = { top: 20, right: 20, bottom: 30, left: 40 };
x: any;
y: any;
svg: any;
g: any;
constructor() {
this.width = 900 - this.margin.left - this.margin.right;
this.height = 500 - this.margin.top - this.margin.bottom;
}
ngOnInit() {
this.initSvg();
this.initAxis();
this.drawAxis();
this.drawBars();
}
initSvg() {
this.svg = d3.select('#barChart')
.append('svg')
.attr('width', '100%')
.attr('height', '100%')
.attr('viewBox', '0 0 900 500');
this.g = this.svg.append('g')
.attr('transform', 'translate(' + this.margin.left + ',' + this.margin.top + ')');
}
initAxis() {
this.x = d3Scale.scaleBand().rangeRound([0, this.width]).padding(0.1);
this.y = d3Scale.scaleLinear().rangeRound([this.height, 0]);
this.x.domain(StatsBarChart.map((d) => d.company));
this.y.domain([0, d3Array.max(StatsBarChart, (d) => d.frequency)]);
}
drawAxis() {
this.g.append('g')
.attr('class', 'axis axis--x')
.attr('transform', 'translate(0,' + this.height + ')')
.call(d3Axis.axisBottom(this.x));
this.g.append('g')
.attr('class', 'axis axis--y')
.call(d3Axis.axisLeft(this.y))
.append('text')
.attr('class', 'axis-title')
.attr('transform', 'rotate(-90)')
.attr('y', 6)
.attr('dy', '0.71em')
.attr('text-anchor', 'end')
.text('Frequency');
}
drawBars() {
this.g.selectAll('.bar')
.data(StatsBarChart)
.enter().append('rect')
.attr('class', 'bar')
.attr('x', (d) => this.x(d.company))
.attr('y', (d) => this.y(d.frequency))
.attr('width', this.x.bandwidth())
.attr('height', (d) => this.height - this.y(d.frequency));
}
}As we know that D3 is a collection of modules, we are importing some of the different modules needed to generate a bar chart in ionic.
Modify the following code in src/pages/pie-chart/pie-chart.page.ts
import { Component, OnInit } from '@angular/core';
import { StatsPieChart } from '../../assets/data/data';
import * as d3 from 'd3-selection';
import * as d3Scale from 'd3-scale';
import * as d3Shape from 'd3-shape';
@Component({
selector: 'app-pie-chart',
templateUrl: './pie-chart.page.html',
styleUrls: ['./pie-chart.page.scss'],
})
export class PieChartPage implements OnInit {
title = 'D3 Pie Chart in Ionic 4';
margin = {top: 20, right: 20, bottom: 30, left: 50};
width: number;
height: number;
radius: number;
arc: any;
labelArc: any;
labelPer: any;
pie: any;
color: any;
svg: any;
constructor() {
this.width = 900 - this.margin.left - this.margin.right ;
this.height = 500 - this.margin.top - this.margin.bottom;
this.radius = Math.min(this.width, this.height) / 2;
}
ngOnInit() {
this.initSvg();
this.drawPie();
}
initSvg() {
this.color = d3Scale.scaleOrdinal()
.range(['#FFA500', '#00FF00', '#FF0000', '#6b486b', '#FF00FF', '#d0743c', '#00FA9A']);
this.arc = d3Shape.arc()
.outerRadius(this.radius - 10)
.innerRadius(0);
this.labelArc = d3Shape.arc()
.outerRadius(this.radius - 40)
.innerRadius(this.radius - 40);
this.labelPer = d3Shape.arc()
.outerRadius(this.radius - 80)
.innerRadius(this.radius - 80);
this.pie = d3Shape.pie()
.sort(null)
.value((d: any) => d.electionP);
this.svg = d3.select('#pieChart')
.append('svg')
.attr('width', '100%')
.attr('height', '100%')
.attr('viewBox', '0 0 ' + Math.min(this.width, this.height) + ' ' + Math.min(this.width, this.height))
.append('g')
.attr('transform', 'translate(' + Math.min(this.width, this.height) / 2 + ',' + Math.min(this.width, this.height) / 2 + ')');
}
drawPie() {
const g = this.svg.selectAll('.arc')
.data(this.pie(StatsPieChart))
.enter().append('g')
.attr('class', 'arc');
g.append('path').attr('d', this.arc)
.style('fill', (d: any) => this.color(d.data.party) );
g.append('text').attr('transform', (d: any) => 'translate(' + this.labelArc.centroid(d) + ')')
.attr('dy', '.35em')
.text((d: any) => d.data.party);
g.append('text').attr('transform', (d: any) => 'translate(' + this.labelPer.centroid(d) + ')')
.attr('dy', '.35em')
.text((d: any) => d.data.electionP + '%');
}
}We can modify the data to change to generate different pie and bar charts and we can use the same method to generate different graphics of D3 in ionic.
Conclusion
We have completed our example on how to implement D3js in Ionic. The D3 stands for data-driven document and is one most popular open-source Javascript libraries is generating visual representations of our data.
