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Rodney Vg


Data Visualization with Vue and D3.js

What is D3?

As you can read on the project’s home page, D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS. Its emphasis on web standards gives you the full capabilities of modern browsers without tying yourself to a proprietary framework.

Whereas most people will refer to D3.js as a data visualization library, it’s not. D3 is more of a framework comprising different parts — such as jQuery parts (which help us select and manipulate DOM elements), Lodash parts, animation parts, data analysis parts, and data visualization parts.

In this tutorial, we’ll be working with the visualization aspect of D3. The real meat of D3 when visualizing data is:

  • the availability of functions for decorating data with drawing instructions
  • creating new drawable data from source data
  • generating SVG paths
  • creating data visualization elements (like an axis) in the DOM from your data and methods

What We’ll Be Building

We want to create an app that lets users search for a repo on GitHub, then get a visual representation of issues opened in the past week that are still open. The end result will look like this:


This tutorial assumes you have a working knowledge of Vue. Previous knowledge of D3.js isn’t required, but if you’d like to get up to speed quickly, you might want to read our D3 by example tutorial.

You’ll also need to have Node installed on your system. You can do this by downloading the binaries for your system from the official website, or using a version manager.

Finally, we’ll be using the following packages to build our app:

  • Vue CLI — to scaffold out the project
  • D3.js — to visualize our data
  • Lodash — which provides a handful of utility methods
  • Moment JS — for date and time formatting
  • axios — an HTTP client to help us make requests to an external API

New Vue Project

I prefer creating new Vue projects using Vue CLI. (If you’re not familiar with Vue CLI, our beginner’s guide in this Vue series gives a full introduction.) Vue CLI provides a nice folder structure for placing different sections of the code, such as styles, components, and so on.

Make sure that the CLI is installed on your machine:

npm install -g @vue/cli

Then create a new project with the following command:

vue create issues-visualization

Note: while creating a new project using Vue CLI, you’ll be prompted to pick a preset. For this particular project, we’ll just stick with the default (Babel + ESLint).

Once our new Vue project has been created, we cd into the project folder and add the various node modules we’ll need:

npm install lodash d3 axios moment

Even though this is a simple app that doesn’t have many running parts, we’ll still take the components approach instead of dumping all the code inside the App.vue file. We’re going to have two components, the App component and a Chartcomponent that we’re yet to create.

The App component will handle fetching data from GitHub, then pass this data to the Chart component as props. The actual drawing of the chart will happen inside the Chart component. Structuring things this way has the advantage that, if you want to use a library other than axios to fetch the data, it’ll be easier to swap it out. Also, if you want to swap D3 for a different charting library, that’ll be easier too.

Building the Search Interface

We’ll start by building a search interface that lets users enter the name of the repo they want to see visualized.

In src/App.vue, get rid of everything inside the <template> tag and replace the content with this:

  <div id="app">
    <form action="#" @submit.prevent="getIssues">
      <div class="form-group">
          placeholder="owner/repo Name"
          class="col-md-2 col-md-offset-5"

Here we have a form which, upon submission, prevents the browser’s default submission action, then calls a getIssuesmethod that we’re yet to define. We’re also using a v-model directive to bind the input from the form to a repositoryproperty inside the data model of our Vue instance. Let’s declare that property repository as an empty string. We’ll also add a startDate property, which we’ll later use as the first date in our time range:

import moment from "moment";
import axios from "axios";

export default {
  name: "app",
  data() {
    return {
      issues: [],
      repository: "",
      startDate: null
  methods: {
    getIssues() {
      // code goes in here

Now on to creating the getIssues method:

getIssues() {
  this.startDate = moment()
    .subtract(6, "days")

      { params: { per_page: 100 } }
    .then(response => {
      const payload = this.getDateRange(); => {
        const key = moment(item.created_at).format("MMM Do YY");
        const obj = payload.filter(o => === key)[0];
        obj.issues += 1;

      this.issues = payload;

In the above block of code, we start by setting the startDate data property to six days ago and formatting it for use with the GitHub API.

We then use axios to make an API request to GitHub to get all issues for a particular repository that were opened in the past week and that are still open. You can refer to GitHub’s search API if you need more examples on how to come up with query string parameters.

When making the HTTP request, we set the results count to 100 per page (the max possible). There are hardly any repositories with over 100 new issues per week, so this should be fine for our purposes. By default, the per_page value is 30.

