Python for Marketing Research and Analytics

Python for Marketing Research and Analytics

Author
Jason S. Schwarz, Chris Chapman, Elea McDonnell Feit
Publisher
Springer International Publishing;Springer
Language
English
Edition
1st ed.
Year
2020
Page
XI, 272
ISBN
9783030497194,9783030497200
File Type
pdf
File Size
14.4 MiB

This book provides an introduction to quantitative marketing with Python. The book presents a hands-on approach to using Python for real marketing questions, organized by key topic areas. Following the Python scientific computing movement toward reproducible research, the book presents all analyses in Colab notebooks, which integrate code, figures, tables, and annotation in a single file. The code notebooks for each chapter may be copied, adapted, and reused in one's own analyses. The book also introduces the usage of machine learning predictive models using the Python sklearn package in the context of marketing research.
This book is designed for three groups of readers: experienced marketing researchers who wish to learn to program in Python, coming from tools and languages such as R, SAS, or SPSS; analysts or students who already program in Python and wish to learn about marketing applications; and undergraduate or graduate marketing students with little or no programming background. It presumes only an introductory level of familiarity with formal statistics and contains a minimum of mathematics.

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