Python for Data Analysis: Data Wrangling with pandas, NumPy, and Jupyter, 3/e (Paperback)
暫譯: Python 數據分析：使用 pandas、NumPy 和 Jupyter 進行數據整理，第 3 版 (平裝本)
McKinney, Wes
- 出版商: O'Reilly
- 出版日期: 2022-09-20
- 定價: $2,800
- 售價: 9.0 折 $2,520
- 語言: 英文
- 頁數: 579
- 裝訂: Quality Paper - also called trade paper
- ISBN: 109810403X
- ISBN-13: 9781098104030
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相關分類:
Python、程式語言、Data Science
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相關翻譯:
Python 資料分析, 3/e (Python for Data Analysis: Data Wrangling with pandas, NumPy, and Jupyter, 3/e) (繁中版)
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商品描述
Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.9 and pandas 1.2, the third edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You'll learn the latest versions of pandas, NumPy, and Jupyter in the process.
Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It's ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub.
- Use the Jupyter notebook and IPython shell for exploratory computing
- Learn basic and advanced features in NumPy
- 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
商品描述(中文翻譯)
獲得一本關於在 Python 中操作、處理、清理和分析數據集的權威手冊。這本針對 Python 3.9 和 pandas 1.2 更新的第三版實用指南，充滿了實際案例研究，展示了如何有效解決各種數據分析問題。在這個過程中，您將學習到最新版本的 pandas、NumPy 和 Jupyter。
本書由 Python pandas 專案的創建者 Wes McKinney 撰寫，是一本對 Python 數據科學工具的實用、現代化介紹。它非常適合剛接觸 Python 的分析師以及對數據科學和科學計算感興趣的 Python 程式設計師。數據文件和相關資料可在 GitHub 上獲得。
- 使用 Jupyter notebook 和 IPython shell 進行探索性計算
- 學習 NumPy 的基本和進階功能
- 開始使用 pandas 庫中的數據分析工具
- 使用靈活的工具加載、清理、轉換、合併和重塑數據
- 使用 matplotlib 創建資訊豐富的可視化
- 應用 pandas 的 groupby 功能來切片、切塊和總結數據集
- 分析和操作常規及不規則的時間序列數據
- 學習如何通過詳細的實例解決現實世界的數據分析問題
