Top 10 Most-Hated Programming Languages by Data Scientists

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Published on October 3rd, 2022

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Table of Contents

Introduction

The world has evolved at an astonishing pace, and app developers have a significant part of the credit for this progress. In case you haven’t noticed, app development has been all the rage lately.

Everyone is trying to break into the app development scene as it offers some of the highest-paying career paths, like web development, data science, artificial intelligence, and more.

But before you jump into your career and create your first app, you must first choose a programming language. And boy, there are many programming languages, over 700, to choose from.

That seems like an insanely high number, right?

There’s no denying that programming is super fun and exciting. It is practically impossible today to imagine leading a life without programming. Every sector we can think of relies on programming in one way or another. As developers, we learn and work with several programming languages throughout our lives. But it’s not like we have to learn more languages.

And programmers play a significant role in which language will be widely adopted and which will not.

To Data scientists, the programming language is what water is to human life. It is the most essential tool in every aspect of engineering operations. However, among all the speech collections, data scientists like to play favorites! The internet is full of content arguing about which programming language is better than the other.

This blog will discuss the 10 most hated programming languages by Data Scientists.

Here is a list of the top 10 programming languages data scientists hate the most.

1. Visual Basic for Applications (VBA)

Microsoft VBA holds first place in the ranking of the most feared Programming Languages. It is integrated into Office applications such as Word and Excel. With legitimate training, anyone can master VBA, a language primarily used for programming and overseeing Microsoft applications such as Excel. It is integrated into most Microsoft Office applications to automate repetitive tasks such as cleaning up spreadsheets, performing spring updates, and organizing records; from now on, you can’t exclude it because you don’t like it. However, after the birth of Python, people gradually stopped caring about VBA, and according to the common opinion, it is not cool enough.

2. Delphi

Delphi is a high-level language supporting object-oriented design. It is rapid development for developing applications from database solutions to mobile applications and is used on Windows and Linux. The main reason so few people programs in Delphi is the cost. Buying a new IDE from Embarcadero once or twice a year is too expensive. Their prices are absurd compared to other languages and IDEs. People just don’t want to pay for Delphi.

3. Objective-C

Experts say that Objective-C looks complex because of the syntax [and] and all the words. In addition, Objective-C is a language that is easy to learn in a short time. It is used for developing OS X and iOS operating systems and applications and provides language support for object graph management and object literal. Programmers often dislike it for its lack of method visibility methods, class namespaces, and a proper import system. They often complain that Objective-C is mostly just plain old C.

Our Learners Also Read: Python Vs C#: Comparison, Benefits, Differences, and Use Cases

4. Ruby

People don’t like Ruby because the syntax is too loose, so you might end up typing “foo bar 1, 2, 3” when you really meant “foo(bar(1,2),3)”. There are some bizarre names for built-in functions. Blocks in Ruby are confusing, and there are several ways to pass them.

5. Coffeescript

Sometimes CoffeeScript is almost unreadable. It optimizes the lousy stuff like aesthetics and hit count vs. readability, fewer errors, and maintainability. CoffeeScript projects often end up with a *.js extension in the name, and how often people who want nothing to do with CoffeeScript will have to deal with that for some reason.

6. Perl

Perl is nothing short of a complex and challenging language to learn. Truth be told, you can learn it surprisingly quickly. Software engineers hate Perl because it’s old and non-standard compared to python. This is very obvious because no young or generally experienced engineer would work on codes composed of Perl. It saw thready days, but competing dialects like Ruby and Python made it less critical. You can master Perl mainly for prototyping, large-scale projects, text manipulation, system administration, web development, and network programming.

7. Assembly

High-level languages are converted into machine language via symbolic instruction language. Yes, Assembly is a crucial link between software and hardware, but it does not automatically imply that it is an easy language. Assembly is difficult to learn because it necessitates a better comprehension of the system architecture at its most fundamental level, according to those who are experienced with it. And while that may be true, it doesn’t make it any less important. It is frequently used to directly manipulate hardware components to address serious performance problems. You must learn Assembly if you are interested in this kind of programming.

8. Java

Java is losing popularity due to the MEAN stack’s advent and developers’ ability to use one language (JavaScript) for everything. The fact that you can write database queries (Mongo), UI (React), and server-side logic (NodeJs platform) all using one language makes it very, very difficult to justify using something like Java for new initiatives in today’s world. However, Java is not going away so quickly. The programming language is robust and tested. It’s also being used left and right in these big companies.

9. PHP

Even developers who have never worked with PHP have heard of its sloppy syntax, unpredictability, and inconsistent function naming. While all other languages have many limitations when it comes to coding, PHP lacks them. And this leads to poor code quality. PHP is precisely what made it a nightmare for many programmers. They were intentionally designed to be global languages, but it took time for them to find their place in online development, largely due to web-oriented frameworks like Ruby on Rails (Ruby), Django (Python), or Spring (Java).

PHP’s development, in contrast, was far less organized. Initial plans merely called for a collection of web tools for personal use, but as new features and functionalities became necessary, they were gradually added. These and some other circumstances led to the following:

Inconsistency: Few languages are as inconsistent as PHP. Function names are written in different conventions, and random order of parameters that have no rule – these are just some examples of minor problems that accumulate and force the programmer to constantly refer to the documentation to do the simplest tasks.

Various performance and security issues: Over time, developers have blamed PHP’s sloppy syntax for making it too easy to write code vulnerable to common attacks like SQL injection.

10. C Programming Language

Did you know that C is the oldest programming language on the planet? The archetype for C++ was created by American computer scientist Dennis Ritchie in 1972 to create a broad cluster of computer systems and hardware. Programming dialects created after C, like PHP and Java, take solid references from C. Be that as it may, regardless of its importance, many software engineers hate it because it needs many cool features. This is why an aspiring developer picks up C++ rather than C. C developers don’t like it because it has no module system, automatic memory allocation, module system and lambdas, garbage collection, and null objects or classes.

Conclusion

No language can be considered perfect. One can learn any language. However, depending on your job or company requirements, you may need to know more than one language. But before starting a career, one should spend some time on which programming language to learn first.

In this blog, we have seen the 10 most hated programming languages by Data Scientists.