Data Analysis and Visualization Using Python

Book Description

Data Analysis and Visualization Using Python: Analyze Data to Create Visualizations for BI Systems

Look at Python from a data science point of view and learn proven techniques for data visualization as used in making critical business decisions. Starting with an introduction to data science with Python, you will take a closer look at the Python environment and get acquainted with editors such as Jupyter Notebook and Spyder. After going through a primer on Python programming, you will grasp fundamental Python programming techniques used in data science. Moving on to data visualization, you will see how it caters to modern business needs and forms a key factor in decision-making. You will also take a look at some popular data visualization libraries in Python.

Shifting focus to data structures, you will learn the various aspects of data structures from a data science perspective. You will then work with file I/O and regular expressions in Python, followed by gathering and cleaning data. Moving on to exploring and analyzing data, you will look at advanced data structures in Python. Then, you will take a deep dive into data visualization techniques, going through a number of plotting systems in Python.

In conclusion, you will complete a detailed case study, where you’ll get a chance to revisit the concepts you’ve covered so far.

What You Will Learn

• Use Python programming techniques for data science
• Master data collections in Python
• Create engaging visualizations for BI systems
• Deploy effective strategies for gathering and cleaning data
• Integrate the Seaborn and Matplotlib plotting systems

Who This Book Is For

Developers with basic Python programming knowledge looking to adopt key strategies for data analysis and visualizations using Python.

Table of Contents

Chapter 1: Introduction to Data Science with Python
Chapter 2: The Importance of Data Visualization in Business Intelligence
Chapter 3: Data Collection Structures
Chapter 4: File I/O Processing and Regular Expressions
Chapter 5: Data Gathering and Cleaning
Chapter 6: Data Exploring and Analysis
Chapter 7: Data Visualization
Chapter 8: Case Studies

中文：

书名：Data Analysis and Visualization Using Python

使用Python进行数据分析和可视化：分析数据以创建BI系统的可视化

从数据科学的角度看待Python，并学习用于制定关键业务决策的经过验证的数据可视化技术。从介绍使用Python的数据科学开始，您将更深入地了解Python环境，并熟悉Jupyter Notebook和Spyder等编辑器。在阅读了有关Python编程的入门读物之后，您将掌握数据科学中使用的基本Python编程技术。转到数据可视化，您将看到它如何迎合现代业务需求，并成为决策中的关键因素。您还将了解一些流行的Python数据可视化库。

将重点转移到数据结构，您将从数据科学的角度学习数据结构的各个方面。然后，您将使用Python中的文件I/O和正则表达式，然后收集和清理数据。接下来研究和分析数据，您将了解一下Python中的高级数据结构。然后，您将深入研究数据可视化技术，了解一些使用Python语言的绘图系统。

总之，您将完成一个详细的案例研究，在其中您将有机会重温到目前为止已经介绍过的概念。

你将学到什么

• 将Python编程技术用于数据科学
• Master data collections in Python
• 为BI系统创建引人入胜的可视化效果
• 部署收集和清理数据的有效策略
• 集成Seborn和Matplotlib绘图系统

这本书是为谁写的

具有基本的Python编程知识的开发人员希望采用关键策略来使用Python进行数据分析和可视化。

目录表

第1章：用Java Python入门数据科学
第二章：数据可视化在商业智能中的重要性
第3章：数据收集结构
第4章：文件I/O处理和正则表达式
第五章：数据收集和数据清理
第六章：数据挖掘和数据分析
第7章：数据可视化
第八章：案例研究