Quick Reference¶

Essential commands, tasks, and troubleshooting for daily use of your Fitness Dashboard.

🚀 Getting Started (First Time)¶

Setup Commands¶

# 1. Initialize database
python scripts/init.py

# 2. Import your data
python src/update_db.py

# 3. Start dashboard
streamlit run src/streamlit_app.py

First Steps¶

Visit: http://localhost:8501
Import data: Replace src/user2632022_workout_history.csv with your export
Check insights: Look for focus area suggestions and trends

📊 Common Tasks¶

Data Management¶

Task	How To
Import new workouts	Replace CSV file → Run `python src/update_db.py`
Fix wrong categories	Model Management page → Find workout → Correct → Retrain
Check data quality	Custom Queries → Look for outliers (pace >60 or <4 min/mile)
Export results	Copy query results → Paste into spreadsheet

Analysis Tasks¶

Task	Where To Go
See recent trends	Main dashboard → Trending card
Compare time periods	Trends page → Date range picker
Find best workouts	Custom Queries → ORDER BY avg_pace_min_mi LIMIT 10
View monthly stats	Monthly View tab
Get recommendations	Main dashboard → Focus Area card

Troubleshooting¶

Problem	Quick Fix
No data showing	Check if you ran `python src/update_db.py`
Classifications wrong	Model Management → Correct examples → Retrain
Dashboard won't start	Check MySQL is running → Verify `poetry install` worked
Import errors	Check CSV file path → Look for missing columns

🔧 Useful SQL Queries¶

Copy these into the Custom Queries page:

Find Your Best Runs¶

SELECT workout_date, distance_mi, avg_pace_min_mi, kcal_burned
FROM workout_summary
WHERE activity_type = 'real_run'
ORDER BY avg_pace_min_mi
LIMIT 10;

Monthly Activity Summary¶

SELECT
    DATE_FORMAT(workout_date, '%Y-%m') as month,
    COUNT(*) as total_workouts,
    SUM(distance_mi) as total_miles,
    AVG(avg_pace_min_mi) as avg_pace
FROM workout_summary
GROUP BY DATE_FORMAT(workout_date, '%Y-%m')
ORDER BY month DESC;

Data Quality Check¶

SELECT * FROM workout_summary
WHERE avg_pace_min_mi > 60 OR avg_pace_min_mi < 4
   OR distance_mi > 50 OR distance_mi < 0.1
ORDER BY workout_date DESC;

Activity Type Breakdown¶

SELECT
    activity_type,
    COUNT(*) as count,
    AVG(distance_mi) as avg_distance,
    AVG(kcal_burned) as avg_calories
FROM workout_summary
GROUP BY activity_type
ORDER BY count DESC;

🎯 Understanding Your Results¶

Focus Area Meanings¶

Building Consistency: Workout irregularly → Establish routine
Adding Frequency: Consistent but infrequent → Work out more often
Optimizing Performance: Already consistent → Focus on improvement

Workout Categories¶

Real Runs: 8-12 min/mile pace, focused running
Walking: 20-28 min/mile pace, leisure activity
Mixed: Variable pace, intervals or run/walk combo
Outlier: Unusual data, check for errors

Confidence Scores¶

85-100%: High confidence, trust the result
70-84%: Medium confidence, review if seems wrong
Below 70%: Low confidence, likely needs correction

⚡ Quick Fixes¶

Dashboard Issues¶

# Dashboard won't start
lsof -ti:8501 | xargs kill  # Kill existing process
streamlit run src/streamlit_app.py

# Database connection errors
brew services restart mysql  # macOS
sudo systemctl restart mysql  # Linux

# Import not working
ls -la src/user2632022_workout_history.csv  # Check file exists
head src/user2632022_workout_history.csv    # Check format

Model Issues¶

Go to Model Management page
Check accuracy - if <70%, needs retraining
Review recent classifications - correct obvious mistakes
Click "Retrain Model" after corrections

Data Issues¶

Run data quality SQL (see above)
Fix obvious errors in your CSV file
Re-import: python src/update_db.py
Refresh dashboard to see changes

📝 Regular Maintenance¶

Weekly¶

Export new data from fitness app
Run python src/update_db.py
Check Model Management accuracy

Monthly¶

Review and correct any wrong classifications
Retrain model if accuracy drops
Export analysis for personal records

As Needed¶

Clean up obvious data errors
Update date ranges for seasonal analysis
Backup your database

🆘 When to Get Help¶

Check Documentation First: - Common Tasks - Step-by-step guides - Dashboard Overview - Interface explanations - Troubleshooting - Detailed problem-solving

Still Stuck? - Submit issue on GitHub - Include error messages and what you were trying to do - Mention your operating system and Python version

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