R Ascends as Statistical Tools Consolidate

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May’s TIOBE Index has a clear headline move inside the top 10: R climbs to #8, matching its best-ever rank. TIOBE CEO Paul Jansen says it fits a broader pattern in statistical programming, where attention is gathering around fewer ecosystems rather than spreading across a long list of specialized tools.

The TIOBE Programming Community Index tracks programming language popularity using search engine activity.

Historical trends trace the popularity of programming languages over decades.

Python slips under 20%, and C stays firmly in second

Python remains #1 at 19.98%, and even with the drop, it still sits far ahead of every other language in the table. The lead is not in question, but the rating continues to drift downward month to month.

C holds #2 at 11.55%. It comes in below April’s higher mark, but it keeps its grip on second place and remains the clearest challenger by a wide margin.

Java noses ahead of C++ after Java 26

The main shuffle near the top is at #3 and #4. Java moves up to #3 at 7.94%, edging past C++ at 7.92%. Jansen ties Java’s uptick to the successful release of Java 26, which appears to have brought it a bit more attention.

Just behind them, C# stays #5 at 5.41%, and JavaScript remains #6 at 3.08%. The lineup stays familiar, but the Java and C++ gap is now extremely narrow, so this slot could trade back again with only a small change next month.

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R reaches #8 again, and the lower tier rearranges around it

Visual Basic holds #7 at 2.90%, while R takes #8 at 1.77%, the best position it has reached in the index. This is the part of the table where small movements tend to show up first, and May’s reshuffle comes directly from R’s climb.

R’s rise pushes the next two spots down a notch. SQL sits #9 at 1.57%, and Delphi/Object Pascal rounds out the top 10 at 1.44%. The ordering here can change quickly, but May’s standout is that R did not just hold in the top 10; it moved into a higher slot.

Statistical programming is narrowing to two main ecosystems

Jansen says statistical work is consolidating around two centers. Python continues to dominate industry use, including machine learning, AI, and production systems, while R remains the leading environment in academia and research-driven fields such as epidemiology and advanced statistical analysis.

He also points to long-established alternatives losing momentum. MATLAB is close to dropping out of the top 20, SAS is nearing a first-ever exit from the top 30, and SPSS recently fell out of the top 100. Looking ahead, Jansen expects Stan to debut in the index next month, reflecting growing interest in probabilistic programming and Bayesian statistics.

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