Vuex Tutorial for Beginners

Vuex is the official state management library for Vue applications.

In this tutorial, we make the assumption that you don’t have and previous experience working with Vuex.

Let’s get started with this tutorial—so what’s Vuex?

Vuex is a a Vue implementation of the Flux state management pattern. It’s a library for working with data in your Vue applications.

Vuex is the official state management library for Vue.js

Vuex enables developers to make complex data management easier and more efficient by using a global data store that can be accessed from all components of the Vue application for getting or setting data.

Vuex allows yo to efficiently share data between the application components.

Vue Components can use different ways to communicate data between each other, such as:

  • props: Props are used to pass state from a parent component to its children,
  • events: Events are used to change the state of a component from its children.

Props and events can be enough for simple scenarios but once the data requirements for your application becomes complex, you’ll need to implement other advanced strategies or patterns.

Among these patterns is the Flux pattern which aims to centralize the state across an application. In a Vue application, you can implement this pattern using Vuex.

Another popular implementation of the Flux pattern is Redux which more popular among React developers. But Redux is framework-agnostic which means you can also use it with Vue.

With that said, Vuex is the better option in Vue because it offers a better integration since it’s the official library for state management in Vue.


In order to compete this tutorial, you need to have a few requirements such as:

  • A development environment ready with Node.js 8.9+ and NPM installed,
  • A basic knowledge of modern JavaScript,
  • A working experience of Vue.js.

That’s all what you need. You’ll install the other requirements throughout this tutorial.

Installing the Vue.js CLI v3

In this tutorial, we’ll be using the latest version of Vue.js CLI to generate a new Vue project so first let’s start by installing the CLI.

Head back to your terminal and run the following command:

$ npm install @vue/cli -g 

Since your are installing the CLI globally on you system, make sure you have the required permissions by configuring your npm configuration or simply use sudo before you command.

Creating a New Vue.js Project

After installing the Vue CLI, let’s use it to generate a new project by running the following command in your terminal:

$ vue create vuex-demo

This will generate a vuex-demo project in your current directory.

The CLI will be asking for a preset that will be used for your project. You can also manually choose the features needed for your project from a set of official plugins like Babel, TypeScript, PWA, Vue Router and Vuex.

So go ahead and manually select Babel, Vue Router and Vuex for your project.

The CLI will also ask you for some other options for configuring the router such as router history and dedicated config files. You can also choose if you want to save the preset or not.

To make sure everything works as expected, navigate inside your project’s folder:

$ cd vuex-demo

Next run the development server using:

$ npm run serve

You should be able to go to the localhost;8080 address to see you application running:

Vuex Tutorial for Beginners

That’s it, you are now ready to start learning Vuex by implementing a simple application that manages its state using a central store.

Creating the Components

Now that we have created our project, let’s create the components of our application.

Under the src/components folder, create two ContactList.vue and ContactDetail files:

$ cd src/components
$ touch ContactList.vue
$ touch ContactDetail.vue

Next open the src/App.vue file and add a link to ContactList.vue component:

<div id="app">
<router-link to="/contacts" exact>Contact List</router-link>

Next open the src/router.js file and add a new route to the ContactList.vue component:

import ContactList from './components/ContactList.vue'
import ContactDetail from './components/ContactDetail.vue'


export default new Router({
  mode: 'history',
  base: process.env.BASE_URL,
  linkClass: "nav-link",
  linkActiveClass: "active",
  routes: [
      path: '/contacts',
      name: 'list',
      component: ContactList    },
      path: '/contacts/:id',
      name: 'detail',
      component: ContactDetail

For now, add the following template inside the src/components/ContactList.vue file:

  <div class="contact-list">
        Contact List

Also inside the src/components/ContactDetail.vue file, add the following template:

  <div class="contact-detail">
        Contact Details

That’s all for now about components.

The Vuex Basics

Before continue building our Vue application, let’s first understand the Vuex basics.

What’s a Vuex Store

A Vuex store is a central object for storing data in your Vue application. It also provides different methods for accessing and mutating global state.

This is an example of a basic store:

import Vue from 'vue'
import Vuex from 'vuex'


export default new Vuex.Store({})

We use the Vuex.Store method to create a store. It takes different properties, such as:

  • state; this object contains the actual state of the application i.e any variables and array etc.
  • mutations: this object contains the methods that will be used to mutate the state,
  • actions: this object contains methods that call the mutation methods.


Mutations are functions that enable you to mutate and upsate the state in a Vuex store. These function can not be called directly but instead they need to be committed using the .commit('mutation') of the Vuex store.

Mutations are synchronous functions.


Actions are functions that can be used to commit the mutations.

Actions can do asynchronous operations.


In this first part of the Vuex tutorial, we’ve installed the Vue CLI and used it to create a Vue demo that will be used to demonstrate the different concepts of Vuex.

We’ve also seen basic concepts like the Vuex store, state, mutations and actions.

