Obsidian Stats

A Python-based productivity tracking system that parses daily journal entries from an Obsidian vault to generate insights, heatmaps, and trend analysis.

Features

• Data Extraction: Parses daily markdown files for specific metrics (tasks, sleep, study deficit, etc.).
• Productivity Scoring: Calculates a weighted daily productivity score with rolling averages.
• Visualizations: Generates calendar heatmaps and trend plots.
• Analysis: Detects anomalies and identifies most/least productive days/weeks.

Repository Structure

• 0_data_import.py: Extracts raw data from Obsidian markdown files into a CSV.
• 1_prod_score.py: Computes productivity scores and generates the daily score plot.
• 2_heatmap.py: Creates a calendar heatmap of productivity throughout the year.
• 3_anomalies.py: Identifies unusual productivity dips or peaks using Isolation Forest.
• 4_week_trend.py: Analyzes productivity trends across different weeks and weekdays.
• 5_correlations.py: Calculates correlations between different habits (e.g., sleep vs. productivity).
• settings.py: Centralized configuration for file paths and environment variables.
• sleep_function.py: Helper script for visualizing the sleep bonus algorithm.

Setup

1. Clone the repository.
2. Create a virtual environment and install dependencies:

   python -m venv venv
   source venv/bin/activate  # On Windows: .\venv\Scripts\activate
   pip install pandas numpy matplotlib seaborn scikit-learn

3. Configure Environment Variables: Copy .env.example to a new file named .env and update the paths to point to your Obsidian vault and preferred output locations:

   OBSIDIAN_VAULT_PATH=/path/to/your/obsidian/daily/journal
   DATA_OUTPUT_CSV=data_output.csv
   PROD_OUTPUT_CSV=prod_output.csv

Usage

Run the scripts in order to update your data and view insights:

1. python 0_data_import.py
2. python 1_prod_score.py
3. Any of the other analysis scripts (2_heatmap.py, etc.).