Getting Started with Python Data Analysis (Paperback)

Phuong Vo.T.H, Martin Czygan

  • 出版商: Packt Publishing
  • 售價: $1,600
  • 貴賓價: 9.5$1,520
  • 語言: 英文
  • 頁數: 188
  • 裝訂: Paperback
  • ISBN: 1785285114
  • ISBN-13: 9781785285110
  • 相關分類: Python程式語言Data Science
  • 海外代購書籍(需單獨結帳)

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商品描述

Learn to use powerful Python libraries for effective data processing and analysis

About This Book

  • Learn the basic processing steps in data analysis and how to use Python in this area through supported packages, especially Numpy, Pandas, and Matplotlib
  • Create, manipulate, and analyze your data to extract useful information to optimize your system
  • A hands-on guide to help you learn data analysis using Python

Who This Book Is For

If you are a Python developer who wants to get started with data analysis and you need a quick introductory guide to the python data analysis libraries, then this book is for you.

What You Will Learn

  • Understand the importance of data analysis and get familiar with its processing steps
  • Get acquainted with Numpy to use with arrays and array-oriented computing in data analysis
  • Create effective visualizations to present your data using Matplotlib
  • Process and analyze data using the time series capabilities of Pandas
  • Interact with different kind of database systems, such as file, disk format, Mongo, and Redis
  • Apply the supported Python package to data analysis applications through examples
  • Explore predictive analytics and machine learning algorithms using Scikit-learn, a Python library

In Detail

Data analysis is the process of applying logical and analytical reasoning to study each component of data. Python is a multi-domain, high-level, programming language. It's often used as a scripting language because of its forgiving syntax and operability with a wide variety of different eco-systems. Python has powerful standard libraries or toolkits such as Pylearn2 and Hebel, which offers a fast, reliable, cross-platform environment for data analysis.

With this book, we will get you started with Python data analysis and show you what its advantages are.

The book starts by introducing the principles of data analysis and supported libraries, along with NumPy basics for statistic and data processing. Next it provides an overview of the Pandas package and uses its powerful features to solve data processing problems.

Moving on, the book takes you through a brief overview of the Matplotlib API and some common plotting functions for DataFrame such as plot. Next, it will teach you to manipulate the time and data structure, and load and store data in a file or database using Python packages. The book will also teach you how to apply powerful packages in Python to process raw data into pure and helpful data using examples.

Finally, the book gives you a brief overview of machine learning algorithms, that is, applying data analysis results to make decisions or build helpful products, such as recommendations and predictions using scikit-learn.

Style and approach

This is an easy-to-follow, step-by-step guide to get you familiar with data analysis and the libraries supported by Python. Topics are explained with real-world examples wherever required.

商品描述(中文翻譯)

學習使用強大的Python函式庫進行有效的數據處理和分析

關於本書
- 通過支援的套件,特別是Numpy、Pandas和Matplotlib,學習數據分析的基本處理步驟以及如何在這個領域中使用Python
- 創建、操作和分析數據,提取有用信息以優化系統
- 一個實踐指南,幫助您學習使用Python進行數據分析

本書適合對數據分析有興趣並希望快速入門Python數據分析函式庫的Python開發人員。

您將學到什麼
- 了解數據分析的重要性,熟悉其處理步驟
- 熟悉Numpy,用於數組和數組導向計算的數據分析
- 使用Matplotlib創建有效的可視化圖表來展示數據
- 使用Pandas的時間序列功能處理和分析數據
- 與不同類型的數據庫系統(如文件、磁盤格式、Mongo和Redis)進行交互
- 通過示例應用支援的Python套件進行數據分析應用
- 使用Python庫Scikit-learn探索預測分析和機器學習算法

詳細內容
數據分析是應用邏輯和分析推理研究數據的過程。Python是一種多領域、高級的編程語言。由於其寬容的語法和與各種不同生態系統的可操作性,它通常被用作腳本語言。Python具有強大的標準庫或工具包,如Pylearn2和Hebel,為數據分析提供了一個快速、可靠、跨平台的環境。

通過本書,我們將帶您入門Python數據分析,並向您展示其優勢。

本書首先介紹數據分析的原則和支援的庫,以及用於統計和數據處理的NumPy基礎知識。接下來,它概述了Pandas套件並使用其強大功能解決數據處理問題。

然後,本書將帶您瀏覽Matplotlib API的簡要概述以及DataFrame的一些常見繪圖函數,例如plot。接下來,它將教您如何操作時間和數據結構,以及如何使用Python套件將數據加載到文件或數據庫中。本書還將通過示例教您如何使用Python中的強大套件將原始數據處理為純淨且有用的數據。

最後,本書將簡要介紹機器學習算法,即將數據分析結果應用於做出決策或構建有用產品,例如使用scikit-learn進行推薦和預測。

風格和方法
這是一本易於理解、步驟清晰的指南,讓您熟悉數據分析以及Python支援的庫。在需要的地方,將通過實際示例來解釋相關主題。