Marketing Data Science: Modeling Techniques in Predictive Analytics with R and Python
By Thomas W. Miller
Programs and Data to Accompany "Marketing Data Science: Modeling Techniques in Predictive Analytics with R and Python" Miller (2015)
| Book Location | Description of Directory or File | File Name |
| MDS Chapter 1 | Measuring and Modeling Individual Preferences (R) | MDS_Exhibit_1_1.R |
| Measuring and Modeling Individual Preferences (Python) | MDS_Exhibit_1_2.py | |
| "Measuring and Modeling Individual Preferences (data)" | mobile_services_ranking.csv | |
| Questions for Conjoint Survey (documentation) | questions_for_survey.txt | |
| Conjoint Analysis Spine Chart (R binary) | mtpa_spine_chart.Rdata | |
| MDS Chapter 2 | Predicting Commuter Transportation Choices (R) | MDS_Exhibit_2_1.R |
| Predicting Commuter Transportation Choices (Python) | MDS_Exhibit_2_2.py | |
| Predicting Commuter Transportation Choices (data) | sydney.csv | |
| Correlation Heat Map Utility (R binary) | correlation_heat_map.RData | |
| MDS Chapter 3 | Identifying Customer Targets (R) | MDS_Exhibit_3_1.R |
| Identifying Customer Targets (Python) | MDS_Extra_3_1.py | |
| Identifying Customer Targets (data) | bank.csv | |
| Empty Python Directory | __init__.py | |
| Evaluating Predictive Accuracy of a Binary Classifier (Python) | evaluate_classifier.py | |
| MDS Chapter 4 | Identifying Consumer Segments (R) | MDS_Exhibit_4_1.R |
| Identifying Consumer Segments (Python) | MDS_Exhibit_4_2.py | |
| Identifying Consumer Segments (data) | bank.csv | |
| MDS Chapter 5 | Predicting Customer Retention (R) | MDS_Exhibit_5_1.R |
| Predicting Customer Retention (Python) | MDS_Extra_5_1.py | |
| Predicting Customer Retention (data) | att.csv | |
| Empty Python Directory | __init__.py | |
| Evaluating Predictive Accuracy of a Binary Classifier (Python) | evaluate_classifier.py | |
| MDS Chapter 6 | Product Positioning of Movies (R) | MDS_Exhibit_6_1.R |
| Product Positioning of Movies (Python) | MDS_Exhibit_6_2.py | |
| Multidimensional Scaling Demonstration: US Cities (R) | MDS_Exhibit_6_3.R | |
| Multidimensional Scaling Demonstration: US Cities (Python) | MDS_Exhibit_6_4.py | |
| Using Activities Market Baskets for Product Positioning (R) | MDS_Exhibit_6_5.R | |
| Using Activities Market Baskets for Product Positioning (Python) | MDS_Exhibit_6_6.py | |
| Hierarchical Clustering of Activities (R) | MDS_Exhibit_6_7.R | |
| Hierarchical Clustering of Activities (Python) | MDS_Extra_6_7.py | |
| Hierarchical Clustering of Activities (data) | wisconsin_dells.csv | |
| MDS Chapter 7 | Analysis for a Field Test of Laundry Soaps (R) | MDS_Exhibit_7_1.R |
| Analysis for a Field Test of Laundry Soaps (Python) | MDS_Extra_7_1.py | |
| Analysis for a Field Test of Laundry Soaps (grouped data) | gsoaps.csv | |
| Analysis for a Field Test of Laundry Soaps (individual data) | soaps.csv | |
| MDS Chapter 8 | Shaking Our Bobbleheads Yes and No (R) | MDS_Exhibit_8_1.R |
| Shaking Our Bobbleheads Yes and No (Python) | MDS_Exhibit_8_2.py | |
| Shaking Our Bobbleheads Yes and No (data) | dodgers.csv | |
| MDS Chapter 9 | Market Basket Analysis of Grocery Store Data (R) | MDS_Exhibit_9_1.R |
| Market Basket Analysis of Grocery Store Data (Python to R) | MDS_Exhibit_9_2.py | |
| MDS Chapter 10 | Training and Testing a Hierarchical Bayes Model (R) | MDS_Exhibit_10_1.R |
| Analyzing Consumer Preferences and Building a Market Simulation (R) | MDS_Exhibit_10_2.R | |
| Training and Testing a Hierarchical Bayes Model (data) | computer_choice_study.csv | |
| Market Simulation Utilities (R binary) | mtpa_market_simulation_utilities.Rdata | |
| Split-plotting Utilities (R binary) | mtpa_split_plotting_utilities.Rdata | |
| MDS Chapter 11 | Network Models and Measures (R) | MDS_Exhibit_11_1.R |
| Analysis of Agent-Based Simulation (R) | MDS_Exhibit_11_2.R | |
| Defining and Visualizing a Small-World Network (Python) | MDS_Exhibit_11_3.py | |
| Analysis of Agent-Based Simulation (Python) | MDS_Exhibit_11_4.py | |
| Analysis of Agent-Based Simulation (data trials) | NetLogo_results | |
| Analysis of Agent-Based Simulation (summary data) | virus_results.csv | |
| MDS Chapter 12 | Competitive Intelligence: Spirit Airlines Financial Dossier (R) | MDS_Exhibit_12_1.R |
| MDS Chapter 13 | Restaurant Site Selection (R) | MDS_Exhibit_13_1.R |
| Restaurant Site Selection (Python) | MDS_Exhibit_13_2.py | |
| Restaurant Site Selection (data) | studenmunds_restaurants.csv | |
| Correlation Heat Map Utility (R binary) | correlation_heat_map.RData | |
| MDS Appendix C | AT&T Choice Study | MDS_Appendix_C_1 |
| Anonymous Microsoft Web Data | MDS_Appendix_C_2 | |
| Bank Marketing Study | MDS_Appendix_C_3 | |
| Boston Housing Study | MDS_Appendix_C_4 | |
| Computer Choice Study | MDS_Appendix_C_5 | |
| DriveTime Sedans | MDS_Appendix_C_6 | |
| Lydia E. Pinkham Medicine Company | MDS_Appendix_C_7 | |
| Procter & Gamble Laundry Soaps | MDS_Appendix_C_8 | |
| Return of the Bobbleheads | MDS_Appendix_C_9 | |
| Studenmund’s Restaurants | MDS_Appendix_C_10 | |
| Sydney Transportation Study | MDS_Appendix_C_11 | |
| ToutBay Begins Again | MDS_Appendix_C_12 | |
| Two Month’s Salary | MDS_Appendix_C_13 | |
| Wisconsin Dells | MDS_Appendix_C_14 | |
| Wikipedia Votes | MDS_Appendix_C_16 | |
| MDS Appendix D | Conjoint Analysis Spine Chart (R) | MDS_Exhibit_D1.R |
| Market Simulation Utilities (R) | MDS_Exhibit_D2.R | |
| Split-plotting Utilities (R) | MDS_Exhibit_D3.R | |
| Utilities for Spatial Data Analysis (R) | MDS_Exhibit_D4.R | |
| Correlation Heat Map Utility (R) | MDS_Exhibit_D5.R | |
| Evaluating Predictive Accuracy of a Binary Classifier (Python) | MDS_Exhibit_D6.py |