If the request completes successfully, we use a custom getDateRange method to initialize a payload variable that we will be able to pass to the Chart component. This payload is an array of objects that will like so:

  {day: "Dec 7th 18", issues: 0},
  {day: "Dec 8th 18", issues: 0},
  {day: "Dec 9th 18", issues: 0},
  {day: "Dec 10th 18", issues: 0},
  {day: "Dec 11th 18", issues: 0},
  {day: "Dec 12th 18", issues: 0},
  {day: "Dec 13th 18", issues: 0}

After that, we iterate over the API’s response. The data we’re interested in is in an items key on a data property on the response object. From this, we take the created_at key (which is a timestamp) and format it as the day property in our objects above. From there, we then look up the corresponding date in the payload array and increment the issues count for that date by one.

Finally, we assign the payload array to our issues data property and log the response.

Next, let’s add in the getDateRange method:

methods: {
  getDateRange() {
    const startDate = moment().subtract(6, 'days');
    const endDate = moment();
    const dates = [];

    while (startDate.isSameOrBefore(endDate)) {
        day: startDate.format('MMM Do YY'),
        issues: 0

      startDate.add(1, 'days');

    return dates;
  getIssues() { ... }

Before we get to the visualization bit, let’s also log any errors we might encounter when making our request to the console (for debugging purposes):

  .get( ...)
  .then(response => {
  .catch(error => {

We’ll add some UX for informing the user in the case that something went wrong later.

So far, we have an input field that lets the user enter the organization/repository name they wish to search issues for. Upon form submission, all issues opened in the past one week are logged to the console.

Below is an example of what was logged on the console for the facebook/react repo:

If you start up the Vue dev server using npm run serve and enter some different repos, you should see something similar. If you’re stuck for inspiration, check out GitHub’s Trending page.

Next comes the fun bit — visualizing this data.

Drawing a Bar Chart Using D3

Earlier on, we mentioned that all the drawing will be handled inside a Chart component. Let’s create the component:

touch src/components/Chart.vue

D3 works on SVG elements, and for us to draw anything with D3, we need to have an SVG element on the page. In our newly created component (src/components/Chart.vue), let’s create an SVG tag:


For this particular tutorial, we’ll visualize our data using a bar chart. I picked a bar chart because it represents a low complexity visual element while it teaches the basic application of D3.js itself. The bar chart is also a good intro to the most important D3 concepts, while still having fun!

Before proceeding, let’s update our App component to include the newly created Chart component below the form:

  <div id="app">
    <form action="#" @submit.prevent="getIssues">

    <chart :issues="issues"></chart>

Let’s also register it as a component:

import Chart from './components/Chart.vue';

export default {
  name: "app",
  components: {

Notice how we’re passing the value of the issues data property to the Chart component as a prop:

<chart :issues="issues"></chart>

Let’s now update our Chart component to make use of that data:

import * as d3 from "d3";
import _ from "lodash";

export default {
  props: ["issues"],
  data() {
    return {
      chart: null
  watch: {
    issues(val) {
      if (this.chart != null) this.chart.remove();
  methods: {
    renderChart(issues_val) {
      // Chart will be drawn here

In the above code block, we’re importing D3 and Lodash. We then instantiate a chart data property as null. We’ll assign a value to this when we start drawing later on.

Since we want to draw the chart every time the value of issues changes, we’ve created a watcher for issues. Each time this value changes, we’ll destroy the old chart and then draw a new chart.

Drawing will happen inside the renderChart method. Let’s start fleshing that out:

renderChart(issues_val) {
  const margin = 60;
  const svg_width = 1000;
  const svg_height = 600;
  const chart_width = 1000 - 2 * margin;
  const chart_height = 600 - 2 * margin;

  const svg = d3
    .attr("width", svg_width)
    .attr("height", svg_height);

Here, we set the height and width of the SVG element we just created. The margin attribute is what we’ll use to give our chart some padding.

D3 comes with DOM selection and manipulation capabilities. Throughout the tutorial, you’ll see lot’s of and d3.selectAll statements. The difference is that select will return the first matching element while selectAll returns all matching elements.

