Become a Python Data Analyst

This is the code repository for Become a Python Data Analyst, published by Packt.

What is this book about?

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.

This book covers the following exciting features:

Explore important Python libraries and learn to install Anaconda distribution
Understand the basics of NumPy
Produce informative and useful visualizations for analyzing data
Perform common statistical calculations
Build predictive models and understand the principles of predictive analytics

If you feel this book is for you, get your copy today!

Instructions and Navigations

All of the code is organized into folders. For example, Chapter02.

The code will look like the following:

# The largest heading
## The second largest heading
###### The smallest heading

Following is what you need for this book: Hands-On Data Analysis with NumPy and Pandas is for you if you are a Python developer and want to take your first steps into the world of data analysis. No previous experience of data analysis is required to enjoy this book.

With the following software and hardware list you can run all code files present in the book (Chapter 1-6).

Software and Hardware List

Chapter	Software required	OS required
All	Python 3.6 or later	Windows, Mac OS X, and Linux (Any)
All	Anaconda 5.2	Windows, Mac OS X, and Linux (Any)
All	Jupyter Notebook	Windows, Mac OS X, and Linux (Any)

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.

Get to Know the Author

Alvaro Fuentes Alvaro Fuentes is a data scientist with an M.S. in quantitative economics and applied mathematics with more than 10 years of experience in analytical roles. He worked in the central bank of Guatemala as an economic analyst, building models for economic and financial data. He founded Quant to provide consulting and training services in data science topics and has been a consultant for many projects in fields such as business, education, psychology, and mass media. He has taught courses to students in topics such as data science, mathematics, statistics, R programming, and Python. He also has technical skills in R programming, Spark, PostgreSQL, Microsoft Excel, machine learning, statistical analysis, econometrics, and mathematical modeling.

Other books by the author

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