Book Image

Become a Python Data Analyst

By : Alvaro Fuentes
Book Image

Become a Python Data Analyst

By: Alvaro Fuentes

Overview of this book

Python is one of the most common and popular languages preferred by leading data analysts and statisticians for working with massive datasets and complex data visualizations. Become a Python Data Analyst introduces Python’s most essential tools and libraries necessary to work with the data analysis process, right from preparing data to performing simple statistical analyses and creating meaningful data visualizations. In this book, we will cover Python libraries such as NumPy, pandas, matplotlib, seaborn, SciPy, and scikit-learn, and apply them in practical data analysis and statistics examples. As you make your way through the chapters, you will learn to efficiently use the Jupyter Notebook to operate and manipulate data using NumPy and the pandas library. In the concluding chapters, you will gain experience in building simple predictive models and carrying out statistical computation and analysis using rich Python tools and proven data analysis techniques. By the end of this book, you will have hands-on experience performing data analysis with Python.
Table of Contents (8 chapters)

Pandas - Everyone's Favorite Data Analysis Library

In this chapter, we will introduce the pandas library. We will talk about Pandas, its capabilities, and its importance in the Python data science stack. We will also talk about series and DataFrames, the main objects in the pandas library. We will discuss their properties, and some of the operations and manipulations that we can do with these objects when doing data analysis. Further on, we will see some examples of how to use the objects in this library using a real-world dataset and answer some simple questions about datasets. The chapter will cover the following topics:

  • The pandas library
  • The operation and manipulation of pandas
  • Answering simple questions about datasets with examples