Compare your life to the world.
Bring your own data, pull in public data like weather, markets, crypto, sports, health, or economics, make a thumbs-up / thumbs-down prediction, then reveal whether the pattern is real, random, strong, weak, positive, or negative.
Start here: choose what you want to do
This app has a lot of power, so the home page keeps it simple. Pick one path and the app will guide you to the right tab.
What do you want to test?
Use this like a playful “Are these connected?” lab. You can test your own life data, compare it to public data, or just explore examples first.
Try it fast
Load a ready-made demo and see a correlation result right away.
Use my data
Upload a CSV or paste spreadsheet data from your life, class, team, or project.
Compare public data
Match your data to weather, stocks, crypto, sports, or world indicators.
Learn first
Use short explanations and resources to understand r, outliers, and causation.
Make a prediction before the graph
Good data exploration starts with a guess. Pick a relationship, decide whether you think it will correlate, then reveal the result.
The app flow
The same flow works for simple classroom demos and advanced public-data comparisons.
Step 1: load or paste your data
Keep it simple: one row per day, student, game, week, or year. Use a Date or Year column if you want to match public data.
Add your personal data
Your data stays in this browser. Use a date column if you want to compare it to weather, market, sports, or other time-based public data.
Try a starter data set
These are designed to make the public-data comparison feel fun right away.
Current data preview
No data loaded yet.
No data yet
Upload, paste, or load a demo data set.
Public Data Lab: compare your data to the outside world
Make a guess first, select your matching column, choose a public source, then reveal whether the relationship is real, weak, surprising, or random.
Use My Data first if needed.
Thumbs up/down and direction.
Weather, markets, sports, or world data.
Matched data + correlation story.
Choose your comparison
Pick your own variable, select the public category, and let the app match rows by date or year.
I expect a relationship.
I expect little/no pattern.
They rise together.
One rises as the other falls.
Choose a public data category
Live connectors use free/public endpoints when possible. If a service blocks browser requests or rate-limits, the app explains what happened instead of crashing.
Connector settings
Choose a category above.
Public match result
No public comparison run yet.
Reveal Interpretation
The app will explain whether your prediction matched the data.
Joined rows preview
These are the rows actually used for the public comparison.
No joined rows yet
Run a public data comparison.
Results: graph first, meaning second
Choose two numeric columns, run the analysis, then use the explanation cards to understand the direction, strength, outliers, and trust score.
Load data first
Add data or run a public data comparison.
Optional tools: test randomness and data quality
Use these after you have a result. They help users decide whether the pattern is trustworthy or just noise.
Random Lab
Shuffle one variable to see whether the original relationship is stronger than random pairings.
Meaning Shuffle explanation
The shuffle test breaks the original pairings. If the real correlation is much stronger than shuffled results, the pattern may be more meaningful.
Data health
A quick quality scan before you trust the story.
Recommendation Next best move
Load data to see a recommendation.
Story builder
Ready-to-use language for students, teachers, or a quick presentation.
Claim
Analyze data to generate a claim.
Evidence
The app will use the correlation, direction, strength, and row count.
Caution
Correlation shows a relationship, not cause and effect.
Matrix: find relationships automatically
Use this when your data has many numeric columns and you want the app to surface the strongest positive and negative relationships.
Correlation matrix
Compare every numeric column at once and automatically surface the strongest relationships.
Strongest positive Best upward pattern
Build a matrix to find it.
Strongest negative Best downward pattern
Build a matrix to find it.
No matrix yet
Load data and click Build matrix.
Learn while you explore
Short explanations and curated links make the app easier for students, teachers, and first-time data explorers.
Understand correlation
Built-in mini-guide plus curated resources for students, teachers, and public-data exploration.
Direction Positive or negative
Positive means the variables tend to rise together. Negative means one tends to fall as the other rises.
Strength Weak to strong
The closer r is to 1 or -1, the stronger the straight-line relationship. Values near 0 show little or no linear pattern.
Caution Not causation
A strong correlation can be a clue, but it does not prove that one thing caused the other.
Resource library
Teacher-friendly links for scatter plots, correlation coefficients, public data, graphing, and deeper statistics learning.
Khan Academy: Scatterplots + correlation review
Clear article for students and teachers explaining scatter plots, association, and correlation language.
Khan Academy: Correlation coefficient intuition
Practice matching r-values to scatterplots to build visual intuition.
StatQuest video index
Friendly statistics videos for deeper learning, including correlation, regression, and data science foundations.
Open-Meteo Historical Weather API
Weather data connector used for daily temperature, precipitation, wind, and sunlight variables.
CoinGecko Market Chart API
Crypto price, market-cap, and volume time series.
World Bank API
Annual public indicators such as GDP, life expectancy, population, and CO₂.
Export center: turn the analysis into a finished report
Save the project, print to PDF, copy the explanation, or download the data for sharing.
Export center
Save, print, copy, or download your analysis. Browser print can save as PDF.
Saved projects
Saved in this browser using local storage.
Report preview
This is the report text that will be copied or downloaded.