Personal Analytics Tool

This Personal Analytics Tool captures and analyzes user interactions over time. It collects data on keyboard and mouse activity, idle time, and email communications, storing it in an SQLite database. Multiple visualization features provide insights into digital habits.

Data Collected

• Keylogging Data: Keystrokes, key hold duration, keypress frequency
• Mouse Activity: Clicks, paths, scroll events
• Idle Time: Inactivity periods
• Email Metadata: Date, subject, sender/recipient, body, size

Visualization Features

• Keylogging: Keystrokes per hour, key hold duration, heatmap
• Mouse: Click distribution, click heatmap, path visualization, scroll analysis
• Idle Time: Distribution
• Email: Volume over time, top senders/recipients, subject word cloud, response times, sentiment analysis, topics over time, interaction network, length distribution, emails by time of day, common subjects, size distribution

Tech Stack

• Python 3.x
• SQLite3
• pandas, numpy, matplotlib, seaborn
• nltk, textblob
• wordcloud
• pynput, psutil
• python-dotenv

Handling sensitive data responsibly and ethically. Ensuring the tool runs efficiently in the background without impacting system performance. Designing visualizations that are both informative and easy to understand.

Gained experience in data collection, storage, and analysis using Python and relevant libraries. Learned about data visualization techniques and best practices. Improved understanding of ethical considerations related to data privacy.