The Axes

For bar charts, data can either be represented in a vertical or horizontal format. D3 comes with axis methods, which let us define our axes the way we want:

  • axisLeft
  • axisTop
  • axisBottom
  • axisRight

Today, we’ll be creating a vertical bar chart. For vertical bar charts, we’ll only need the axisLeft and axisBottommethods:

renderChart(issues_val) {

  this.chart = svg
    .attr("transform", `translate(${margin}, ${margin})`);

  const yScale = d3
    .range([chart_height, 0])
    .domain([0, _.maxBy(issues_val, "issues").issues]);

    .call(d3.axisLeft(yScale).ticks(_.maxBy(issues_val, "issues").issues));

  const xScale = d3
    .range([0, chart_width])
    .domain( =>

    .attr("transform", `translate(0, ${chart_height})`)

The above block of code draws axes on the SVG element. Let’s go through it step by step:

this.chart = svg.append('g')
  .attr('transform', `translate(${margin}, ${margin})`);

We first specify where we want our chart to start within the SVG element. When working with D3, for any element we want to be added to the SVG, we usually call the append method, then define attributes for this new element.

To add attributes to an element, we usually call the attr method, which takes in two parameters. The first parameter is the attribute we want to apply to the selected DOM element, and the second parameter is the value we want, or a callback function that returns the desired value. Here we’re moving the start of the chart to the 60, 60 position of the SVG:

const yScale = d3.scaleLinear()
  .range([chart_height, 0])
  .domain([0, _.maxBy(issues_val, 'issues').issues]);

  .ticks(_.maxBy(issues_val, 'issues').issues));

This codeblock draws the y-axis while making use of D3 scales to come up with a y-scale. Scales are functions that will transform our data by either increasing or decreasing its value for better visualization.

The range function specifies the length that should be divided between the limits of the input data. You may have noticed I used height as the first parameter and not zero when calling range. This is because the SVG coordinate system starts from the top left corner. You’ll get to understand this better when we get to draw the bar heights.

On the other hand, the domain function denotes minimum and maximum values of the input data. For this particular data set, we want to start from zero to the highest value in our data set. Think of the domain as the input and range as the output.

After defining a y-scale, we make use of this scale to draw the axis by calling the axisLeft method, which takes in the y-scale as the argument.

The snippet below draws the x-axis:

const xScale = d3.scaleBand()
  .range([0, chart_width])
  .domain( =>

  .attr('transform', `translate(0, ${chart_height})`)

For the xScale we use the scaleBand function, which helps to split the range into bands and compute the coordinates and widths of the bars with additional padding. Assuming 3 is the maximum number of issues raised across all dates, the chart output should look like this:

If you test this in your browser with the code we’ve covered so far, you should see something similar.

Now enough with the axes. Let’s spit some bars!

Drawing Bars

For our bar chart, the bar width will be fixed and the bar height will vary depending on the dataset size:

renderChart(issues_val) {

  const barGroups = this.chart

    .attr("class", "bar")
    .attr("x", g => xScale(
    .attr("y", g => yScale(g.issues))
    .attr("height", g => chart_height - yScale(g.issues))
    .attr("width", xScale.bandwidth());

Let’s address how we added the bars. First, we created a barGroups element:

const barGroups = this.chart

Calling the selectAll method on our chart returns an empty selection/array, since we don’t have any rectangles in our chart so far. We then chain the data method, passing in the dataset we want visualized. This puts the data in a waiting state for further processing.

The next step is to chain the enter method. The enter method looks both at the data set we passed into data() and at the selection we get after calling selectAll(), and then tries to look for “matches” — more like mapping between our sample data and elements already present in the DOM. In this particular case, no matches were found.

Note: this article is an excellent guide for understanding the <em>select</em>, <em>enter</em> and <em>append</em> sequence when working with D3 to manipulate the DOM.

Since selectAll('rect') returned an empty array, the enter method will return a new selection representing the elements in our data set.

Note that, after chaining enter(), every item in the returned array is acted upon individually. This means that any method chained onto barGroups will define the behavior of individual items.

  .attr('class', 'bar')
  .attr('x', (g) => xScale(
  .attr('y', (g) => yScale(g.issues))
  .attr('height', (g) => chart_height - yScale(g.issues))
  .attr('width', xScale.bandwidth());

The code block above creates a rectangle for each item in our in our data set. We give each of these rectangles a class of bar.

To set the x and y coordinates for the rectangles, we use the scaling functions we defined earlier. So far, these rectangles are sitting on top of each other, and we need to give our rectangles some height and width.

The width of our bars would be determined by the scaleBand function. Chaining the bandwidth function to the xScalereturns a calculated bandwidth from the range and padding provided to the x-scale.

To set the bar height, we subtract the computed y-coordinate of the bar from the height of the SVG to get the correct representation of the value as a column. Remember that, when working with SVGs, x and y coordinates are always calculated starting from the top-left corner.

