Bike Sales Data Analysis and Dashboard

Project Overview

This project involves the analysis of a bike sales dataset. The dataset includes information about individuals such as gender, marital status, age, salary, and the distance they commute to work. The main goal of this project was to clean and preprocess the data, create meaningful categorizations, perform data analysis, and visualize the results in an interactive dashboard.

Data Preprocessing and Transformation

1. Gender Conversion:

   • Transformed gender representation from single characters (m, f) to full terms (Married, Single).

2. Age Classification:

   • Categorized ages into three distinct groups:
     • Young: Less than 30 years old
     • Adult: Between 30 and 55 years old
     • Old: Greater than 55 years old

3. Marital Status Standardization:

   • Ensured that the marital status column only contained the values Married and Single.

Data Analysis

1. Pivot Tables:

   • Created pivot tables to summarize the data and derive insights based on different categories such as gender, age group, and marital status.

2. Data Visualization:

   • Visualized the data using charts and graphs to highlight key trends and patterns.

Dashboard Creation

1. Interactive Dashboard:

   • Built an interactive dashboard to present the data and visualizations.
   • Included filters to allow users to dynamically adjust the view based on:
     • Marital status (Married, Single, or both)
     • Residential region (Europe, North America)

2. Dashboard Features:

   • Users can filter the data to see information specific to married individuals, single individuals, or both.
   • Users can also filter the data based on the region to compare bike sales in Europe versus North America.
   • The dashboard provides a comprehensive view of the dataset with easy-to-use controls for an enhanced user experience.

Conclusion

This project demonstrates the end-to-end process of data analysis, from cleaning and preprocessing raw data to creating an interactive dashboard for visualization. The dashboard provides valuable insights into bike sales trends based on gender, age, marital status, and region, making it a powerful tool for data-driven decision-making.