This task will use only the first set (i.e., the first two columns). The data file is a text file with tabs as column separators and a few lines as a header. This is a set of artificially constructed data that gives the same results when fitted with a straight line, but their plots are very different. The example data is the first set of Anscombe's quartet, shown in the table below. This is a common situation that many data scientists have encountered.
The program you will write in this series:
The full examples are available in the polyglot_fit repository. It is not intended to be an exhaustive comparison of the languages, just a little showcase.Īll of the programs are meant to be run on the command line, not with a graphical user interface (GUI).
To that ends, I will explain how to write a program in Python and GNU Octave for a particular task you could classify as data science. If you are already familiar with one of the languages, start with that one and go through the others to look for similarities and differences. To get a feeling for a new programming language (and its documentation), I always start by writing some example programs that perform a task I know well.
Why? It is mostly a combination of boredom with the old ways and curiosity about the new ways. Choosing Python and GNU Octave for data scienceĮvery so often, I try to learn a new programming language. Some are well-known for solving problems in this space, while others are lesser-known. This article will help you become familiar with doing data science with some popular languages. Welcome to the communityĭata science is a domain of knowledge that spans programming languages.Running Kubernetes on your Raspberry Pi.
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