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)

Answering simple questions about a dataset

Let's take an example to look at a few questions and answer them. Say the HR director asks you to answer a few descriptive questions about the employees of the company. The following are a few such questions:

  • How many employees are there by department in the dataset?
  • What is the overall attrition rate?
  • What is the average hourly rate?
  • What is the average number of years at the company?
  • Who are the five employees with the most number of years at the company?
  • How satisfied are employees overall?

Total employees by department in the dataset

To view the departments in the dataset, you use the data['Department'] statement. We get the column called Department, which is...