Adding Labels

So far we have a bar chart. But this chart is not really helpful, as it doesn’t tell the user what each axis represents. To give our chart more context, we’ll have to add labels for the axes as well as a chart title.

To add labels, we append text elements to our SVG:

  .attr('class', 'label')
  .attr('x', -(chart_height / 2) - margin)
  .attr('y', margin / 2.4)
  .attr('transform', 'rotate(-90)')
  .attr('text-anchor', 'middle')
  .text('Issues opened')

  .attr('class', 'label')
  .attr('x', chart_width / 2 + margin)
  .attr('y', chart_height + margin * 1.7)
  .attr('text-anchor', 'middle')

  .attr('class', 'title')
  .attr('x', chart_width / 2 + margin)
  .attr('y', 40)
  .attr('text-anchor', 'middle')
  .text('Issues in the past 1 week')

The text elements can be positioned with x and y coordinates while text alignment is done with the text-anchor attribute. To add the text itself, we call the text method on the text element.

We can test things out by serving our app then searching for a repo. Search for any popular repo — such as facebook/react:

Back in our App component, we can now get rid of the console statement inside the getIssues method:


Even though our chart does an excellent job of visualizing our data, there’s still much to be done in terms of the user experience. In the next section, we’ll look at how to add transitions to D3 charts.

Adding Transitions

For this particular chart, we want to make it such that, when one hovers over a bar element, its shade changes and the number of issues represented by the bar shows up at the top of the bar.

For this to happen, we have to do some event handling on mouseEnter and mouseLeave for the barGroups.

Edit the barGroups code block above the three svg blocks:

  .attr("width", xScale.bandwidth())
  .on("mouseenter", function(actual, i) {
      .attr("opacity", 0.6)
      .attr("x", a => xScale( - 5)
      .attr("width", xScale.bandwidth() + 10);
      .attr("class", "value")
      .attr("x", a => xScale( + xScale.bandwidth() / 2)
      .attr("y", a => yScale(a.issues) - 20)
      .attr("text-anchor", "middle")
      .text((a, idx) => {
        return idx !== i ? "" : `${a.issues} issues`;

We call the transition method to add animations to an element when working with D3.

Each time the cursor hovers over a bar, we reduce the opacity of the bar and increase the width by 10px. We also add text on top of the bar, stating the number of issues the bar represents. This transition takes a duration of 300 milliseconds.

Since we don’t want to leave this bar in the new state when the mouse leaves, let’s define a mouseleave event, which removes the selection features we had applied in the mouseenter event:

  .attr("width", xScale.bandwidth())
  .on("mouseenter", function(actual, i) { ... })
  .on("mouseleave", function() {
    d3.selectAll(".issues").attr("opacity", 1);
      .attr("opacity", 1)
      .attr("x", a => xScale(
      .attr("width", xScale.bandwidth());


What we are doing above is setting the opacity of the bar to the original value and also removing the text from the bar.


The code above removes any text on the DOM that has a class of value.

Here’s the final result:

If you try things out in your browser now, you should see something like the above.

Some Final UI/UX Touches

When making the request to GitHub, we anticipate some loading time before getting a response back from GitHub. For UX purposes, we’ll make the user aware we’re still retrieving results from GitHub by flashing a loading alert on the page. In the App component, add this snippet to the HTML section of your code — right above the Chart component:

<div class="alert alert-info" v-show="loading">Loading...</div>
<chart :issues="issues"></chart>

For prototyping purposes, we’ll leverage Bootstrap. Vue has an official Bootstrap package that we’re going to install:

npm install bootstrap-vue

Once the package has been installed, we’ll have to import Bootstrap’s CSS classes to our main.js file to make the alert show up:

import "bootstrap/dist/css/bootstrap.css";
import "bootstrap-vue/dist/bootstrap-vue.css";

We’re almost done, but we need to add a loading attribute to our data model — whose value will determine whether or not to show the loading alert:

data() {
  return {
    loading: false,

Every time we make a new request, we’ll set the value of loading to true, so the alert shows up, and then we’ll finally set this value to false for successful requests or in the case the app errored:

getIssues() {
  this.loading = true;
  axios.get( ... )
  .then( ... )
  .catch( ... )
  .finally(() => (this.loading = false));

Error Handling

As it stands, we’re just logging any errors we might run into on the console — something the user isn’t aware of. To make the user is aware if something goes wrong when making the request, we’ll flash an error alert on the page. Add this snippet below the loading alert we just created:

