MARC details
| 000 -LEADER |
|---|
| fixed length control field |
03487nam a22002777a 4500 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
230221s2021 |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781789955248 |
| 022 ## - INTERNATIONAL STANDARD SERIAL NUMBER |
|---|
| ISSN-L |
9781789955248 |
| 041 ## - LANGUAGE CODE |
|---|
| Language code of text/sound track or separate title |
English |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
005.133 |
| Item number |
NAV |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Navlani, Avinash |
| 9 (RLIN) |
673845 |
| Relator term |
author |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
Python Data Analysis Perform Data Collection Data Processing Wrangling Visualization and Model Building Using Python |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
3rd |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Place of publication, distribution, etc. |
Birmingham : |
| Name of publisher, distributor, etc. |
Packt Publishing, |
| Date of publication, distribution, etc. |
c2021 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
VIII, 462 p. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Includes Index |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
SUMMARY:<br/>Data analysis enables you to generate value from small and big data by discovering new patterns and trends, and Python is one of the most popular tools for analyzing a wide variety of data. With this book, you'll get up and running using Python for data analysis by exploring the different phases and methodologies used in data analysis and learning how to use modern libraries from the Python ecosystem to create efficient data pipelines.<br/><br/>Starting with the essential statistical and data analysis fundamentals using Python, you'll perform complex data analysis and modeling, data manipulation, data cleaning, and data visualization using easy-to-follow examples. You'll then understand how to conduct time series analysis and signal processing using ARMA models. As you advance, you'll get to grips with smart processing and data analytics using machine learning algorithms such as regression, classification, Principal Component Analysis (PCA), and clustering. In the concluding chapters, you'll work on real-world examples to analyze textual and image data using natural language processing (NLP) and image analytics techniques, respectively. Finally, the book will demonstrate parallel computing using Dask.<br/><br/>By the end of this data analysis book, you'll be equipped with the skills you need to prepare data for analysis and create meaningful data visualizations for forecasting values from data.<br/>What you will learn<br/><br/> Explore data science and its various process models<br/> Perform data manipulation using NumPy and pandas for aggregating, cleaning, and handling missing values<br/> Create interactive visualizations using Matplotlib, Seaborn, and Bokeh<br/> Retrieve, process, and store data in a wide range of formats<br/> Understand data preprocessing and feature engineering using pandas and scikit-learn<br/> Perform time series analysis and signal processing using sunspot cycle data<br/> Analyze textual data and image data to perform advanced analysis<br/> Get up to speed with parallel computing using Dask<br/><br/>Who this book is for<br/><br/>This book is for data analysts, business analysts, statisticians, and data scientists looking to learn how to use Python for data analysis. Students and academic faculties will also find this book useful for learning and teaching Python data analysis using a hands-on approach. A basic understanding of math and working knowledge of the Python programming language will help you get started with this book. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Electronic Data Processing |
| 9 (RLIN) |
721 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| 9 (RLIN) |
1561 |
| Topical term or geographic name entry element |
Python Computer Program Language |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Information Visualization |
| 9 (RLIN) |
2373 |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| Relator term |
author |
| Personal name |
Fandango, Armando |
| 9 (RLIN) |
649872 |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| Relator term |
author |
| Personal name |
Idris, Ivan |
| 9 (RLIN) |
209654 |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
|---|
| Link text |
TOC |
| Uniform Resource Identifier |
<a href="https://eaklibrary.neduet.edu.pk:8443/catalog/bk/books/toc/9781789955248.pdf">https://eaklibrary.neduet.edu.pk:8443/catalog/bk/books/toc/9781789955248.pdf</a> |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
|---|
| Link text |
WEB LINKS |
| Uniform Resource Identifier |
<a href="https://www.packtpub.com/product/python-data-analysis-third-edition/9781789955248">https://www.packtpub.com/product/python-data-analysis-third-edition/9781789955248</a> |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Book |
