From the course: Data Science Foundations: Fundamentals
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Languages for data science
From the course: Data Science Foundations: Fundamentals
Languages for data science
- [Instructor] I love the saxophone. I play it very badly, but I love to listen to it. And one of the curious things about the saxophone is that if you want to play gigs professionally, you can't play just the saxophone. At the very least, you have to play both the alto and the tenor saxophone, as well as the flute and the clarinet. And for other gigs, you may need to be able to play oboe, English horn, bassoon, bass clarinet, and even recorder and crumhorn, like one of my teachers. You have to be a musical polyglot. I mention this because one of the most common questions in data science is whether you should work in Python or in R, two very common languages for working with data. The reason this question comes up is because programming languages give you immense control over your work in data science. You may find that your questions go beyond the capabilities of data analysis applications and so the ability to create…
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