This is the code repository for Practical Data Analysis using Jupyter Notebook, published by Packt.
Learn how to speak the language of data by extracting useful and actionable insights using Python
The book will take you on a journey through the evolution of data analysis explaining each step in the process in a very simple and easy to understand manner. You will learn how to use various Python libraries to work with data. Learn how to sift through the many different types of data, clean it, and analyze it to gain useful insights.
This book covers the following exciting features:
- Understand the importance of data literacy and how to communicate effectively using data
- Find out how to use Python packages such as NumPy, pandas, Matplotlib, and the Natural Language Toolkit (NLTK) for data analysis
- Wrangle data and create DataFrames using pandas
- Produce charts and data visualizations using time-series datasets
- Discover relationships and how to join data together using SQL
- Use NLP techniques to work with unstructured data to create sentiment analysis models
- Discover patterns in real-world datasets that provide accurate insights
If you feel this book is for you, get your copy today!
All of the code is organized into folders.
The code will look like the following:
product_data = {
'product a': [13, 20, 0, 10],
'product b': [10, 30, 17, 20],
'product c': [6, 9, 10, 0]
}
Following is what you need for this book: This book is for aspiring data analysts and data scientists looking for hands-on tutorials and real-world examples to understand data analysis concepts using SQL, Python, and Jupyter Notebook. Anyone looking to evolve their skills to become data-driven personally and professionally will also find this book useful. No prior knowledge of data analysis or programming is required to get started with this book.
With the following software and hardware list you can run all code files present in the book (Chapter 2-12).
| Chapter | Software required | OS required |
|---|---|---|
| 2 - 12 | Jupyter Notebook, Anaconda, Python 3.X, NLTK / Google Colab | 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.
Marc Wintjen is a risk analytics architect at Bloomberg L.P. with over 20 years of professional experience. An evangelist for data literacy, he's known as the data mensch for helping others make data-driven decisions. His passion for all things data has evolved from SQL and data warehousing to big data analytics and data visualization.
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