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Vuex Tutorial for Beginners
Jeromy  Lowe

Jeromy Lowe


Data Visualization in R with ggplot2: A Beginner Tutorial

A famous general is thought to have said, “A good sketch is better than a long speech.” That advice may have come from the battlefield, but it’s applicable in lots of other areas — including data science. “Sketching” out our data by visualizing it using ggplot2 in R is more impactful than simply describing the trends we find.

This is why we visualize data. We visualize data because it’s easier to learn from something that we can see rather than read. And thankfully for data analysts and data scientists who use R, there’s a tidyverse package called ggplot2 that makes data visualization a snap!

In this blog post, we’ll learn how to take some data and produce a visualization using R. To work through it, it’s best if you already have an understanding of R programming syntax, but you don’t need to be an expert or have any prior experience working with ggplot2

#data science tutorials #beginner #ggplot2 #r #r tutorial #r tutorials #rstats #tutorial #tutorials

Willie  Beier

Willie Beier


Tutorial: Getting Started with R and RStudio

In this tutorial we’ll learn how to begin programming with R using RStudio. We’ll install R, and RStudio RStudio, an extremely popular development environment for R. We’ll learn the key RStudio features in order to start programming in R on our own.

If you already know how to use RStudio and want to learn some tips, tricks, and shortcuts, check out this Dataquest blog post.

Table of Contents

#data science tutorials #beginner #r tutorial #r tutorials #rstats #tutorial #tutorials

Tutorial: Loading and Cleaning Data with R and the tidyverse

1. Characteristics of Clean Data and Messy Data

What exactly is clean data? Clean data is accurate, complete, and in a format that is ready to analyze. Characteristics of clean data include data that are:

  • Free of duplicate rows/values
  • Error-free (e.g. free of misspellings)
  • Relevant (e.g. free of special characters)
  • The appropriate data type for analysis
  • Free of outliers (or only contain outliers have been identified/understood), and
  • Follows a “tidy data” structure

Common symptoms of messy data include data that contain:

  • Special characters (e.g. commas in numeric values)
  • Numeric values stored as text/character data types
  • Duplicate rows
  • Misspellings
  • Inaccuracies
  • White space
  • Missing data
  • Zeros instead of null values

2. Motivation

In this blog post, we will work with five property-sales datasets that are publicly available on the New York City Department of Finance Rolling Sales Data website. We encourage you to download the datasets and follow along! Each file contains one year of real estate sales data for one of New York City’s five boroughs. We will work with the following Microsoft Excel files:

  • rollingsales_bronx.xls
  • rollingsales_brooklyn.xls
  • rollingsales_manhattan.xls
  • rollingsales_queens.xls
  • rollingsales_statenisland.xls

As we work through this blog post, imagine that you are helping a friend launch their home-inspection business in New York City. You offer to help them by analyzing the data to better understand the real-estate market. But you realize that before you can analyze the data in R, you will need to diagnose and clean it first. And before you can diagnose the data, you will need to load it into R!

3. Load Data into R with readxl

Benefits of using tidyverse tools are often evident in the data-loading process. In many cases, the tidyverse package readxl will clean some data for you as Microsoft Excel data is loaded into R. If you are working with CSV data, the tidyverse readr package function read_csv() is the function to use (we’ll cover that later).

Let’s look at an example. Here’s how the Excel file for the Brooklyn borough looks:

The Brooklyn Excel file

Now let’s load the Brooklyn dataset into R from an Excel file. We’ll use the readxlpackage. We specify the function argument skip = 4 because the row that we want to use as the header (i.e. column names) is actually row 5. We can ignore the first four rows entirely and load the data into R beginning at row 5. Here’s the code:

library(readxl) # Load Excel files
brooklyn <- read_excel("rollingsales_brooklyn.xls", skip = 4)

Note we saved this dataset with the variable name brooklyn for future use.

4. View the Data with tidyr::glimpse()

The tidyverse offers a user-friendly way to view this data with the glimpse() function that is part of the tibble package. To use this package, we will need to load it for use in our current session. But rather than loading this package alone, we can load many of the tidyverse packages at one time. If you do not have the tidyverse collection of packages, install it on your machine using the following command in your R or R Studio session:


Once the package is installed, load it to memory:


Now that tidyverse is loaded into memory, take a “glimpse” of the Brooklyn dataset:

