Learn Data Analysis with Python

Get started using Python in data analysis with this compact practical guide. This book includes three exercises and a case study on getting data in and out of Python code in the right format. Learn Data Analysis with Python also helps you discover meaning in the data using analysis and shows you how to visualize it.
Each lesson is, as much as possible, self-contained to allow you to dip in and out of the examples as your needs dictate. If you are already using Python for data analysis, you will find a number of things that you wish you knew how to do in Python. You can then take these techniques and apply them directly to your own projects.
If you aren't using Python for data analysis, this book takes you through the basics at the beginning to give you a solid foundation in the topic. As you work your way through the book you will have a better of idea of how to use Python for data analysis when you are finished.
What You Will Learn

• Get data into and out of Python code

• Prepare the data and its format

• Find the meaning of the data

• Visualize the data using iPython

  Who This Book Is For
  Those who want to learn data analysis using Python. Some experience with Python is recommended but not required, as is some prior experience with data analysis or data science.

  A quick and practical hands-on guide to learning and using Python in data analysis Includes three exercises and one analysis project case study Learn to visualize data using Python

  Autorentext

  AJ Henley is teaching courses on data analysis using Python, Java and more. He is a technology educator with over 20 years experience as a developer, designer and systems engineer. He is an instructor at Howard University and Montgomery College.
  Dave Wolf is a certified Project Management Professional (PMP) with over twenty years' experience as a software developer, analyst and trainer. His latest projects include collaboratively developing training materials and programming bootcamps for Java and Python.

  Inhalt

  1. How to Use This Book.- 2. Getting Data into and out of Python.- 3. Preparing Data is Half the Battle.- 4. Finding the Meaning.- 5. Visualizing Data.- 6. Practice Problems.