Python for data analysis : data wrangling with pandas, NumPy, and Jupyter / Wes McKinney.
Material type:
TextPublication details: New Delhi: Shroff Publishers and Distributors Pvt.Ltd., 2022Edition: Third editionDescription: xvi, 561 pages illustrations 24 cmISBN: - 9781098104030
- 109810403X
- 006.312 23 M1583p
| Item type | Current library | Call number | Vol info | Copy number | Status | Barcode | |
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Library, Independent University, Bangladesh (IUB) Reference Stacks | 006.312 M1583p (Browse shelf(Opens below)) | 2022 | 01 | Not For Loan | 029692 | |
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Library, Independent University, Bangladesh (IUB) Reference Stacks | 006.312 M1583p (Browse shelf(Opens below)) | 2022 | 02 | Not For Loan | 029693 |
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| 006.31015192 M9781p Probabilistic machine learning : advanced topics / | 006.312 H2331d 2012 Data mining : concepts and techniques / | 006.312 M1583p Python for data analysis : data wrangling with pandas, NumPy, and Jupyter / | 006.312 M1583p Python for data analysis : data wrangling with pandas, NumPy, and Jupyter / | 006.312 M675c Clustering for Data Mining : a data recovery approach / | 006.312 V224p Python data science handbook : essential tools for working with data / | 006.312 V224p Python data science handbook : essential tools for working with data / |
Previous edition: 2017.
Includes index.
Includes bibliographical references and index.
Preliminaries -- Python language basics IPython, and Jupyter notebooks -- Built-in data structures, functions, and files -- NumPy basics: arrays and vectorized computation -- Getting started with pandas -- Data loading, storage, and file formats -- Data cleaing and preparation -- Data wrangling: join, combine, reshape -- Plotting and visualization -- Data aggregation and group operations -- Time series -- Introduction to modeling libraries in Python -- Data analysis examples -- Advanced NumPy -- More on the IPython system.
"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. It's ideal for analysts new to Python and for Python programmers new to data science and scientific computing." -- Provided by publisher
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