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Multivariate Crops Data Analysis In Python

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Product details
ISBN: 9789372197983
ISBN 10: 937219798X
Book Title: MULTIVARIATE CROPS DATA ANALYSIS IN PYTHON
Authored/Edited/Compiled By: Prity Kumari, Radhika Ghetiya & Praful Sondarava
Series Name: N/A
Volume: N/A
Language: English
Imprint: NIPA
Year: 2026
Binding: Hardback
Pages: 316
Date of Publication: 46039
Subject: New Releases , Complete Price List, Hardback , Agricultural Biotechnology And Crop Improvement , Agricultural Mathematics And Statistics, Agricultural Sciences , Plant Breeding And Genetics, Computer Science And IT, Data Science And Artificial Intelligence , Engineering
Description provided by Nipa Genx Electronic Resources & Solutions.

Multivariate Crops Data Analysis in Python

Hardback

English

316

9789372197983

937219798X

NIPA

2026

1

Agricultural Mathematics and Statistics, Data Science, Agricultural Biotechnology, Plant Breeding

Specifications
Book Title
MULTIVARIATE CROPS DATA ANALYSIS IN PYTHON
ISBN
9789372197983
ISBN 10
937219798X
Author/Editor/Compiled By
Prity Kumari, Radhika Ghetiya & Praful Sondarava
Language
English
Imprint
NIPA
Publication Year
2026
Binding
Hardback
Pages
316
Subject
New Releases, Complete Price List, Hardback, Agricultural Biotechnology And Crop Improvement, Agricultural Mathematics And Statistics, Agricultural Sciences, Plant Breeding And Genetics, Computer Science And IT, Data Science And Artificial Intelligence, Engineering
Series Name
N/A
Volume
N/A
Minimum Order Quantity
1
Store Name
NIPA GENX ELECTRONIC RESOURCES & SOLUTIONS
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Agricultural Statistics Books
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Product
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India
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Frequently asked by buyers
What statistical methods are covered in this book?

The book covers multivariate distributions, Hotelling T2, MANOVA, principal component analysis (PCA), factor analysis, cluster analysis, and discriminant analysis.

Is Python used throughout the book for practical work?

Yes, each chapter includes Python code to support hands-on learning and application to crop experimental data.

What type of datasets are used in the examples?

The examples use real agricultural experimental datasets, so the content is directly relevant to crop data analysis.

Who is this book suitable for?

It is suitable for students, researchers, and agricultural professionals working with multivariate crop data and statistical analysis.

What is the binding and page count?

This edition is hardback and contains 316 pages.

What are the ISBN details?

The book ISBN is 9789372197983 and the ISBN 10 is 937219798X.

Can the Python code be adapted for other research datasets?

Yes, the code snippets are described as fully customizable, allowing readers to adapt them to their own research needs.

What is the minimum order quantity for bulk procurement?

The minimum order quantity is 1, which supports both individual and institutional procurement.

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Multivariate Crops Data Analysis In Python
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