Free sample CSV data
Download clean, fictional tracking datasets with ordinary variation, planned gaps, and documented columns. Open them in a spreadsheet or test two numeric columns in the private Analytics Sandbox.
Track your whole day
Food, sleep, movement, spending, notes, habits, and memories stay connected in one personal record.
Explore Kiomora21 fictional rows
Sleep, energy, mood, steps, screen time, focus time, and water. Includes one missing sleep value for realistic cleanup practice.
sleep_hoursenergy_1_5mood_1_5stepsscreen_time_minutesfocus_minuteswater_ml28 fictional rows
Planned days, completion, energy, and difficulty. Unplanned days intentionally leave completion and difficulty blank.
planned_dayhabit_completedenergy_1_5difficulty_1_521 fictional rows
Sleep duration, restfulness, caffeine amount, last caffeine hour, and screen time before bed. Values are fictional and non-medical.
sleep_hoursrestfulness_1_5caffeine_mglast_caffeine_hourscreen_time_before_bed_minutesThese files are made-up examples for learning calculations and data cleanup. A relationship between two columns does not show that one caused the other.
Missing values are intentional. Decide whether to exclude an incomplete row rather than silently replacing it with zero.
Open the Personal Analytics SandboxCompare sleep_hours with energy_1_5. Then inspect the dates instead of treating the coefficient as an explanation.
Compare screen_time_minutes with focus_minutes. Look for unusual days and missing context before changing a routine.
Filter to planned days, then compare difficulty with completion. A binary completion value can be numeric, but the small sample still limits interpretation.