Python and R are among the most frequently mentioned skills in job postings for data science positions. But reports on which programming language is actually used most often on the job for these professionals are conflicting, according to a Thursday report from Cloud Academy.
The TIOBE Programming Community Index shows R as being on a downward trend this year in terms of search engine requests. However, a Kaggle survey of 16,000 data professionals found that while Python was the most popular programming language overall, statisticians and data scientists were more likely to report using R at work than other roles. Among data scientists, 87% reported using Python and 71% reported using R at work, that report found.
Cloud Academy analyzed data engineer job descriptions to see what technologies companies were seeking the most often. There was significantly less demand for data engineers proficient in R compared to those proficient in Python, it found. Nearly 66% of data engineer job postings mentioned Python, compared to just 18% of postings that mentioned R.
“Python is known to be an intuitive language that’s used across multiple domains in computer science,” the report stated. “It’s easy to work with, and the data science community has put the work in to create the plumbing it needs to solve complex computational problems. It could also be that more companies are moving data projects and products into production. R is not a general purpose programming language like Python.”
Python is currently among the fastest-growing programming languages in the world, largely due to the ease of learning involved, the explosion of data science and artificial intelligence (AI) in the enterprise, and the large developer community around it.
Other in-demand skills for data engineers include SQL, Spark, Hadoop, Java, Amazon Web Services (AWS), Scala, and Kafka.
The big takeaways for tech leaders:
- 66% of data engineer job postings mentioned Python, compared to just 18% of postings that mentioned R. — Cloud Academy, 2018
- In-demand skills for data engineers include SQL, Spark, Hadoop, Java, Amazon Web Services (AWS), Scala, and Kafka. — Cloud Academy, 2018