As of 2025, JavaScript and HTML/CSS are the most commonly used programming languages among software developers around the world, with more than 66 percent of respondents stating that they used JavaScript and just around 61.9 percent using HTML/CSS. Python, SQL, and Bash/Shell rounded out the top five most widely used programming languages around the world. Programming languages At a very basic level, programming languages serve as sets of instructions that direct computers on how to behave and carry out tasks. Thanks to the increased prevalence of, and reliance on, computers and electronic devices in today’s society, these languages play a crucial role in the everyday lives of people around the world. An increasing number of people are interested in furthering their understanding of these tools through courses and bootcamps, while current developers are constantly seeking new languages and resources to learn to add to their skills. Furthermore, programming knowledge is becoming an important skill to possess within various industries throughout the business world. Job seekers with skills in Python, R, and SQL will find their knowledge to be among the most highly desirable data science skills and likely assist in their search for employment.

Context

A common question for those new and familiar to computer science and software engineering is what is the most best and/or most popular programming language. It is very difficult to give a definitive answer, as there are a seemingly indefinite number of metrics that can define the 'best' or 'most popular' programming language.

One such metric that can be used to define a 'popular' programming language is the number of projects and files that are made using that programming language. As GitHub is the most popular public collaboration and file-sharing platform, analyzing the languages that are used for repositories, PRs, and issues on GitHub and be a good indicator for the popularity of a language.

Content

This dataset contains statistics about the programming languages used for repositories, PRs, and issues on GitHub. The data is from 2011 to 2021.

Source

This data was queried and aggregated from BigQuery's public github_repos and githubarchive datasets.

Limitations

Only data for public GitHub repositories, and their corresponding PRs/issues, have their data available publicly. Thus, this dataset is only based on public repositories, which may not be fully representative of all repositories on GitHub.

programming languages statistics: The tech market which is also booming along with digital marketing is pretty good for a better income source. The tech market has many other things including programming languages. Programming languages are the basis for the formation of various websites, games, software, mobile applications, etc... There are nearly 9,000 programming languages around the world with each language with its own feature. In this most popular programming language statistics, we will have a look at statistical information and general knowledge about worldwide available various programming languages. Programming Languages Statistics (Editor’s Choice) There are 8,945 programming languages as stated by most popular Programming languages statistics. As of 2022, JavaScript is one of the most popular programming languages as around 47.86% of recruiters are demanding JavaScript language skills. A basic python developer earns between $70,000 to $1,00,00 a year. As per the most popular programming languages statistics Python has ranked number 1 in the United States of America, India, Germany, France, and the United Kingdom

The most popular programming language used in the past 12 months by software developers worldwide is JavaScript as of 2024, according to ** percent of the software developers surveyed. This is followed by Python at ** percent of the respondents surveyed.

JavaScript and Java were some of the most tested programming languages on the DevSkiller platform as of 2024. SQL and Python ranked second and fourth, with ** percent and ** percent of respondents testing this language in 2024, respectively. Nevertheless, the tech skill developers wanted to learn the most in 2024 was related to artificial intelligence, machine learning, and deep learning. At the same time, the fastest growing IT skills among DevSkiller customers were C/C++ and data science, while cybersecurity ranked third. Software skills When it came to the most used programming language among developers worldwide, JavaScript took the top spot, chosen by 62 percent of surveyed respondents. Most software developers learn how to code between 11 and 17 years old, with some of them writing their first line of code by the age of 5. Moreover, seven out of 10 developers learned how to program by accessing online resources such as videos and blogs. Software skills pay In 2024, the average annual software developer’s salary in the U.S. amounted to nearly ** thousand U.S. dollars, while in Germany, it totaled above ** thousand U.S. dollars. The programming languages associated with the highest salaries worldwide in 2024 were Clojure and Erlang.

This dataset contains the following columns:

Month: The date (in year-month format) when the data was recorded. Python Worldwide(%): The percentage of global popularity for Python during that month. JavaScript Worldwide(%): The percentage of global popularity for JavaScript. Java Worldwide(%): The percentage of global popularity for Java. C# Worldwide(%): The percentage of global popularity for C#. PhP Worldwide(%): The percentage of global popularity for PhP. Flutter Worldwide(%): The percentage of global popularity for Flutter. React Worldwide(%): The percentage of global popularity for React. Swift Worldwide(%): The percentage of global popularity for Swift. TypeScript Worldwide(%): The percentage of global popularity for TypeScript. Matlab Worldwide(%): The percentage of global popularity for Matlab.

Each row represents data for a particular month, starting from January 2004, tracking the popularity trends of these programming languages worldwide.

About Dataset

This dataset was created during the Programming Language Ecosystem project from TU Wien using the code inside the repository https://github.com/ValentinFutterer/UsageOfProgramminglanguages2011-2023?tab=readme-ov-file.

