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PythonBest Overall

  • Why: Easy to learn, massive libraries (Pandas, NumPy, Scikit-learn, TensorFlow, Matplotlib)
  • Use: Data analysis, machine learning, visualization
    RBest for Statistics
  • Why: Great for statistical analysis and plots
  • Use: Academic research, data visualization
  • SQLBest for Data Access
  • Why: Query and manipulate databases
  • Use: Data extraction, joining tables

Start with Python — it’s the most versatile and widely used in data science.

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