His argument against Python is that a person using it for data science needs to learn about extra Python packages, like NumPy, which brings Matlab-like data-analysis powers to Python.

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Python is easy to learn, it has vast and deep support, and most every data science library and machine learning framework out there has a Python interface.

Python’s popularity is skyrocketing, and for good reason. It’s versatile, beginner-friendly, and opens doors to exciting fields like data science, automation, and web development.

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Python has turned into a data science and machine learning mainstay, while Julia was built from the ground up to do the job.

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Harnham said that Python was now the top programming language used in data science, "with R falling firmly into second place." The remaining top-five data science technologies were SQL, AWS and Spark.