The centerpiece of this repository is the usage_of_programming_languages_2011-2023.csv. This csv file shows the popularity of programming languages over the last 12 years in yearly increments. The repository also contains graphs created with the dataset. To get an accurate estimate on the popularity of programming languages, this dataset was created using 3 vastly different sources.

About Data collection methodology

The dataset was created using the github repository above. As input data, three public datasets where used.

github_metadata

Taken from https://www.kaggle.com/datasets/pelmers/github-repository-metadata-with-5-stars/ by Peter Elmers. It is licensed under CC BY 4.0 https://creativecommons.org/licenses/by/4.0/. It shows metadata information (no code) of all github repositories with more than 5 stars.

PYPL_survey_2004-2023

Taken from https://github.com/pypl/pypl.github.io/tree/master, put online by the user pcarbonn. It is licensed under CC BY 3.0 https://creativecommons.org/licenses/by/3.0/. It shows from 2004 to 2023 for each month the share of programming related google searches per language.

stack_overflow_developer_survey

Taken from https://insights.stackoverflow.com/survey. It is licensed under Open Data Commons Open Database License (ODbL) v1.0 https://opendatacommons.org/licenses/odbl/1-0/. It shows from 2011 to 2023 the results of the yearly stackoverflow developer survey.

All these datasets were downloaded on the 12.12.2023. The datasets are all in the github repository above

Description of the data

The dataset contains a column for the year and then many columns for the different languages, denoting their usage in percent. Additionally, vertical barcharts and piecharts for each year plus a line graph for each language over the whole timespan as png's are provided.

The languages that are going to be considered for the project can be seen here:

- Python

- C

- C++

- Java

- C#

- JavaScript

- PHP

- SQL

- Assembly

- Scratch

- Fortran

- Go

- Kotlin

- Delphi

- Swift

- Rust

- Ruby

- R

- COBOL

- F#

- Perl

- TypeScript

- Haskell

- Scala

License

This project is licensed under the Open Data Commons Open Database License (ODbL) v1.0 https://opendatacommons.org/licenses/odbl/1-0/ license.

TLDR: You are free to share, adapt, and create derivative works from this dataser as long as you attribute me, keep the database open (if you redistribute it), and continue to share-alike any adapted database under the ODbl.

Acknowledgments

Thanks go out to

- stackoverflow https://insights.stackoverflow.com/survey for providing the data from the yearly stackoverflow developer survey.

- the PYPL survey, https://github.com/pypl/pypl.github.io/tree/master for providing google search data.

- Peter Elmers, for crawling metadata on github repositories and providing the data https://www.kaggle.com/datasets/pelmers/github-repository-metadata-with-5-stars/.

The Dataset comes from Programming Languages Database

languages.csv

The full data dictionary is available from PLDB.com.

In the fourth quarter 2024, the most popular programming languages in published job offers in Poland were ***********, and Java.

This dataset titled "Programming Languages Search over Time" provides weekly search interest scores for three prominent programming languages - Python, Java, and C++ - over a period spanning from April 21, 2019, to April 23, 2024. The search interest scores represent the relative popularity of each programming language as determined by search engine queries.

This dataset can be used to analyze and visualize trends and patterns in the popularity of these programming languages over time, providing valuable insights into their usage and adoption in the software development community.

The dataset contains information on over 4000 programming languages. Which include facts about the language such as what year it was created, What is its rank, and other parameters that you will come to know once you explore the dataset.

Credits. https://github.com/breck7/pldb

According to the survey, Rust was the most desired language in 2022, with over ** percent of respondents that are not developing with it, but expressed interest in developing with it. Python ranked second, followed by TypeScript.

This dataset is a chronological ordering / timeline of Programming language . What one can do with this dataset ? -> Find relation between different programming language using Predecessors column. -> Most frequent chief developer / company etc.

This book is written for statisticians, data analysts, programmers, researchers, teachers, students, professionals, and general consumers on how to perform different types of statistical data analysis for research purposes using the R programming language. R is an open-source software and object-oriented programming language with a development environment (IDE) called RStudio for computing statistics and graphical displays through data manipulation, modelling, and calculation. R packages and supported libraries provides a wide range of functions for programming and analyzing of data. Unlike many of the existing statistical softwares, R has the added benefit of allowing the users to write more efficient codes by using command-line scripting and vectors. It has several built-in functions and libraries that are extensible and allows the users to define their own (customized) functions on how they expect the program to behave while handling the data, which can also be stored in the simple object system.For all intents and purposes, this book serves as both textbook and manual for R statistics particularly in academic research, data analytics, and computer programming targeted to help inform and guide the work of the R users or statisticians. It provides information about different types of statistical data analysis and methods, and the best scenarios for use of each case in R. It gives a hands-on step-by-step practical guide on how to identify and conduct the different parametric and non-parametric procedures. This includes a description of the different conditions or assumptions that are necessary for performing the various statistical methods or tests, and how to understand the results of the methods. The book also covers the different data formats and sources, and how to test for reliability and validity of the available datasets. Different research experiments, case scenarios and examples are explained in this book. It is the first book to provide a comprehensive description and step-by-step practical hands-on guide to carrying out the different types of statistical analysis in R particularly for research purposes with examples. Ranging from how to import and store datasets in R as Objects, how to code and call the methods or functions for manipulating the datasets or objects, factorization, and vectorization, to better reasoning, interpretation, and storage of the results for future use, and graphical visualizations and representations. Thus, congruence of Statistics and Computer programming for Research.