<div class="alert alert-danger" v-show="errored">An error occured</div>
<chart :issues="issues"></chartchart>

We also need to update our data model with the errored attribute, which we initialize with a false value:

data() {
  return {
    loading: false,
    errored: false,

We’ll set the errored value to true every time we run into an error. This should happen inside the catch block:

getIssues() {
  this.loading = true;
  this.errored = false;
  axios.get( ... )
  .then( ... )
  .catch(error => {
    this.errored = true;
  .finally( ... );

Some Basic Styling

Eagle-eyed readers will have noticed that in the screen shot at the top of this guide, the color of the bars was blue. Let’s add that as a final touch to our App component:

.bar {
  fill: #319bbe;


Congratulations for making it to this point. Even though we have a working bar chart, there’s still more we can do to make the chart more visually appealing. We could, for example, add grid lines, or alternatively visualize this data using a line chart.

What we drew was a simple bar chart, but D3.js has amazing capabilities in terms of what you can do. Any data visualization that you’ve seen anywhere — including powerpoint presentations — can probably be handled by D3. This article is a good read for some of the things D3 is capable of doing. You can also check out D3 on GitHub to see other use cases.

Further reading:

React vs Vue – Choosing the Best JavaScript Library

Set Up a Vue.js Development Environment

10+ Top Vue.js Tools & Libraries

How to Enforcing Rules in JS with Getters and Setters

Vue.js Pattern for Async Requests: Using Renderless Components

#vue-js #javascript

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Data Visualization with Vue and D3.js
Aria Barnes

Aria Barnes


Why is Vue JS the most Preferred Choice for Responsive Web Application Development?

For more than two decades, JavaScript has facilitated businesses to develop responsive web applications for their customers. Used both client and server-side, JavaScript enables you to bring dynamics to pages through expanded functionality and real-time modifications.

Did you know!

According to a web development survey 2020, JavaScript is the most used language for the 8th year, with 67.7% of people choosing it. With this came up several javascript frameworks for frontend, backend development, or even testing.

And one such framework is Vue.Js. It is used to build simple projects and can also be advanced to create sophisticated apps using state-of-the-art tools. Beyond that, some other solid reasons give Vuejs a thumbs up for responsive web application development.

Want to know them? Then follow this blog until the end. Through this article, I will describe all the reasons and benefits of Vue js development. So, stay tuned.

Vue.Js - A Brief Introduction

Released in the year 2014 for public use, Vue.Js is an open-source JavaScript framework used to create UIs and single-page applications. It has over 77.4 million likes on Github for creating intuitive web interfaces.

The recent version is Vue.js 2.6, and is the second most preferred framework according to Stack Overflow Developer Survey 2019.

Every Vue.js development company is widely using the framework across the world for responsive web application development. It is centered around the view layer, provides a lot of functionality for the view layer, and builds single-page web applications.

Some most astonishing stats about Vue.Js:

• Vue was ranked #2 in the Front End JavaScript Framework rankings in the State of JS 2019 survey by developers.

• Approximately 427k to 693k sites are built with Vue js, according to Wappalyzer and BuiltWith statistics of June 2020.

• According to the State of JS 2019 survey, 40.5% of JavaScript developers are currently using Vue, while 34.5% have shown keen interest in using it in the future.

• In Stack Overflow's Developer Survey 2020, Vue was ranked the 3rd most popular front-end JavaScript framework.

Why is Vue.Js so popular?

• High-speed run-time performance
• Vue.Js uses a virtual DOM.
• The main focus is on the core library, while the collaborating libraries handle other features such as global state management and routing.
• Vue.JS provides responsive visual components.

Top 7 Reasons to Choose Vue JS for Web Application Development

Vue js development has certain benefits, which will encourage you to use it in your projects. For example, Vue.js is similar to Angular and React in many aspects, and it continues to enjoy increasing popularity compared to other frameworks.

The framework is only 20 kilobytes in size, making it easy for you to download files instantly. Vue.js easily beats other frameworks when it comes to loading times and usage.

Take a look at the compelling advantages of using Vue.Js for web app development.

#1 Simple Integration

Vue.Js is popular because it allows you to integrate Vue.js into other frameworks such as React, enabling you to customize the project as per your needs and requirements.

It helps you build apps with Vue.js from scratch and introduce Vue.js elements into their existing apps. Due to its ease of integration, Vue.js is becoming a popular choice for web development as it can be used with various existing web applications.

You can feel free to include Vue.js CDN and start using it. Most third-party Vue components and libraries are additionally accessible and supported with the Vue.js CDN.

