INTRODUCTION

Often one gets the question as a Data Scientist what the Python Data Science Stack actually is and where a beginner should start to learn. The Python ecosystem, especially around topics such as data analytics, data mining, data science, and machine learning is so vast and rich that it confuses many. For such an audience a slide deck is created that starts with pointing out the benefits of the Python language for analytics. Even beginners in Python are addressed by some slides that explain the syntax of Python and how to get started. After that, some slides present the most important packages of the data science stack, namely NumPy, Matplotlib, and Pandas. NumPy is one of the most fundamental libraries in Python and perhaps the most useful of them all. NumPy handles large datasets effectively and efficiently. Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Finally, Pandas is a high-level data manipulation tool and is built on the Numpy package. The key data structure of the Pandas package is called the DataFrame. DataFrames allow you to store and manipulate tabular data in rows of observations and columns of variables. At the end of the course, you will have a solid grasp on NumPy, Matplotlib, and Pandas and how it works in Python.