Avoiding Data Pitfalls How to Steer Clear of Common Blunders When Working with Data and Presenting Analysis and Visualizations.pdf

The DevOps Handbook How to Create World-Class Agility, Reliability, and Security in Technology Organizations by Gene Kim, Jez Humble, and Patrick Debois.pdf

DevOps in Python Infrastructure as Python by Zadka, Moshe
Explore and apply best practices for efficient application deployment. This book draws upon author Moshe Zadka's years of Dev Ops experience and focuses on the parts of Python, and the Python ecosystem, that are relevant for DevOps engineers.

You'll start by writing command-line scripts and automating simple DevOps-style tasks. You'll then move on to more advanced cases, like using Jupyter as an auditable remote-control panel, and writing Ansible and Salt extensions. This work also covers how to use the AWS API to manage cloud infrastructure, and how to manage Python programs and environments on remote machines.

Take a modern API-first approach to creating 3 different Django back-ends: a Library API, Todo API, and a Blog API with user authentication, permissions, proper documentation, and more. You'll even learn how to connect them to a React front-end for a truly full-stack web application.

Topics covered include Django 3.0 and Python 3.7, Django REST Framework, HTTP, API permissions, custom user models, user authentication (basic, sessions, and tokens), viewsets, routers, schemas, and documentation.

Pandas 1.x Cookbook Practical recipes for scientific computing, time series analysis, and exploratory data analysis using Python.pdf
Key Features:
• Use the power of pandas to solve most complex scientific computing problems with ease
• Leverage fast, robust data structures in pandas to gain useful insights from your data
• Practical, easy to implement recipes for quick solutions to common problems in data using pandas

Selenium Framework Design in Data-Driven Testing. 2018 Packt Publishing
Key Features
- A comprehensive guide to designing data-driven test frameworks using the Selenium 3 WebDriver API, AppiumDriver API, Java-Bindings, and TestNG
- Learn how to use Selenium Page Object Design Patterns and D.R.Y. (Don't Repeat Yourself) Approaches to software development in automated testing
- Discover the Selenium Grid Architecture and build your own grid for browser and mobile devices
- Use third party tools and services like ExtentReports for results processing, reporting, and SauceLabs for cloud-based test services

Test-Driven Development with Python: Obey the Testing Goat: Using Django, Selenium, and JavaScript
By taking you through the development of a real web application from beginning to end, this hands-on guide demonstrates the practical advantages of test-driven development (TDD) with Python. You’ll learn how to write and run tests before building each part of your app, and then develop the minimum amount of code required to pass those tests. The result? Clean code that works.

In the process, you’ll learn the basics of Django, Selenium, Git, jQuery, and Mock, along with current web development techniques. If you’re ready to take your Python skills to the next level, this book clearly demonstrates how TDD encourages simple designs and inspires confidence.

Hands-On Data Analysis with NumPy and pandas
About This Book
• Explore the tools you need to become a data analyst
• Discover practical examples to help you grasp data processing concepts
• Walk through hierarchical indexing and grouping for data analysis

What You Will Learn
• Understand how to install and manage Anaconda
• Read, sort, and map data using NumPy and pandas
• Find out how to create and slice data arrays using NumPy
• Discover how to subset your DataFrames using pandas
• Handle missing data in a pandas DataFrame
• Explore hierarchical indexing and plotting with pandas

Pandas for Everyone. Python Data Analysis
• Setting up your Python and Pandas environment
• Getting started with Pandas dataframes
• Using dataframes to calculate and perform basic statistical tasks
• Plotting in Matplotlib
• Cleaning data, reshaping dataframes, handling missing values, working with dates, and more
• Building basic data analytics models
• Applying machine learning techniques: both supervised and unsupervised
• Creating reproducible documents using literate programming techniques

The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style employed is more accessible and concise, in keeping with the needs of engineering students. The book outlines the shortest possible path from no previous experience with programming to a set of skills that allows students to write simple programs for solving common mathematical problems with numerical methods in the context of engineering and science courses. The emphasis is on generic algorithms, clean program design, the use of functions, and automatic tests for verification.