You don't need to set up node and npm to start using Vue.js. This implies that it helps develop new web applications, just like modifying previous applications.

The diversity of components allows you to create different types of web applications and replace existing frameworks. In addition, you can also choose to hire Vue js developers to use the technology to experiment with many other JavaScript applications.

#2 Easy to Understand

One of the main reasons for the growing popularity of Vue.Js is that the framework is straightforward to understand for individuals. This means that you can easily add Vue.Js to your web projects.

Also, Vue.Js has a well-defined architecture for storing your data with life-cycle and custom methods. Vue.Js also provides additional features such as watchers, directives, and computed properties, making it extremely easy to build modern apps and web applications with ease.

Another significant advantage of using the Vue.Js framework is that it makes it easy to build small and large-scale web applications in the shortest amount of time.

#3 Well-defined Ecosystem

The VueJS ecosystem is vibrant and well-defined, allowing Vue.Js development company to switch users to VueJS over other frameworks for web app development.

Without spending hours, you can easily find solutions to your problems. Furthermore, VueJs lets you choose only the building blocks you need.

Although the main focus of Vue is the view layer, with the help of Vue Router, Vue Test Utils, Vuex, and Vue CLI, you can find solutions and recommendations for frequently occurring problems.

The problems fall into these categories, and hence it becomes easy for programmers to get started with coding right away and not waste time figuring out how to use these tools.

The Vue ecosystem is easy to customize and scales between a library and a framework. Compared to other frameworks, its development speed is excellent, and it can also integrate different projects. This is the reason why most website development companies also prefer the Vue.Js ecosystem over others.

#4 Flexibility

Another benefit of going with Vue.Js for web app development needs is flexibility. Vue.Js provides an excellent level of flexibility. And makes it easier for web app development companies to write their templates in HTML, JavaScript, or pure JavaScript using virtual nodes.

Another significant benefit of using Vue.Js is that it makes it easier for developers to work with tools like templating engines, CSS preprocessors, and type checking tools like TypeScript.

#5 Two-Way Communication

Vue.Js is an excellent option for you because it encourages two-way communication. This has become possible with the MVVM architecture to handle HTML blocks. In this way, Vue.Js is very similar to Angular.Js, making it easier to handle HTML blocks as well.

With Vue.Js, two-way data binding is straightforward. This means that any changes made by the developer to the UI are passed to the data, and the changes made to the data are reflected in the UI.

This is also one reason why Vue.Js is also known as reactive because it can react to changes made to the data. This sets it apart from other libraries such as React.Js, which are designed to support only one-way communication.

#6 Detailed Documentation

One essential thing is well-defined documentation that helps you understand the required mechanism and build your application with ease. It shows all the options offered by the framework and related best practice examples.

Vue has excellent docs, and its API references are one of the best in the industry. They are well written, clear, and accessible in dealing with everything you need to know to build a Vue application.

Besides, the documentation at Vue.js is constantly improved and updated. It also includes a simple introductory guide and an excellent overview of the API. Perhaps, this is one of the most detailed documentation available for this type of language.

#7 Large Community Support

Support for the platform is impressive. In 2018, support continued to impress as every question was answered diligently. Over 6,200 problems were solved with an average resolution time of just six hours.

To support the community, there are frequent release cycles of updated information. Furthermore, the community continues to grow and develop with backend support from developers.

Wrapping Up

VueJS is an incredible choice for responsive web app development. Since it is lightweight and user-friendly, it builds a fast and integrated web application. The capabilities and potential of VueJS for web app development are extensive.

While Vuejs is simple to get started with, using it to build scalable web apps requires professionalism. Hence, you can approach a top Vue js development company in India to develop high-performing web apps.

Equipped with all the above features, it doesn't matter whether you want to build a small concept app or a full-fledged web app; Vue.Js is the most performant you can rely on.

Original source


#vue js development company #vue js development company in india #vue js development company india #vue js development services #vue js development #vue js development companies

 iOS App Dev

iOS App Dev


Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition

NBB: Ad-hoc CLJS Scripting on Node.js


Not babashka. Node.js babashka!?

Ad-hoc CLJS scripting on Node.js.


Experimental. Please report issues here.

Goals and features

Nbb's main goal is to make it easy to get started with ad hoc CLJS scripting on Node.js.

Additional goals and features are:

  • Fast startup without relying on a custom version of Node.js.
  • Small artifact (current size is around 1.2MB).
  • First class macros.
  • Support building small TUI apps using Reagent.
  • Complement babashka with libraries from the Node.js ecosystem.


