Why use R programming?

Why One Should Learn R Programming Language?

R programming language is specific, i.e. instead of doing a little everything, It does a few things very well. It’s not a general-purpose programming language like C, Java, PHP, etc. However, R is not limited to a particular industry or use case. It is widely used across various industries because data is essential for modern businesses. By analysing past data, data scientists and analysts can assess a company's performance and provide valuable insights to guide future decision-making for business leaders. R is used in many industries. Here are some of them listed.

• Fintech: R is utilised by financial technology companies for tasks such as credit risk modelling, fraud detection, mortgage and volatility modelling, client assessment, and loan stress test simulations.
   
• Research: R is widely adopted in academia for statistical computing and data analysis. Many universities, including Cornell and the University of California, teach R in courses that focus on these subjects.
   
• Retail: R is employed in retail and e-commerce for risk assessment, marketing strategies, machine learning for cross-selling and product recommendations, sales modelling, and targeted advertising. Companies like Amazon and Flipkart rely on R for data analytics.
   
• Government: The National Weather Service employs R to predict disasters, forecast weather, and create weather visualisation. The FDA uses R for drug evaluation, pre-clinical trials, and predicting reactions related to food products.
   
• Data journalism: R is a favoured language among data journalists, enabling them to extract insights from public data and generate visually appealing graphics to tell compelling stories.
   
• Social media: R is utilised in social media analytics for segmenting potential customers, targeted advertising, and analysing user data, which is crucial for the profitability of social media platforms.
   
• Healthcare: R plays a significant role in genetics, bioinformatics, drug discovery, and epidemiology. It is used in drug safety assessment during pre-clinical trials and in predicting the spread of diseases in epidemiology.
   
• Manufacturing: Companies leverage R to analyse customer feedback, improve product design based on consumer sentiment, and make production decisions considering factors like crop yield (as seen in John Deere's case).

Why Do We Use R Programming Language? 

There are various reasons why one should learn R programming language. Here are some: 

• R is free and open-source. That means you don't need to pay for licenses.
   
• It is platform-independent. This makes it cost-effective and versatile. You only need to make one program that can run on various platforms. 
   
• Currently, R has over 10,000 packages available. It is stored in CRAN repositories, and it is continuously updated.
   
• It's popular for statistics and preferred by programmers for statistical tools.
   
• It's suitable for machine learning, offering features and packages for tasks like regression and classification.
   
• R helps with data wrangling. R contains various packages which help transform messy data into structured formats.
   
• Last but importantly, It has continuously evolved with a supportive community.
   

However, there are some drawbacks to consider:

• R has a steep learning curve and is better suited for experienced programmers.
   
• It’s not super secure. It lacks basic security measures and can't be used for web-safe applications.
   
• Compared to other languages like Python or MATLAB, R may be slower.
   
• Memory management is also not the strong point of R language. It requires more memory as data is stored in physical memory. Although, cloud-based memory service may eliminate this drawback.
   
• R does not have consistent package quality. Documentation and package quality can vary due to the community-driven nature of R. Docs, and packages may be patchy or inconsistent as it doesn’t have official dedicated support.
   

Despite these drawbacks, R remains a powerful and widely used language for data analysis and statistical computing.

Frequently Asked Questions

Can I use R programming for tasks other than data analysis?

Absolutely, R can also be used for anything from web development and machine learning to creating interactive visualisations. Because of its adaptability, R may be used for various projects in various disciplines, even though R is mainly used for data analytics.

Can R programming be integrated with other languages or tools?

R programming integrates with Python, Java, and C++, allowing users to combine the strengths of different languages and access additional libraries. This integration expands the capabilities of R and enhances its functionality for various tasks.

Is R programming suitable for both research and production environments?

Yes, R programming is used extensively in both research and production environments. Researchers rely on R for statistical analysis and experimentation, while production environments benefit from its ability to handle data analysis pipelines, automate tasks, and generate reports.

Conclusion

In this article, we covered the question, Why use R programming?  We also looked at Why One Should Learn R Programming Language by knowing its use cases in different sectors. We also learn Why We Use R Programming Language by understanding the advantages and shortcomings of the language.

Recommended Readings:

• What is R Programming Language?
• How to Download R on your Computer?
• R vs C++

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