Python for data analysis : data wrangling with Pandas, NumPy, and IPython / Wes McKinney.
Material type: TextPublication details: Mumbai : Shroff Publishers & Distributors, 2018.Edition: 2nd edDescription: xvi, 522 pISBN:- 9789352136414
- 005.262P 23 MCK
- QA76.73.P98
Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds |
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Books | Learning Resource Centre | Compact Shelving | 005.262P MCK (Browse shelf(Opens below)) | Available | 13798 | ||
Books | Learning Resource Centre | Reserve Books | 005.262P MCK (Browse shelf(Opens below)) | Not for loan | 13797 | ||
Books | Learning Resource Centre | 005.262P MCK (Browse shelf(Opens below)) | Available | 13796 | |||
Books | Learning Resource Centre | 005.262P MCK (Browse shelf(Opens below)) | Available | 13795 |
Includes index.
Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second 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, IPython, 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 IPython shell and Jupyter notebook for exploratory computingLearn basic and advanced features in NumPy (Numerical Python)Get started with data analysis tools in the pandas libraryUse flexible tools to load, clean, transform, merge, and reshape dataCreate informative visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsAnalyze and manipulate regular and irregular time series dataLearn how to solve real-world data analysis problems with thorough, detailed examples.
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