Python for Marketing Research and Analytics

by Jason Schwarz, Chris Chapman, and Elea McDonnell Feit

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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. 

  • ISBN13 9783030497194
  • Publish Date 3 November 2020
  • Publish Status Active
  • Publish Country CH
  • Imprint Springer Nature Switzerland AG
  • Edition 1st ed. 2020
  • Format Hardcover
  • Pages 272
  • Language English