Content

The dataset contains "Hello world" programs for different programming languages. Each row in the main file describes the one program: language, file extension, and the program's text itself.

For example, the language Asciidots has the .arnoldc files extension and the Hello World program looks like: .-$"Hello World"

Acknowledgements

This dataset scrapping from the next sources: - https://github.com/leachim6/hello-world - https://helloworldcollection.github.io/

Inspiration

You can try to resolve the next tasks: - Generate features for some languages - Clustering languages by their code or some features

Poland Individuals: Writing Code in a Programming Language: 25-34 data was reported at 10.100 % in 2024. This records an increase from the previous number of 8.700 % for 2023. Poland Individuals: Writing Code in a Programming Language: 25-34 data is updated yearly, averaging 5.600 % from Dec 2015 (Median) to 2024, with 7 observations. The data reached an all-time high of 10.100 % in 2024 and a record low of 3.600 % in 2015. Poland Individuals: Writing Code in a Programming Language: 25-34 data remains active status in CEIC and is reported by Statistics Poland. The data is categorized under Global Database’s Poland – Table PL.G040: Individuals Carrying Out Software Related Activities: by Age.

JavaScript was the most frequently used coding language in Russia, used by around ********** of the surveyed software companies in 2024. Furthermore, over ******** of the companies reported to use Python and Java.

As shown in the chart, Python ranks first with a usage rate of 28.7%, demonstrating its continued advantage in the fields of data science and artificial intelligence. JavaScript follows closely at 19.3%, reflecting its widespread use in front-end and full-stack development. Traditional languages such as Java and C# still maintain a stable market share, while emerging languages like Go and Rust show significant growth potential. Overall, the popularity of programming languages is closely related to technological trends. The leading positions of Python and JavaScript indicate a shift in development focus towards data-driven and web-oriented directions. In the future, with the further development of cloud computing and artificial intelligence, the usage of emerging languages such as Go and Rust is expected to continue increasing.

This is a repository for codes and datasets for the open-access paper in Linguistik Indonesia, the flagship journal for the Linguistic Society of Indonesia (Masyarakat Linguistik Indonesia [MLI]) (cf. the link in the references below).

The global Programming Language Learning market is poised for substantial expansion, projected to reach an estimated market size of $5,500 million by 2025, with a robust Compound Annual Growth Rate (CAGR) of 15% anticipated through 2033. This significant growth is primarily fueled by the escalating demand for skilled professionals across various tech-centric industries. The continuous evolution of technology necessitates a constant upskilling and reskilling of the workforce, making programming language proficiency a critical asset. Sectors like software development, data science, artificial intelligence, and cybersecurity are experiencing an insatiable appetite for individuals adept in languages such as Python, JavaScript, and C. The proliferation of online learning platforms and the increasing adoption of remote work further democratize access to programming education, broadening the reach of this market. Furthermore, educational institutions are increasingly integrating coding into their curricula, fostering a generation of digitally literate individuals from an early age. The market is characterized by a dynamic interplay of driving forces and emerging trends. Key drivers include the digital transformation initiatives undertaken by businesses of all sizes, the burgeoning freelance economy, and the growing interest in personal projects and startups that require coding skills. Emerging trends highlight a shift towards specialized learning, with an increased focus on advanced programming concepts, machine learning, and cloud computing. The market is also witnessing a rise in personalized learning experiences, adaptive learning paths, and gamified educational content to enhance engagement and retention. However, challenges such as the rapidly evolving technological landscape requiring continuous curriculum updates, the perceived complexity of certain programming languages, and the need for robust assessment mechanisms to validate skill acquisition represent potential restraints. Despite these challenges, the overarching trajectory points towards continued innovation and expansion within the programming language learning ecosystem. This comprehensive report offers an in-depth analysis of the global programming language learning market, a dynamic sector experiencing exponential growth fueled by digital transformation and the increasing demand for skilled technology professionals. The study period spans from 2019 to 2033, with a base year of 2025 and a forecast period of 2025-2033. This report leverages extensive historical data from 2019-2024 to provide accurate and insightful market projections. The market is meticulously segmented by programming language type (C, Python, JavaScript, Others), application (Worker, Student), and key industry developments. Valued in the millions, this report aims to equip stakeholders with actionable intelligence to navigate this evolving landscape.