We have worked with data already in some of the previous chapters in this book, including data collection and some statistical computations. The samples in all of those cases were quite small, though. To run data analysis and train machine learning models smoothly on datasets of millions of records, researchers built a distinctive ecosystem of Python packages.
In this introductory chapter, we won't code much—instead, we'll overview the foundational packages and tools for the data science ecosystem, which we will be using throughout this part of this book, including the following:
- Introducing Python for data science
- Exploring NumPy
- Understanding pandas
- Trying SciPy and scikit-learn
- Understanding Jupyter
