We've talked about NumPy in previous chapters. Now let's move on to pandas, a well-designed package for storing, managing, and manipulating data in Python. We'll start this chapter by discussing what pandas is and why people use it. Next, we'll discuss the two most important objects provided by pandas: series and DataFrames. We will then cover how to subset your data. In this chapter, we'll get a brief overview of what pandas is, and why it's popular.
Hands-On Data Analysis with NumPy and Pandas
By :
Hands-On Data Analysis with NumPy and Pandas
By:
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)
Title Page
Packt Upsell
Contributors
Preface
Free Chapter
Setting Up a Python Data Analysis Environment
Diving into NumPY
Operations on NumPy Arrays
pandas are Fun! What is pandas?
Arithmetic, Function Application, and Mapping with pandas
Managing, Indexing, and Plotting
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Index
Customer Reviews