Python Data Analytics: With Pandas, NumPy, and Matplotlib

Fabio Nelli

Python Data Analytics: With Pandas, NumPy, and Matplotlib

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商品描述

Explore the latest Python tools and techniques to help you tackle the world of data acquisition and analysis. You'll review scientific computing with NumPy, visualization with matplotlib, and machine learning with scikit-learn. 
 
This revision is fully updated with new content on social media data analysis, image analysis with OpenCV, and deep learning libraries. Each chapter includes multiple examples demonstrating how to work with each library. At its heart lies the coverage of pandas, for high-performance, easy-to-use data structures and tools for data manipulation
 

Author Fabio Nelli expertly demonstrates using Python for data processing, management, and information retrieval. Later chapters apply what you've learned to handwriting recognition and extending graphical capabilities with the JavaScript D3 library. Whether you are dealing with sales data, investment data, medical data, web page usage, or other data sets, Python Data Analytics, Second Edition is an invaluable reference with its examples of storing, accessing, and analyzing data.

 
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
Who This Book Is For
 
Experienced Python developers who need to learn about Pythonic tools for data analysis

商品描述(中文翻譯)

探索最新的Python工具和技術，幫助您應對數據收集和分析的世界。您將回顧使用NumPy進行科學計算，使用matplotlib進行可視化，以及使用scikit-learn進行機器學習。

這本修訂版完全更新，新增了有關社交媒體數據分析、使用OpenCV進行圖像分析以及深度學習庫的內容。每一章節都包含多個示例，演示如何使用每個庫進行工作。其中重點是pandas，它提供了高性能、易於使用的數據結構和工具，用於數據操作。

作者Fabio Nelli熟練地演示了如何使用Python進行數據處理、管理和信息檢索。後面的章節將所學應用於手寫識別和擴展JavaScript D3庫的圖形能力。無論您處理銷售數據、投資數據、醫療數據、網頁使用情況還是其他數據集，Python數據分析（第二版）都是一本寶貴的參考資料，其中包含了存儲、訪問和分析數據的示例。

您將學到什麼：
- 理解數據分析的核心概念和Python生態系統
- 深入研究pandas，用於讀取、寫入和處理數據
- 使用工具和技術進行數據可視化和圖像分析
- 檢查流行的深度學習庫Keras、Theano、TensorFlow和PyTorch

適合閱讀對象：
- 有經驗的Python開發人員，需要了解用於數據分析的Python工具

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