Mastering Microsoft Power BI: Expert techniques for effective data analytics and business intelligence

Проектируйте, создавайте и управляйте надежными решениями Power BI, чтобы получать значимые бизнес-идеи

Ключевая особенность
- Освойте все функции панели мониторинга и отчетности Microsoft Power BI
- Объединяйте данные из разных источников, создавайте потрясающие визуализации и публикуйте свои отчеты на разных платформах

This book supplies insightful, detailed guidance on fundamental data mining techniques. The book guides readers through the use of Python software for developing predictive models and techniques in order to describe and find patterns in data. The authors use interesting, real-world examples to build a theoretical and practical understanding of key data mining methods, with a focus on analytics rather than programming.

Professional developers know the many benefits of writing application code that’s clean, well-organized, and easy to maintain. By learning and following established patterns and best practices, you can take your code and your career to a new level.
With Practices of the Python Pro, you’ll learn to design professional-level, clean, easily maintainable software at scale using the incredibly popular programming language, Python. You’ll find easy-to-grok examples that use pseudocode and Python to introduce software development best practices, along with dozens of instantly useful techniques that will help you code like a pro.

Designing Event-Driven Systems Concepts and Patterns for Streaming Services with Apache Kafka.pdf

Mastering pandas for Finance.pdf

Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6
- Use the IPython shell and Jupyter notebook for exploratory computing
- Learn basic and advanced features in NumPy (Numerical Python)
- Get started with data analysis tools in the pandas library
- Use flexible tools to load, clean, transform, merge, and reshape data
- Create informative visualizations with matplotlib
- Apply the pandas groupby facility to slice, dice, and summarize datasets
- Analyze and manipulate regular and irregular time series data
- Learn how to solve real-world data analysis problems with thorough, detailed examples

Python for Finance
Mastering Data-Driven Finance
Second Edition
Yves Hilpisch

Practical DataOps Delivering Agile Data Science At Scale by Harvinder Atwal.pdf

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.