Min, Max, and Quartiles
Reading the range and percentiles.
Min, Max, and Quartiles is a free Data Science Academy lesson on CoddyKit — lesson 3 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the Data Science Academy learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
The Edges of Your Data
Center and spread leave out the extremes. Knowing the smallest and largest values frames the range your data can possibly take. 🔭
Min and Max
The min is the lowest value and the max is the highest. They are your first guard against typos like a negative age or an impossible price.
df["age"].min(), df["age"].max()The Range
Subtract min from max and you get the range, the total width of your data. It is simple but easily wrecked by a single extreme value.
Splitting Sorted Data
Sort your values and cut them into four equal parts. The three cut points are your quartiles, and they describe the data far more robustly.
Q1, the First Quartile
The first quartile Q1 is the 25th percentile. One quarter of your values fall below it, marking the bottom of the bulk.
Q2 Is the Median
The second quartile Q2 is the 50th percentile, which is exactly the median you already met. Half the data sits on each side of it.
Q3, the Third Quartile
The third quartile Q3 is the 75th percentile. Three quarters of values fall below it, so only the top slice lies above.
Asking for a Percentile
The quantile method gives you any cut point you want. Pass 0.25 for Q1 or 0.75 for Q3 directly on a column.
df["score"].quantile(0.75)The Interquartile Range
Subtract Q1 from Q3 and you have the IQR, the spread of the middle half. It ignores the extremes, so outliers cannot inflate it.
The Five-Number Summary
Min, Q1, median, Q3, and max form the five-number summary. Together they sketch the full shape of a distribution in just five values.
Already in describe
You do not compute quartiles by hand. The describe output lists the 25, 50, and 75 percent rows for every numeric column.
df.describe()Quick Check
You want a spread measure that ignores extreme values entirely.
Recap: Range and Quartiles
You can now read the edges with min and max and the inner structure with quartiles and IQR. Five numbers describe a whole distribution. 📊
Frequently asked questions
Is the “Min, Max, and Quartiles” lesson free?
Yes — the full text of “Min, Max, and Quartiles” is free to read here on the web, and the Data Science Academy course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the Data Science Academy course, upgrade to CoddyKit PRO.
What will I learn in “Min, Max, and Quartiles”?
Reading the range and percentiles. You practise Data Science Academy with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start Data Science Academy?
No prior experience is required. Data Science Academy on CoddyKit is structured for beginners through advanced learners; this is — lesson 3 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “Min, Max, and Quartiles” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this Data Science Academy lesson?
Yes. Every Data Science Academy lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
All lessons in this course
- Mean, Median, and Mode
- Spread: Variance and Std Dev
- Min, Max, and Quartiles
- Outliers and What They Mean