Python for Data Analysis Data Wrangling with Pandas, NumPy, and Jupyter Wes McKinney

By:

McKinney,Wes

Material type: Text

TextLanguage: English Publication details: Beijing O'Reilly 2022Edition: 3Description: xvi, 561 pISBN:

978-9355421906 (PB)

Subject(s):

DDC classification:

005.133 MCK

Contents:

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

Summary: Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.10 and pandas 1.4, 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

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Reference	IIITDM Kurnool Reference	Reference	005.133 MCK (Browse shelf(Opens below))	Not for loan		0005755
Books	IIITDM Kurnool	Non-fiction	005.133 MCK (Browse shelf(Opens below))	Available		0005756
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Books	IIITDM Kurnool	Non-fiction	005.133 MCK (Browse shelf(Opens below))	Checked out	22.01.2025	0005758
Books	IIITDM Kurnool COMPUTER SCIENCE ENGINEERING		005.133 MCK (Browse shelf(Opens below))	Checked out	25.09.2025	0005759

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Previous	005.1 SOM Software engineering	005.1 SOM Software engineering	005.1 SOM Software engineering	005.133 MCK Python for Data Analysis Data Wrangling with Pandas, NumPy, and Jupyter	005.133 SEV Python for Everybody : Exploring Data Using Python 3	005.133 SUR Hands-On Exploratory Data Analysis with Python: Perform EDA techniques to understand, summarize, and investigate your data	005.133 SUR Hands-On Exploratory Data Analysis with Python: Perform EDA techniques to understand, summarize, and investigate your data	Next

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 3.10 and pandas 1.4, 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

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