## Observations: 20,185
## Variables: 21
## $ BOROUGH <chr> "3", "3", "3", "3", "3", "3", "…
## $ `TAX CLASS AT PRESENT` <chr> "1", "1", "1", "1", "1", "1", "…
## $ BLOCK <dbl> 6359, 6360, 6364, 6367, 6371, 6…
## $ LOT <dbl> 70, 48, 74, 24, 19, 32, 65, 20,…
## $ `EASE-MENT` <lgl> NA, NA, NA, NA, NA, NA, NA, NA,…
## $ `BUILDING CLASS AT PRESENT` <chr> "S1", "A5", "A5", "A9", "A9", "…
## $ ADDRESS <chr> "8684 15TH AVENUE", "14 BAY 10T…
## $ `APARTMENT NUMBER` <chr> NA, NA, NA, NA, NA, NA, NA, NA,…
## $ `ZIP CODE` <dbl> 11228, 11228, 11214, 11214, 112…
## $ `RESIDENTIAL UNITS` <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1…
## $ `COMMERCIAL UNITS` <dbl> 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ `TOTAL UNITS` <dbl> 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1…
## $ `LAND SQUARE FEET` <dbl> 1933, 2513, 2492, 1571, 2320, 3…
## $ `GROSS SQUARE FEET` <dbl> 4080, 1428, 972, 1456, 1566, 22…
## $ `YEAR BUILT` <dbl> 1930, 1930, 1950, 1935, 1930, 1…
## $ `TAX CLASS AT TIME OF SALE` <chr> "1", "1", "1", "1", "1", "1", "…
## $ `BUILDING CLASS AT TIME OF SALE` <chr> "S1", "A5", "A5", "A9", "A9", "…
## $ `SALE PRICE` <dbl> 1300000, 849000, 0, 830000, 0, …
## $ `SALE DATE` <dttm> 2020-04-28, 2020-03-18, 2019-0…

The glimpse() function provides a user-friendly way to view the column names and data types for all columns, or variables, in the data frame. With this function, we are also able to view the first few observations in the data frame. This data frame has 20,185 observations, or property sales records. And there are 21 variables, or columns.

#data science tutorials #beginner #r #r tutorial #r tutorials #rstats #tidyverse #tutorial #tutorials

Marcus  Flatley

Marcus Flatley


Getting Started with R Markdown — Guide and Cheatsheet

In this blog post, we’ll look at how to use R Markdown. By the end, you’ll have the skills you need to produce a document or presentation using R Mardown, from scratch!

We’ll show you how to convert the default R Markdown document into a useful reference guide of your own. We encourage you to follow along by building out your own R Markdown guide, but if you prefer to just read along, that works, too!

R Markdown is an open-source tool for producing reproducible reports in R. It enables you to keep all of your code, results, plots, and writing in one place. R Markdown is particularly useful when you are producing a document for an audience that is interested in the results from your analysis, but not your code.

R Markdown is powerful because it can be used for data analysis and data science, collaborating with others, and communicating results to decision makers. With R Markdown, you have the option to export your work to numerous formats including PDF, Microsoft Word, a slideshow, or an HTML document for use in a website.

r markdown tips, tricks, and shortcuts

Turn your data analysis into pretty documents with R Markdown.

We’ll use the RStudio integrated development environment (IDE) to produce our R Markdown reference guide. If you’d like to learn more about RStudio, check out our list of 23 awesome RStudio tips and tricks!

Here at Dataquest, we love using R Markdown for coding in R and authoring content. In fact, we wrote this blog post in R Markdown! Also, learners on the Dataquest platform use R Markdown for completing their R projects.

We included fully-reproducible code examples in this blog post. When you’ve mastered the content in this post, check out our other blog post on R Markdown tips, tricks, and shortcuts.

Okay, let’s get started with building our very own R Markdown reference document!

R Markdown Guide and Cheatsheet: Quick Navigation

1. Install R Markdown

R Markdown is a free, open source tool that is installed like any other R package. Use the following command to install R Markdown:


Now that R Markdown is installed, open a new R Markdown file in RStudio by navigating to File > New File > R Markdown…. R Markdown files have the file extension “.Rmd”.

2. Default Output Format

When you open a new R Markdown file in RStudio, a pop-up window appears that prompts you to select output format to use for the document.

New Document

The default output format is HTML. With HTML, you can easily view it in a web browser.

We recommend selecting the default HTML setting for now — it can save you time! Why? Because compiling an HTML document is generally faster than generating a PDF or other format. When you near a finished product, you change the output to the format of your choosing and then make the final touches.

One final thing to note is that the title you give your document in the pop-up above is not the file name! Navigate to File > Save As.. to name, and save, the document.

#data science tutorials #beginner #r #r markdown #r tutorial #r tutorials #rstats #rstudio #tutorial #tutorials

I am Developer


Laravel 8 Tutorial for Beginners

Hello everyone! I just updated this tutorial for Laravel 8. In this tutorial, we’ll go through the basics of the Laravel framework by building a simple blogging system. Note that this tutorial is only for beginners who are interested in web development but don’t know where to start. Check it out if you are interested: Laravel Tutorial For Beginners

Laravel is a very powerful framework that follows the MVC structure. It is designed for web developers who need a simple, elegant yet powerful toolkit to build a fully-featured website.

Recommended:-Laravel Try Catch

#laravel 8 tutorial #laravel 8 tutorial crud #laravel 8 tutorial point #laravel 8 auth tutorial #laravel 8 project example #laravel 8 tutorial for beginners