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Mastering Flask Web and API Development

You're reading from   Mastering Flask Web and API Development Build and deploy production-ready Flask apps seamlessly across web, APIs, and mobile platforms

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Product type Paperback
Published in Aug 2024
Publisher Packt
ISBN-13 9781837633227
Length 494 pages
Edition 1st Edition
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Author (1):
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Sherwin John C. Tragura Sherwin John C. Tragura
Author Profile Icon Sherwin John C. Tragura
Sherwin John C. Tragura
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Table of Contents (18) Chapters Close

Preface 1. Part 1:Learning the Flask 3.x Framework
2. Chapter 1: A Deep Dive into the Flask Framework FREE CHAPTER 3. Chapter 2: Adding Advanced Core Features 4. Chapter 3: Creating REST Web Services 5. Chapter 4: Utilizing Flask Extensions 6. Part 2:Building Advanced Flask 3.x Applications
7. Chapter 5: Building Asynchronous Transactions 8. Chapter 6: Developing Computational and Scientific Applications 9. Chapter 7: Using Non-Relational Data Storage 10. Chapter 8: Building Workflows with Flask 11. Chapter 9: Securing Flask Applications 12. Part 3:Testing, Deploying, and Building Enterprise-Grade Applications
13. Chapter 10: Creating Test Cases for Flask 14. Chapter 11: Deploying Flask Applications 15. Chapter 12: Integrating Flask with Other Tools and Frameworks 16. Index 17. Other Books You May Enjoy

Using the pandas module for data and graphical analysis

The pandas module is a popular Python library for data analysis because of its easy-to-apply utility functions and a high-performance tabular data structure called DataFrame. However, for the module to work, it needs the numpy module, a low-level library that supports multi-dimensional array objects called ndarray and its mathematical operations, and matplotlib, a library for visualizations. So, install these two modules first:

pip install numpy matplotlib

Then, install the pandas module:

pip install pandas

Since our data will be coming from XLSX sheets, install the openpyxl dependency module of pandas that deals with reading and writing XLSX documents:

pip install openpyxl

After installing all the dependency modules, we can start creating the DataFrame object.

Utilizing the DataFrame

To read an XLSX document, the pandas module has a read_excel() method with parameters such as usecols, which indicates the...

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