Nbb requires Node.js v12 or newer.

How does this tool work?

CLJS code is evaluated through SCI, the same interpreter that powers babashka. Because SCI works with advanced compilation, the bundle size, especially when combined with other dependencies, is smaller than what you get with self-hosted CLJS. That makes startup faster. The trade-off is that execution is less performant and that only a subset of CLJS is available (e.g. no deftype, yet).


Install nbb from NPM:

$ npm install nbb -g

Omit -g for a local install.

Try out an expression:

$ nbb -e '(+ 1 2 3)'

And then install some other NPM libraries to use in the script. E.g.:

$ npm install csv-parse shelljs zx

Create a script which uses the NPM libraries:

(ns script
  (:require ["csv-parse/lib/sync$default" :as csv-parse]
            ["fs" :as fs]
            ["path" :as path]
            ["shelljs$default" :as sh]
            ["term-size$default" :as term-size]
            ["zx$default" :as zx]
            ["zx$fs" :as zxfs]
            [nbb.core :refer [*file*]]))

(prn (path/resolve "."))

(prn (term-size))

(println (count (str (fs/readFileSync *file*))))

(prn (sh/ls "."))

(prn (csv-parse "foo,bar"))

(prn (zxfs/existsSync *file*))

(zx/$ #js ["ls"])

Call the script:

$ nbb script.cljs
#js {:columns 216, :rows 47}
#js ["node_modules" "package-lock.json" "package.json" "script.cljs"]
#js [#js ["foo" "bar"]]
$ ls


Nbb has first class support for macros: you can define them right inside your .cljs file, like you are used to from JVM Clojure. Consider the plet macro to make working with promises more palatable:

(defmacro plet
  [bindings & body]
  (let [binding-pairs (reverse (partition 2 bindings))
        body (cons 'do body)]
    (reduce (fn [body [sym expr]]
              (let [expr (list '.resolve 'js/Promise expr)]
                (list '.then expr (list 'clojure.core/fn (vector sym)

Using this macro we can look async code more like sync code. Consider this puppeteer example:

(-> (.launch puppeteer)
      (.then (fn [browser]
               (-> (.newPage browser)
                   (.then (fn [page]
                            (-> (.goto page "")
                                (.then #(.screenshot page #js{:path "screenshot.png"}))
                                (.catch #(js/console.log %))
                                (.then #(.close browser)))))))))

Using plet this becomes:

(plet [browser (.launch puppeteer)
       page (.newPage browser)
       _ (.goto page "")
       _ (-> (.screenshot page #js{:path "screenshot.png"})
             (.catch #(js/console.log %)))]
      (.close browser))

See the puppeteer example for the full code.

Since v0.0.36, nbb includes promesa which is a library to deal with promises. The above plet macro is similar to promesa.core/let.

Startup time

$ time nbb -e '(+ 1 2 3)'
nbb -e '(+ 1 2 3)'   0.17s  user 0.02s system 109% cpu 0.168 total

The baseline startup time for a script is about 170ms seconds on my laptop. When invoked via npx this adds another 300ms or so, so for faster startup, either use a globally installed nbb or use $(npm bin)/nbb script.cljs to bypass npx.


NPM dependencies

Nbb does not depend on any NPM dependencies. All NPM libraries loaded by a script are resolved relative to that script. When using the Reagent module, React is resolved in the same way as any other NPM library.


To load .cljs files from local paths or dependencies, you can use the --classpath argument. The current dir is added to the classpath automatically. So if there is a file foo/bar.cljs relative to your current dir, then you can load it via (:require [ :as fb]). Note that nbb uses the same naming conventions for namespaces and directories as other Clojure tools: foo-bar in the namespace name becomes foo_bar in the directory name.

To load dependencies from the Clojure ecosystem, you can use the Clojure CLI or babashka to download them and produce a classpath:

$ classpath="$(clojure -A:nbb -Spath -Sdeps '{:aliases {:nbb {:replace-deps {com.github.seancorfield/honeysql {:git/tag "v2.0.0-rc5" :git/sha "01c3a55"}}}}}')"

and then feed it to the --classpath argument:

$ nbb --classpath "$classpath" -e "(require '[honey.sql :as sql]) (sql/format {:select :foo :from :bar :where [:= :baz 2]})"
["SELECT foo FROM bar WHERE baz = ?" 2]

Currently nbb only reads from directories, not jar files, so you are encouraged to use git libs. Support for .jar files will be added later.

