Fitness Activity Dashboard

Exploring daily activity patterns from fitness tracker data

This interactive dashboard allows you to explore daily physical activity, compare individuals, and investigate how steps, distance, activity intensity, and sedentary behaviour relate to calories burned.

Project Aim

The aim of this dashboard is to help you understand patterns in fitness data through visualisations.

The app focuses on activity trends, calorie relationships, and user-level differences in behaviour.

Target Audience

This dashboard is designed for users interested in fitness, health behaviour, and data-driven activity tracking.

It does not require technical knowledge and is intended to be easy to explore.

What Can You Explore?

  • Overall activity levels across the dataset
  • Daily and weekly activity trends
  • Relationships between steps, distance, active minutes, and calories
  • Differences between individual users
  • User groups created using K-means clustering

Dataset Summary

  • Daily activity records from wearable fitness trackers
  • Includes steps, distance, activity minutes, sedentary minutes, and calories
  • Covers multiple anonymised users
  • Cleaned by combining CSV files, removing duplicates, and creating new features

How to Use the Dashboard

1. Start with Overview

View headline statistics and overall activity patterns.

2. Explore Trends

Filter by user, date range, and activity metric.

3. Analyse Calories

Investigate which activity variables relate most strongly to calories.

4. Compare Users

Use clustering to identify broad user activity profiles.

Important Data Note

Some records contain zero steps or zero distance. These values were kept because they may represent inactive days, rest days, or missing tracking periods. Derived metrics such as calories per step were only calculated where division was valid.

The data is anonymised and does not include demographic information. Therefore, the dashboard focuses on recorded activity patterns rather than making fitness claims about individuals.

Overview of the Dataset

Overall, users averaged ~7200 steps and ~2200 calories a day. Sedentary minutes make up the largest part of the recorded day.

Number of users

Number of daily records

Average daily steps

Average daily calories

Average Daily Steps Over Time

Average Daily Minutes by Activity Type

Activity Trends

Saturday had the highest average steps (weekend, more free time for exercise), whilst Sunday had the lowest (generally considered a 'rest day').

Selected Metric Over Time

Average Steps by Weekday

Calories & Relationships

Calories are most strongly related to total distance, total steps, and very active minutes. Sedentary minutes show very little relationship with calories.

Relationship with Calories

Correlation Heatmap

User Comparison and Clustering

The clusters suggest three general user types: lower activity users, moderate activity users, and high activity or high calorie users.

User Clusters

Cluster Averages

User Summary Table