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Minimalist Data Wrangling with Python

Name: Minimalist Data Wrangling with Python
Creator: Gagolewski, Marek
Keywords: FOS: Computer and information sciences, Artificial Intelligence and Image Processing, scipy, 80308 Programming Languages, data frames, Computer Software, vectors, matrices, numpy, FOS: Mathematics

descriptionPublicationkeyboard_double_arrow_right Book 16 Jul 2022 English Publisher:Zenodo

Authors: Gagolewski, Marek;

Minimalist Data Wrangling with Python

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Abstract

Minimalist Data Wrangling with Python is envisaged as a student's first introduction to data science, providing a high-level overview as well as discussing key concepts in detail. We explore methods for cleaning data gathered from different sources, transforming, selecting, and extracting features, performing exploratory data analysis and dimensionality reduction, identifying naturally occurring data clusters, modelling patterns in data, comparing data between groups, and reporting the results. This textbook is a non-profit project. Its online and PDF versions are freely available at https://datawranglingpy.gagolewski.com/. To order a paper copy, see https://datawranglingpy.gagolewski.com/order-paper-copy.html. Marek Gagolewski is an Associate Professor in Data Science at Warsaw University of Technology. His research interests are related to data science, in particular: modelling complex phenomena, developing usable, general purpose algorithms, studying their analytical properties, and finding out how people use, misuse, understand, and misunderstand methods of data analysis in research, commercial, and decision making settings. In his spare time, he writes books for his students and develops free (libre) data analysis software, such as stringi – one of the most often downloaded R packages, and genieclust – a fast and robust clustering algorithm in both Python and R. See also: Deep R Programming at https://deepr.gagolewski.com/.

Please cite this book as: Gagolewski M. (2025), Minimalist Data Wrangling with Python, Zenodo, Melbourne, DOI: 10.5281/zenodo.6451068, ISBN: 978-0-6455719-1-2, URL: https://datawranglingpy.gagolewski.com/

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Deakin University
Australia

Keywords

FOS: Computer and information sciences, Artificial Intelligence and Image Processing, scipy, 80308 Programming Languages, data frames, Computer Software, vectors, matrices, numpy, FOS: Mathematics, 80204 Mathematical Software, 80306 Open Software, 80304 Concurrent Programming, pandas, matplotlib, Data Wrangling, Data Science, Statistics, outliers, 80110 Simulation and Modelling, data cleansing, missing values, classification, Applied Computer Science, regression, scikit-learn, data science, text processing, time series, data wrangling, Python, clustering

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