Wednesday, November 16, 2022

R vs Python - Which One is Dominant for Machine Learning and Data Science?

November 16, 2022

R vs Python- Which One is Dominant for Machine Learning and Data Science?

Machine Learning and Data Science are in high demand. Both these domains are pretty hard and involve extensive usage of mathematics, statistics, programming, and domain knowledge. While all these skills can be acquired with practice, you should know a programming language to be a data scientist or a Machine Learning engineer.  

There is a lack of skilled professionals in this area, and if you are someone who is looking to jump into the domain, you need the proper tools and technologies.

Two widely used programming languages in the Data Science and Machine Learning domain are Python and R. If you are looking to upskill and break into these areas, you need to learn any of these languages.

Beginners are often confused about what to choose, so in this article, we will learn everything about both languages, and at the end, we will have a comparison based on real-world usage of the languages.

Let’s start off with Python.


Who hasn't heard of Python and its power in the Data Science and Machine Learning domain? It is an open-source and high-level programming language. The main aim of Python's development was to have a language that was easy to learn and provide excellent code readability. Both these aims have been taken care of very well.

Today Python has changed a lot since its initial release. It has a large community, and even companies like Google and Facebook use Python in their tech stack.

Python found its shot to fame with the extensive demand for Machine Learning and Data Science among companies and developers. Since it has become popular, it has held the top spot in Data Science languages, but it constantly competes with R, which is equally remarkable.

Having known about the background of Python, let’s have a look at the rival R.


R is a mathematical language developed with the sole aim of making mathematical and statistical computing easier. Being an interpreted language, R is slower and more prone to errors as there is no compilation and no pre checks that happen.

R is the language for people moving to Data Science and Machine Learning from mathematical and statistical backgrounds. Unlike Python, which can be written and run anywhere, you might need to install an IDE to use R to its fullest. It is open-source, and you can easily integrate it with other languages. RStudio is the favorite IDE among R developers, so you may give it a try.


After knowing a brief history of these languages, it is time that we discuss the intricacies of these languages, and find out which one is dominant for Machine Learning and Data Science

Which is Better For Machine Learning & Data Science?


For people coming from a programming background with significant knowledge of object-oriented programming and programming in general, Python is the language to go.

But, if you are from a maths/stats background and you are starting to learn Data Science and Machine Learning, R is the language you should pick up first.

You will feel comfortable with the syntax, and as your needs change, you can pick up newer languages too. I had a good command over compiled languages like C and Java, which helped me transfer my learnings and understand the Python language better.

Community Support

As a data analyst who is just starting out, for me, community support was a significant factor, and that is where I chose Python. With an established community and tons of solutions on websites like Stack Overflow, learning and implementing Python can be pretty straightforward.

If you like to dig deeper into documentation and you are just learning Data Science and Machine Learning casually, you might choose R.

Python has an active community on programming platforms, and if you ask something, you’ll surely get answers pretty soon as you post. With the wide applications of the language, you’ll often get different solutions for your problems, so that you can implement solutions better.


By learning Python, I have opened a lot of doors for myself. I can pick up any domain in software development or Data Science, and I can easily accomplish it with my Python skills. 

Python has enabled me to develop web applications, backend services, CI/CD processes, and even data pipelines for large enterprise-scale data warehouses. It is also a reason why businesses look to hire python programmers as they give the same level of output in a cost effective way

While Python allows you to be a generalist and pick up new skills as and when required, R will enable you to be a specialist.

If you are determined to make big in Data Science and Machine Learning, then you should choose R as when the data becomes too much to handle, R has speed benefits and better libraries.

Third-Party Libraries

When it comes to Data Science and Machine Learning, there is a lot to code, but you can save time by using third-party libraries.

Third-party libraries are open-source packages that can be installed and used instantly to support your code. Such libraries help you to stop reinventing the wheel and provide you with functionalities that are ready-to-use and widely tested.

Both Python and R have an awesome community and excellent third-party libraries. While Python is more popular, it has significant options to choose from.

You can easily get multiple libraries that perform the same tasks, and it is up to you to choose the best.

