Book Image

Hands-On Data Analysis with NumPy and Pandas

By : Curtis Miller
5 (1)
Book Image

Hands-On Data Analysis with NumPy and Pandas

5 (1)
By: Curtis Miller

Overview of this book

Python, a multi-paradigm programming language, has become the language of choice for data scientists for visualization, data analysis, and machine learning. Hands-On Data Analysis with NumPy and Pandas starts by guiding you in setting up the right environment for data analysis with Python, along with helping you install the correct Python distribution. In addition to this, you will work with the Jupyter notebook and set up a database. Once you have covered Jupyter, you will dig deep into Python’s NumPy package, a powerful extension with advanced mathematical functions. You will then move on to creating NumPy arrays and employing different array methods and functions. You will explore Python’s pandas extension which will help you get to grips with data mining and learn to subset your data. Last but not the least you will grasp how to manage your datasets by sorting and ranking them. By the end of this book, you will have learned to index and group your data for sophisticated data analysis and manipulation.
Table of Contents (12 chapters)

Summary


In this chapter, we started by introducing NumPy data types. We then quickly moved on to discuss NumPy arrays, called ndarray objects, which are the main objects of interest in NumPy. We discussed how to create these arrays from programmer input, from other Python objects, from files, and even from functions. We proceeded to discuss how mathematical operations are performed on ndarray objects, from basic arithmetic to full-blown linear algebra.

In the next chapter, we will discuss some important topics: slicing ndarray objects arithmetic and linear algebra with arrays, and employing array methods and functions.