Current file

The name of the file that is currently being executed is available via nbb.core/*file* or on the metadata of vars:

(ns foo
  (:require [nbb.core :refer [*file*]]))

(prn *file*) ;; "/private/tmp/foo.cljs"

(defn f [])
(prn (:file (meta #'f))) ;; "/private/tmp/foo.cljs"


Nbb includes reagent.core which will be lazily loaded when required. You can use this together with ink to create a TUI application:

$ npm install ink


(ns ink-demo
  (:require ["ink" :refer [render Text]]
            [reagent.core :as r]))

(defonce state (r/atom 0))

(doseq [n (range 1 11)]
  (js/setTimeout #(swap! state inc) (* n 500)))

(defn hello []
  [:> Text {:color "green"} "Hello, world! " @state])

(render (r/as-element [hello]))


Working with callbacks and promises can become tedious. Since nbb v0.0.36 the promesa.core namespace is included with the let and do! macros. An example:

(ns prom
  (:require [promesa.core :as p]))

(defn sleep [ms]
   (fn [resolve _]
     (js/setTimeout resolve ms))))

(defn do-stuff
   (println "Doing stuff which takes a while")
   (sleep 1000)

(p/let [a (do-stuff)
        b (inc a)
        c (do-stuff)
        d (+ b c)]
  (prn d))
$ nbb prom.cljs
Doing stuff which takes a while
Doing stuff which takes a while

Also see API docs.


Since nbb v0.0.75 applied-science/js-interop is available:

(ns example
  (:require [applied-science.js-interop :as j]))

(def o (j/lit {:a 1 :b 2 :c {:d 1}}))

(prn (j/select-keys o [:a :b])) ;; #js {:a 1, :b 2}
(prn (j/get-in o [:c :d])) ;; 1

Most of this library is supported in nbb, except the following:

  • destructuring using :syms
  • property access using .-x notation. In nbb, you must use keywords.

See the example of what is currently supported.


See the examples directory for small examples.

Also check out these projects built with nbb:


See API documentation.

Migrating to shadow-cljs

See this gist on how to convert an nbb script or project to shadow-cljs.



  • babashka >= 0.4.0
  • Clojure CLI >=
  • Node.js 16.5.0 (lower version may work, but this is the one I used to build)

To build:

  • Clone and cd into this repo
  • bb release

Run bb tasks for more project-related tasks.

Download Details:
Author: borkdude
Download Link: Download The Source Code
Official Website: 
License: EPL-1.0

#node #javascript

Sid  Schuppe

Sid Schuppe


How To Blend Data in Google Data Studio For Better Data Analysis

Using data to inform decisions is essential to product management, or anything really. And thankfully, we aren’t short of it. Any online application generates an abundance of data and it’s up to us to collect it and then make sense of it.

Google Data Studio helps us understand the meaning behind data, enabling us to build beautiful visualizations and dashboards that transform data into stories. If it wasn’t already, data literacy is as much a fundamental skill as learning to read or write. Or it certainly will be.

Nothing is more powerful than data democracy, where anyone in your organization can regularly make decisions informed with data. As part of enabling this, we need to be able to visualize data in a way that brings it to life and makes it more accessible. I’ve recently been learning how to do this and wanted to share some of the cool ways you can do this in Google Data Studio.

#google-data-studio #blending-data #dashboard #data-visualization #creating-visualizations #how-to-visualize-data #data-analysis #data-visualisation

sophia tondon

sophia tondon


Top 10 VueJS Development Companies To Know In 2021-22

Vue.js is one of the most used and popular frontend development, or you can say client-side development framework. It is mainly used to develop single-page applications for both web and mobile. Famous companies like GitLab, NASA, Monito, Adobe, Accenture are currently using VueJS.

Do You Know?

Around 3079 companies reportedly use Vue.js in their tech stacks.
At GitHub, VueJS got 180.9K GitHub stars, including 28.5K GitHub forks.
Observing the increasing usage of VueJS and its robust features, various industry verticals are preferring to develop the website and mobile app Frontend using VueJS, and due to this reason, businesses are focusing on hiring VueJS developers from the top Vue.js development companies.

But the major concern of the enterprises is how to find the top companies to avail leading VueJS development service? Let’s move further and know what can help you find the best VueJS companies.

Read More -

#hire vue js developer #hire vue.js developers #hire vue.js developer, #hire vue.js developers, #vue js development company #vue.js development company