Tutorials · Chapter D (4/4) · ~9 min

Data: tables and simple plots

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Read a tiny table, compute stats, and show a plot you can screenshot.

Code Lab

Data: tables & simple stats

Run the average, then print the top student name.

Python

# Tiny data table (list of dicts)
rows = [
  {"name": "Ada", "score": 88},
  {"name": "Lin", "score": 92},
  {"name": "Sam", "score": 79},
]

# Average score
avg = sum(r["score"] for r in rows) / len(rows)
print("average", round(avg, 1))

# Challenge: print the student with the highest score

Recap

What you just did

You loaded a small dataset, asked it plain questions (average? extreme?), and drew a simple plot. That’s the builder habit: look first, model second. You can open the result and say, “Here’s the table I measured — and the picture of it.”

Teach

How it works

Think of a table as rows of examples:

# each row: [feature, label]
rows = [[2, 0], [5, 1], [3, 0], [8, 1]]
xs = [r[0] for r in rows]
print("mean x:", sum(xs) / len(xs))
print("max x:", max(xs))

Table → columns you can name (feature, label)
Stat → one number that summarizes a column
Plot → a shape your eyes catch faster than a list

Mental model: stats answer “what’s typical?”; plots answer “what’s weird?”

Use it

When you'd use this

Checking a CSV before you trust a prediction
Spotting one giant outlier that would trick a model
Showing a teammate “the data looks like this” instead of guessing

Watch out

A pretty chart can still lie if the wrong column is plotted. Always match the axis label to the question you’re answering. Empty rows and missing values will break averages — glance at the raw rows once.

Try next

Try this next

Compute the min of your feature column the same way you did the max. Does the plot make that min obvious?