Python’s libraries are managed by pip, and installing them is pretty easy. If you are looking to get started with development quickly, pip and Python will help you integrate all major third-party libraries.

With Python, you get instant support on libraries, and newer versions are released regularly that contain feature updates.

On the other hand, R’s third-party libraries are not as par to Python’s. R offers maximum in-built functionalities, and if you need to use third-party libraries, you can get them too but it's different from Python.

Today, R’s community has converted all major Data Science and Machine Learning libraries available in Python to R, but still, there is a long way to go.



In the end, both these languages are just the tools to create incredible Machine Learning models or help businesses to make better decisions. It is your personal choice on which you learn first, but in the end, it's a tech career, and in the real world, you will often come across situations where you might have to pick up another language and master it to get the work done.

Both Python and R are just replacements for one another, and if you have your Data Science concepts clear, you can implement them in any language.

While you learn Data Science, there will be some areas where Python will excel, and there will be some areas where R excels.

For me, both languages look pretty similar in functionality, and it all boils down to a personal preference. If you love to be a generalist, you should learn Python as it opens lots of doors for you. On the other hand, if you want to master everything in Data Science, and Machine Learning, and dominate at work, then R is your friend. 

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Shopify vs. Magento: Which One is better for Ecommerce Platform

Shopify vs. Magento: Which One is better for Ecommerce Platform

November 16, 2022

Shopify vs. Magento: Which One is better for Ecommerce Platform

Magento or Shopify, which one to choose for the new online store? You are not alone who is struggling with this question. These days, it is difficult to select the right platform to kick off your new business idea, with great eCommerce and website builder options available. 

Both Shopify and Magento are best for mid to large-size businesses. Shopify is an easy-to-use platform for building online stores, while Magento, an open-source system, is free to install on your devices.

An argument between the two platforms is expected as both are leading e-commerce platforms. You might be considering your option if you are thinking of creating an online store or want to migrate the current one to another platform. We will help you to simplify your problem through this article that covers a detailed comparison between these two platforms.

But first, let us identify what Shopify and Magento are and what makes them different from each other. So let’s get started!

What is Shopify?

Introduced in 2006 by Tobias Lütke and Scott Lake, Shopify is a popular online e-commerce platform that small businesses can use to build an online store to sell products on websites or through social media. The company also sells point of sales (POS) software that small businesses can use in brick-and-mortar stores.

What Can I Sell on Shopify?

    Products that you ship yourself.

    Goods and services which are sold in a retail store.

    Services sold and managed by online booking.

    Dropship items that ship to customers directly from your vendors.

    Services and products sold in-person by mobile locations.

    Rental sports equipment, cameras, formal wear, etc.


What is Magento?

Introduced in 2008 by Varien, Magento is an e-commerce platform built on open-source technology that provides online merchants with flexible shopping cart systems and controls the look, content, and functionality of the online store.

It is written in PHP over ZEND framework. To set up and maintain a Magento e-commerce store, you need to hire a dedicated PHP developer to help you through the development process.

Adobe purchased Magento Commerce in 2018 and integrated the software into the Adobe Experience Cloud. Under the new setup, Adobe is offering two versions of Magento services:

Magento Open Source

It is a free, open-source platform with limited features. It is great on the budget but requires some technical skills to run.

Adobe Commerce

It is a fully-featured product that includes PCI compliance, advanced marketing capabilities, technical support, and more. As Magento offers several products now everything is rolled into one product known as Adobe Commerce.

Adobe commerce doesn’t provide details on any pricing plans. You have to provide your contact details and wait for sales representatives to reach out and offer you a customized quote.

Difference Between Shopify and Magento





A cloud-based eCommerce platform that allows businesses to create an online store.

An open-source eCommerce platform that allows businesses to build and manage online stores easily.  

Release Date

June 2004

31 March 2008

Invented by

Tobias Lütke & Scott Lake

Roy Rubin







Used Programming Language





(As of October 2022)

Shopify has over 4 million eCommerce sites. 

