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Fabio Nelli - Pandas in 7 Days: Utilize Python to manipulate data, conduct scientific computing, time series analysis, and exploratory data analysis

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Fabio Nelli Pandas in 7 Days: Utilize Python to manipulate data, conduct scientific computing, time series analysis, and exploratory data analysis
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Pandas in 7 Days Utilize Python to manipulate data conduct - photo 1

Pandas in 7 Days

Utilize Python to manipulate data conduct scientific computing time series - photo 2

Utilize Python to manipulate data, conduct
scientific computing, time series analysis, and
exploratory data analysis

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Fabio Nelli
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www.bpbonline.com

FIRST EDITION 2022

Copyright BPB Publications, India

ISBN: 978-93-5551-213-0

All Rights Reserved. No part of this publication may be reproduced, distributed or transmitted in any form or by any means or stored in a database or retrieval system, without the prior written permission of the publisher with the exception to the program listings which may be entered, stored and executed in a computer system, but they can not be reproduced by the means of publication, photocopy, recording, or by any electronic and mechanical means.

LIMITS OF LIABILITY AND DISCLAIMER OF WARRANTY

The information contained in this book is true to correct and the best of authors and publishers knowledge. The author has made every effort to ensure the accuracy of these publications, but publisher cannot be held responsible for any loss or damage arising from any information in this book.

All trademarks referred to in the book are acknowledged as properties of their respective owners but BPB Publications cannot guarantee the accuracy of this information.

wwwbpbonlinecom Dedicated to All those who are constantly looking for - photo 5

www.bpbonline.com

Dedicated to

All those who are constantly looking for awareness

&

in a special way to My wife and my son

About the Author

Fabio Nellihas a Masters degree in Chemistry and a Bachelors degree in IT & Automation Engineering. He is currently working professionally at many research institutes and private companies, presenting educational courses about data analysis and data visualization technologies. He also completes his activity by writing articles on the web (in particular on his website, meccanismocomplesso.org) and in-depth books on the subject.

About the Reviewers

Purna Chander Kathulais a Data Manager and a Python Developer who guides teams working on complex Data Engineering tasks, building data pipelines, easy handling of heavy lifting jobs, legacy data ingestions, Validations, Data Analysis, and Visualizations. His expertise lies in building tools and frameworks that validates structured, semi structured, and unstructured data. He is Coursera-certified in Applied Data Science with Python from the University of Michigan. He has authored two books, Instant Sikuli Test Automation and Hands-on Data Analysis and visualization with Pandas. He lives with his family and two children, and loves watching fiction movies and spending time with family and friends in his free time.

Pragnesh Prajapatiis a Data Scientist with extensive experience in building AI products. He is currently working as a Senior Data Scientist at Cerebulb (India) Private Limited to develop predictive analytics products for industries like sugar, cement, and mining. He is also working as an Mlops Solution architect in a freelance capacity to develop Mlops solution for big data architecture.

He completed his B.E graduation in Electronics and Communication where he was exposed to IOT devices. He has taken 12+ online courses related to ML, Python, Deep learning, MLOPS, and AWS.

He started his professional journey as an Embedded Consultant in Amnex Info Technologies, primarily working on IOT devices, and later worked as a machine learning consultant in the R&D Department. He has worked on IOT, Machine Learning, and Deep Learning products.

He started mentoring and tutoring students in 2021, and worked with an Edu-tech company as a data science tutor.

In his free time, he likes to learn new technologies (for instance, quantum machine learning), listen to podcasts, and play guitar.

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