Learn Data Analysis with Python
Apress (Verlag)
978-1-4842-3485-3 (ISBN)
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.
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.
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.
“The present book is built as an accessible, yet thorough introduction to data analysis using Python as programming environment. … The style of the book and textbook-like presentation of concepts recommend it as a good starting point for novices who wish either to understand more about data analysis or wish to learn Python through meaningful examples.” (Irina Ioana Mohorianu, zbMATH 1393.68002, 2018)
| Erscheinungsdatum | 11.03.2018 |
|---|---|
| Zusatzinfo | 15 Illustrations, color; IX, 97 p. 15 illus. in color. |
| Verlagsort | Berkley |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
| Informatik ► Programmiersprachen / -werkzeuge ► Python | |
| Mathematik / Informatik ► Mathematik ► Finanz- / Wirtschaftsmathematik | |
| Schlagworte | Analysis • application • Big Data • Code • Data • Data Science • learn • machine learning • Program • Python • Software • source |
| ISBN-10 | 1-4842-3485-5 / 1484234855 |
| ISBN-13 | 978-1-4842-3485-3 / 9781484234853 |
| Zustand | Neuware |
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