📊 Key Insights
Python's Rise: Python showed steady growth from 2010-2018, then accelerated dramatically after 2018 due to AI/ML boom, reaching 25%+ market share by 2025.
R's Stability: R maintained consistent popularity (3-5%) throughout the period, remaining strong in academic and statistical research domains.
SQL's Persistence: SQL showed steady growth and remained essential for data manipulation, reaching ~8% by 2025.
Java's Decline: Java's popularity in data science decreased from ~20% to ~7% as Python gained dominance in ML/AI applications.
JavaScript's Growth: JavaScript emerged as a data visualization tool, growing from ~2% to ~6% by 2025.
📚 Data Sources
Primary Sources: TIOBE Programming Community Index, Stack Overflow Developer Surveys (2010-2025), PYPL Index
Industry Reports: upGrad Data Science Trends, DataCamp Language Rankings, Towards Data Science analysis
Academic Sources: Stanford University AI studies, Nature Data Science reports, Medium technical analysis
Methodology: Data compiled from search engine trends, job postings, developer surveys, and GitHub activity. Percentages represent relative popularity in data science context, not absolute usage.
Note: Trend lines are based on aggregated data from multiple sources and represent general popularity patterns rather than precise measurements.