Magento 1 has over 167,000 active user sites, while Magento 2 has 100,000 active sites.

Apps using the technology

Netflix, Tesla, Red Bull, Kylie Cosmetics, and more.

Ford, Landrover, Nestlé Nespresso, Olympus, and more.



    Shopify Payments: Shopify has its payment processor included with its platform; if you use Shopify Payments, there are no additional transaction fees.


    Abandoned checkout recovery: Automatically email users with a link to their abandoned card, encouraging them to complete their purchase.


    Mobile App: Shopify’s customizable mobile app lets you manage your products, orders, staff, and customers while you’re on the go.


    Blogging platform: Not only you will have a store website, but also a blog to publish articles and encourage reviews from customers.


    Marketing: The platform has advanced marketing capabilities like loyalty programs, SEO, cards, loyalty programs, discounts, social media integration, and more.


    Shopify App Store: The Shopify App Store has more than 7000 apps that you can download to extend the store’s functionality.


    Customer Support: Shopify offers its users 24/7 support, and access to its help center, e-commerce university, and discussion forums.


    Payment Processing: It works with common payment gateways like Braintree and PayPal and has integrations with more than 300 international gateways.


    Instant checkout: In addition to your general shopping capabilities, Magento offers an instant checkout that allows users to quickly and easily checkout on one page.


    Site management: Magento has advanced site-management abilities that allow you to control multiple websites & stores from one admin and create previews, and schedule content updates.


    International commerce: Along with working with international payment gateways, Magento allows you to manage multiple country sites from the same store or environment. You can also support tax rates, multiple currencies, and languages.


    Reporting: Magento includes 100 predefined reports, 9 reporting dashboards, and the ability to create and edit your reports.


    Customer development: Magento gives various ways to engage and support your customers like login checkout, Coupons, email marketing campaigns, product wishlists, promotions, and gift-wrapping options.


    Add-ons: The platform marketplace offers more than 4200 different add-ons and extensions that you can download to improve the store’s functionality.


    Lots of beautiful responsive store themes to select from.

    Great app store to extend the website’s functionality.

    A comprehensive eCommerce builder

    Many checkout and payment options.

    A large community of dedicated fans.

    Good customer support.

    Easy to use.

    Flexible platform with multiple customization options.

    Excellent community with massive support for users.

    Tons of themes to choose from.

    Open source and free to use.

    Contact support is available.



    Some themes have a price attached to them.

    Integrating apps into your store complicates it more.

    Charges a fee for every transaction (if you don't use Shopify payments)

    A bit of a learning curve

    Requires time to set up

     Quite difficult for beginners.

    Higher costs are associated with setting up your score.


Shopify comes with stable and reliable performance. As it has a hosted solution, the company guarantees for Shopify website’s speed.


In Magento, the website’s speed depends on the hosting service you selected.


Magento Community Edition (CE) 2.4.5

Shopify 2.18




All your hosting costs are included in the subscription (monthly or yearly), no need to pay extra.


Magento is free to install, but you need to pay for your domain, web hosting, security, and extension.


Number of Apps and Add-ons



Final Thoughts

Going through all these modes of comparison, we can say Magento and Shopify both are powerful platforms with their pros and cons.

Since Shopify is a hosted and managed service, it provides greater ease of use, and in Magento, everything you have to do by yourself (tech-savvy people can do it alone) from hosting purchase to software setup and installation.

Magento's websites are more functional than Shopify websites as you design everything from scratch,  you can give the desired look and feel to your website.

At last, what we conclude from the above comparison is:

Shopify is best for - 

    Small stores and start-ups with few products.

    If you want easy to operate eCommerce platform with all the required features.

    Drop shipping and syncing with multiple online stores channels


Magento is best for -

    Large stores with many orders and million-dollar earnings.

    Businesses with a dedicated web developers team to support.

    Enterprises that want to design and customize their website from scratch.

    Selling various products in different countries and languages.

We hope this article helped you to get out of the confusion of “Magento vs Shopify – which one is best for an eCommerce platform?” Start your online store by choosing the best eCommerce platform according to your business requirements.

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