Calendar Heatmap of Online Retail Sales

Introduction

• Online retail sales show important business trends
  
• Understanding these trends helps in decision making
  
• This project visualizes sales using a calendar heatmap

Objective

• To analyze online retail sales over one year
  
• To convert monthly data into daily data
  
• To visualize patterns using a calendar heatmap

Data Source

• Data based on reports from Digital Commerce 360
  
• Monthly online retail sales data
  
• Values compiled and approximated from available trends

Data Loading

• Dataset stored as a CSV file
  
• Loaded into R using read.csv()
  
• Data contains:
  • Month
    
  • Sales values

Data Cleaning

• Month values were in text format
  
• Converted into date format using R
  
• Ensured data is suitable for analysis

Data Transformation

• Monthly data converted into daily data
  
• Sales distributed evenly across days
  
• Created dataset suitable for calendar visualization

Feature Engineering

• Extracted:
  • Day of week
    
  • Week number
    
• These features help structure the heatmap

Visualization

The calendar heatmap is used to visualize daily online sales. Each tile represents a day, and color intensity indicates the sales value. Darker colors represent higher sales, while lighter colors represent lower sales.