Site

http://archive.ics.uci.edu/ml/datasets/clickstream+data+for+online+shopping

Attributes (Sections highlighted in red are too vague to be useful.)

• Year — all 2008
• Month — from April (4) to August (8)
• Day
• Order — sequence of clicks during a session
• Country
• Session ID
• Page 1 — concerns the main product category
  • 1 = Trousers
  • 2 = Skirts
  • 3 = Blouses
  • 4 = Sale
• Page 2 — contains info about the code for each product (217 in total)
• Color — color of product
• Location — photo location on the page (screen has been divided into 6 parts)
  • 1 = top left
  • 2 = top in the middle
  • 3 = top right
  • 4 = bottom left
  • 5 = bottom in the middle
  • 6 = bottom right
• Model Photography
  • 1= en face
  • 2 = profile
• Price — in US dollars
• Price 2 — Is the price of a particular product higher than the average price for the entire product category
  • 1 = Yes
  • 2 = No
• Page — page within the e-store website (1 to 5)For each country,

• Data Analysis Techniques

  Listing

  • https://careerfoundry.com/en/blog/data-analytics/data-analysis-techniques/

  Regression

  • https://statisticsbyjim.com/regression/choosing-regression-analysis/
  • https://docs.displayr.com/wiki/Case_Study_-_Regression_-_Introduction

  Cluster

  • https://developers.google.com/machine-learning/clustering/clustering-algorithms
  • http://ucanalytics.com/blogs/customer-segmentation-cluster-analysis-telecom-case-study-example/
• This is the question that I need
• determine which is the most popular category, the most preferred color, and the average price of each product looked at. Only list the previous attributes of the top 5 countries with the highest total product prices.* for each country*
  • List
  • 
    
  • Which model photography receives the most clicks?
    • Bar Graph