Book Image

Learning pandas - Second Edition

By : Michael Heydt
Book Image

Learning pandas - Second Edition

By: Michael Heydt

Overview of this book

You will learn how to use pandas to perform data analysis in Python. You will start with an overview of data analysis and iteratively progress from modeling data, to accessing data from remote sources, performing numeric and statistical analysis, through indexing and performing aggregate analysis, and finally to visualizing statistical data and applying pandas to finance. With the knowledge you gain from this book, you will quickly learn pandas and how it can empower you in the exciting world of data manipulation, analysis and science.
Table of Contents (16 chapters)

Numerical and Statistical Methods

pandas is extremely powerful for modeling and manipulating data, but it also provides many powerful tools for numerical and statistical analysis. These capabilities are tightly integrated with pandas data structures and thereby make complex calculations very simple once the data is modeled.

This chapter will examine many of these capabilities. It starts with common numerical methods such as arithmetic with alignment across multiple objects, as well as finding specific values such as minimums and maximums. We then will look at many of the statistical capabilities of pandas, such as working with quantiles, ranking of values, variance, correlation, and many others.

Last but not least, we will examine a very powerful capability provided in pandas known as the rolling window. Rolling windows provide a means of applying various methods such mean calculation...