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In this chapter we will extend our use of Pandas from Chapter 2 and dive more deeply into Data Science techniques. Then we’ll go over some important graphing tools.Data Science and Bioinformatics are closely related fields, and so many times bioinformaticians are called upon to get involved in traditional data science tasks. As such, it is important to have a solid grounding in data science techniques. In this chapter we’ll go over Numpy, a critical scientific library for Python. We’ll also get a quick introduction to some key Data Science techniques like Principal Components Analysis (PCA) and Decision Trees. In doing so, we’ll learn about an amazing toolkit called scikit-learn. We’ll also develop some basic graphing skills that we’ll use throughout the book.
- In this chapter we’re going to cover the following main topics:
- NumPy – the Engine behind Python...
