Chapter 11: Introduction to NumPy and pandas
In recent years, Python has gained a lot of popularity in the data science field. Its very efficient and readable syntax makes the language a very good choice for scientific research, while still being suitable for production workloads: it's very easy to deploy research projects into real applications that will bring value to users. Thanks to this growing interest, a lot of specialized Python libraries have emerged. The most well known are probably NumPy and pandas. Their goal is to provide a set of tools to manipulate a big set of data in an efficient way, much more than what we could actually achieve with standard Python, and we'll show how and why in this chapter. NumPy and pandas are at the heart ...
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