- eBook:Python for Data Analysis: A Practical Guide for Manipulating, Processing, Cleaning, and Crunching Data Sets in Python. How to Effectively Solve a Wide Range of Data Analysis Problems
- Author:Dylan Penny
- Data:January 1, 2021
- Pages:107 pages
You don’t need a costly computer science degree, a genius mind, and a 1000-page textbook to learn Python’s basics for Data Analysis.
This book, PYTHON FOR DATA ANALYSIS: A PRACTICAL GUIDE TO MANIPULATING, PROCESSING, CLEANING, AND CRUNCHING DATA SETS IN PYTHON. HOW TO EFFECTIVELY SOLVE A WIDE RANGE OF DATA ANALYSIS PROBLEMS, is a concise, step-by-step guide to Python for Data Analysis.
Many books about Pythons are theoretical and have little to no practical examples. This manual offers a plethora of simple illustrations and examples to underline core concepts and enhance your understanding. Loads of practice exercises are provided to make you learn fast, remember, and build a thorough understanding of the key concepts.
Are you ready to find out more?
Here’s a short preview of what you will learn inside this book:
Why Python for data analysis?
Data analysis bases
Python libraries and installation
Python language basics, ipython and jupyter notebooks
Built-in data structures, functions, and files
Introduction to modeling libraries in Python
CHAPTER 2. DATA ANALYSIS, THE BASICS
CHAPTER 3. ESSENTIAL PYTHON LIBRARIES (NUMPY, IPYTHON)
CHAPTER 4. PYTHON LIBRARIES AND INSTALLATION (MATPLOTLIB, PANDAS)
CHAPTER 5. INSTALLATION AND SETUP
CHAPTER 6. PYTHON LANGUAGE BASICS, IPYTHON AND JUPYTER NOTEBOOKS
CHAPTER 7. BUILT-IN DATA STRUCTURES, FUNCTIONS, AND FILES
CHAPTER 8. NUMPY BASICS: ARRAYS AND VECTORIZED COMPUTATION
CHAPTER 9. GETTING STARTED WITH PANDAS
CHAPTER 10. PLOTTING AND VISUALIZATION
CHAPTER 11. DATA AGGREGATION AND GROUP OPERATIONS
CHAPTER 12. INTRODUCTION TO MODELING LIBRARIES IN PYTHON
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