Key Features
• Explore the latest version of Django, and learn effectively with the help of practical examples
• Follow a task-based approach to develop professional web apps using Django and Python
• Learn to deploy, scale, and secure apps using Docker and Amazon Web Services(AWS)

What you will learn
• Discover how to set the basic configurations to start any Django project
• Understand full-stack web application development using Django
• Build a database structure using reusable model mixins
• Implement security, performance, and deployment features in your web apps
• Import data from local sources and external web services and export it to your app
• Secure web applications against malicious usage and find and fix common performance bottlenecks

Django is a web framework for perfectionists with deadlines, designed to help you build manageable medium and large web projects in a short time span. This fourth edition of Django Web Development Cookbook is updated with Django 3's latest features to guide you effectively through the development process. This Django book starts by helping you create a virtual environment and project structure for building Python web apps. You'll learn how to build models, views, forms, and templates for your web apps and then integrate JavaScript in your Django apps to add more features. As you advance, you'll create responsive multilingual websites, ready to be shared on social networks. The book will take you through uploading and processing images, rendering data in HTML5, PDF, and Excel, using and creating APIs, and navigating different data types in Django. You'll become well-versed in security best practices and caching techniques to enhance your website's security and speed.

Python is one of the top 3 tools that Data Scientists use.One of the tools in their arsenal is the Pandas library.This tool is popular because it gives you so much functionality out of the box.In addition, you can use all the power of Python to make the hard stuff easy!

Learning the Pandas Libraryis designed to bring developers and aspiring data scientists who are anxious to learn Pandas up to speed quickly. It starts with the fundamentals of the data structures. Then, it covers the essential functionality. It includes many examples, graphics, code samples, and plots from real world examples.

Microsoft Power BI Quick Start Guide Build dashboards and visualizations to make your data come to life.pdf

https://github.com/PacktPublishing/Microsoft-Power-BI-Quick-Start-Guide - This is the code repository for Microsoft Power BI Quick Start Guide, published by Packt.

Build dashboards and visualizations to make your data come to life

Mastering Large Datasets with Python Parallelize and Distribute Your Python Code.pdf

What's inside
• An introduction to the map and reduce paradigm
• Parallelization with the multiprocessing module and pathos framework
• Hadoop and Spark for distributed computing
• Running AWS jobs to process large datasets

Python Projects for Beginners A Ten-Week Bootcamp Approach to Python Programming.pdf

What You Will Learn
- Understand beginning and more advanced concepts of the Python language
- Be introduced to data analysis using pandas, the Python Data Analysis library
- Walk through the process of interviewing and answering technical questions
- Create real-world applications with the Python language
- Learn how to use Anaconda, Jupyter Notebooks, and the Python Shell

Personal Finance with Python Using pandas, Requests, and Recurrent.pdf

Deal with data, build up financial formulas in code from scratch, and evaluate and think about money in your day-to-day life. This book is about Python and personal finance and how you can effectively mix the two together.

In Personal Finance with Python you will learn Python and finance at the same time by creating a profit calculator, a currency converter, an amortization schedule, a budget, a portfolio rebalancer, and a purchase forecaster. Many of the examples use pandas, the main data manipulation tool in Python. Each chapter is hands-on, self-contained, and motivated by fun and interesting examples.

Demonstrate the use of Python Requests with the help of examples

Use the Requests module to deal with the inner sections of the request-response cycles

Implement the RESTful Web API with Python Requests

Authenticate Requests using different authentication methods

Emulate server actions and interact with a mock server

Interact with social networking sites such as Facebook, Twitter, and reddit

Scrape the Web with Python Requests and BeautifulSoup

Build your own web application with Flask

Python Data Analytics With Pandas, NumPy, and Matplotlib by Fabio Nelli.pdf

What You'll Learn
- Understand the core concepts of data analysis and the Python ecosystem
- Go in depth with pandas for reading, writing, and processing data
- Use tools and techniques for data visualization and image analysis
- Examine popular deep learning libraries Keras, Theano,TensorFlow, and PyTorch

Reinventing ITIL in the Age of DevOps Innovative Techniques to Make Processes Agile and Relevant.pdf

What You Will Learn
• Discover the basics of ITIL and DevOps
• Compare ITIL and DevOps
• Understand the structure of a DevOps organization and adapt the ITIL roles to this structure
• Re-engineer ITIL for DevOps projects
• Implement major processes such as incident management, configuration management, and change management processes in DevOps projects
• Automate activities within processes

Django 3 By Example Build powerful and reliable Python web applications from scratch by Antonio Melé.pdf

Learn Django 3 with four end-to-end web projects Key Features Learn Django 3 by building real-world web applications from scratch in Python, using coding best practices Integrate other technologies into your application with clear, step-by-step explanations and comprehensive example code Implement advanced functionalities like a full-text search engine, a user activity stream, or a recommendation engine Add real-time features with Django Channels and WebSockets Book Description If you want to learn the entire process of developing professional web applications with Python and Django, then this book is for you. In the process of building four professional Django projects, you will learn about Django 3 features, how to solve common web development problems, how to implement best practices, and how to successfully deploy your applications...