Matplotlib & Visualisation · Lesson 145

Mini Lab Build an EDA Figure

This mini lab combines distribution and relationship views in one deliberately designed figure so each subplot answers a different exploratory question.

ConceptWorked examplePracticeKnowledge check
Textbook walkthrough

Mini Lab Build an EDA Figure

This mini lab combines distribution and relationship views in one deliberately designed figure so each subplot answers a different exploratory question.

Learning goal: explain why Mini Lab Build an EDA Figure behaves this way, apply it to a small example, and verify the result independently. Begin by being able to justify this first step: State the small task and expected result before coding.

Deeper walkthrough

Read Mini Lab Build an EDA Figure as a mechanism, not a recipe

Treat this as a sequence of observable decisions rather than one opaque command. Stage 1: State the small task and expected result before coding. Stage 2: Use the concepts from this module rather than introducing unnecessary new machinery. Stage 3: Inspect intermediate values on the tiny example. Final checkpoint: Explain why the final result follows from the code.

Mechanism

Follow the transformation

State the small task and expected result before coding.

Use the concepts from this module rather than introducing unnecessary new machinery.

Inspect intermediate values on the tiny example.

Evidence

Know what would convince you

  • Trace a tiny input by hand and compare the runtime result.
  • Inspect type, value/shape and any mutation/side effect explicitly.
Useful distinctionInput: Objects/values supplied to the operation.
Click a stage to inspect what happens, what changes, and what should be checked before moving on.
Stage 1

State the small task and expected…

State the small task and expected result before coding. For Mini Lab Build an EDA Figure, identify the exact state before this stage, the operation or rule applied here, and the observable state afterwards so the mechanism remains inspectable.

State focus: identify exactly what changed at this stage and what observable evidence confirms that change.
How it works

Trace the mechanism step by step

  1. State the small task and expected result before coding.
  2. Use the concepts from this module rather than introducing unnecessary new machinery.
  3. Inspect intermediate values on the tiny example.
  4. Check at least one edge case.
  5. Explain why the final result follows from the code.
Worked demonstration

Mini Lab Build an EDA Figure

# Step 1 — Import the module so its functions/classes are available to the rest of this example.
import matplotlib.pyplot as plt
# Step 2 — Encode the selected variables into a visual layer that can be inspected for pattern and anomalies.
fig, ax = plt.subplots(1, 2, figsize=(7,3))
# Step 3 — Execute this statement and inspect how it changes the current value, object or program state.
ax[0].hist([1,2,2,3,5])
# Step 4 — Execute this statement and inspect how it changes the current value, object or program state.
ax[0].set_title("Distribution")
# Step 5 — Execute this statement and inspect how it changes the current value, object or program state.
ax[1].scatter([1,2,3],[2,4,5])
# Step 6 — Execute this statement and inspect how it changes the current value, object or program state.
ax[1].set_title("Relationship")
# Step 7 — Encode the selected variables into a visual layer that can be inspected for pattern and anomalies.
plt.tight_layout()
Expected / illustrative result
The first axis shows shape/frequency; the second shows a two-variable relationship.
Interpret the result.

For Mini Lab Build an EDA Figure, connect every important mark, axis position or summary to its source values; check how scale, ordering, aggregation or binning affects what a reader sees.

Distinctions & related ideas

Place the concept correctly

InputObjects/values supplied to the operation.
StateNames or mutable objects that may change during execution.
OutputReturned value, side effect, file, plot or exception to inspect.
Use deliberately

When it is appropriate

Use Mini Lab Build an EDA Figure when it answers a defined question in Matplotlib & Visualisation and its inputs/assumptions match the current data or program state.

Boundary conditions

When to stop or reconsider

Reconsider Mini Lab Build an EDA Figure when the required information is unavailable, the operation would violate a validation/data boundary, or a simpler operation answers the question more transparently.

Common mistakes

Failure modes to recognise

  • Running the operation on the wrong object/type or in the wrong environment.
  • Inferring correctness from “no exception” without checking the produced value/state.
  • Hiding a boundary case instead of making its behaviour explicit.
Verification

How to check the result

  • Trace a tiny input by hand and compare the runtime result.
  • Inspect type, value/shape and any mutation/side effect explicitly.
  • Run an edge or invalid case and confirm the exception/behaviour is deliberate.
Hands-on practice

Demonstrate understanding

Try this:

Construct a tiny example of Mini Lab Build an EDA Figure. First state the small task and expected result before coding. Then use the concepts from this module rather than introducing unnecessary new machinery. Predict the result before execution and explain one boundary or failure case.

Use a handful of values and label axes/units. Point to each mark and identify the source value or aggregation that created it.
Knowledge check

Check reasoning, not memorisation

Which approach best demonstrates understanding of Mini Lab Build an EDA Figure?

Quick reference

Remember the logic

Step 1State the small task and expected result before coding.
Step 2Use the concepts from this module rather than introducing unnecessary new machinery.
Step 3Inspect intermediate values on the tiny example.
Step 4Check at least one edge case.
Lesson summary

What to remember

  • This mini lab combines distribution and relationship views in one deliberately designed figure so each subplot answers a different exploratory question.
  • State the small task and expected result before coding.
  • Running the operation on the wrong object/type or in the wrong environment.
  • Trace a tiny input by hand and compare the runtime result.