Rung 1 — What's There
Five dives, built and ready to run. Every dataset is in data/, rebuildable with python3 fetch.py.
The entry rung. The student is looking at a thing they could go and count themselves, and the whole job of the rung is that a shape is something a person chose to impose on data — not a property the data came with.
Grammar, unchanged all four years (README.md):
Q1 the trap — the named failure mode of this shape, from the library card Q2 the finding — what does it say Q3 the turn — you in it, or your doubt about it. Never optional.
1.1 · the table — every value and no shape
| dataset | rows | |
|---|---|---|
| affects them | table_la_311_sample.csv — 311 requests, every column | 40 |
| Earth & space | table_quakes_full.csv — SoCal earthquakes, 2024 | 2,508 |
Q1. What kind of chart is this, and what is one thing it cannot show you? Q2. Read three rows out loud. What happened, where, and when? Q3. Which of these two files could you actually check by going outside?
Run the small one first and let it feel fine. Forty rows of 311 are legible — a person can read them. Then put 2,508 earthquakes on the screen and scroll.
The table fails at a size you can feel, and that is GAISE's own reason for teaching graphs at all. Nobody has to be told; they just watched it happen.
1.2 · the bar — a ranking of places, and a ranking of sizes
| dataset | shape of it | |
|---|---|---|
| affects them | bar_la_311_by_council_district.csv | 15 bars, 65,952 to 108,379 — almost flat |
| Earth & space | bar_quakes_by_magnitude_band.csv | 1,684 / 721 / 88 / 14 / 1 — falls off a cliff |
Q1. What kind of chart is this, and what is one thing it cannot show you? Q2. In each chart, how many times bigger is the first bar than the last? Q3. Council districts are places with people in them. Magnitude bands are sizes. Does the chart know the difference? Should it?
A 1.6x spread and a 1,684x spread, drawn identically. The bar does not care which it is handed, and the reader must.
A trap that is ours, not the Earth's. The M1 bar is short because the query starts at M1.5, so that band is half missing. Somebody's filter is visible in the chart — hand that to them rather than hiding it. It is the first time they see a choice made by the person who fetched the data.
1.3 · the number — a number with no comparison is not a finding
| dataset | |
|---|---|
| affects them | number_la_aqi_california_counties.csv — EPA annual AQI, all 52 CA counties, 2024 |
| Earth & space | line_co2_mauna_loa_annual.csv — Mauna Loa CO2, 1959–2025 |
Two stages, and the order is the lesson.
Stage one — one number, alone on the screen:
Los Angeles County, 2024: 78 days unhealthy for sensitive groups.
Q1. Is that a lot? Every student will answer. None of them can. Sit in it.
Stage two — the same file, everyone else:
Riverside 80. Los Angeles 78. Kern 73. And at the other end, Santa Cruz, Siskiyou and Sonoma at zero.
Q2. Now — is 78 a lot? Against zero it is enormous. Against Riverside it is ordinary. LA is third of fifty-two, not first. Did you expect that? Q3. You breathe this air. Which comparison do you want used when somebody decides whether to do something about it — and does your answer change depending on what you want the decision to be?
Run the CO2 number the same way: 427.35 ppm alone means nothing. Then show all 67 years, which rise every single year without exception.
1.4 · the picture graph — the icon is a unit, and it breaks
| dataset | rows | |
|---|---|---|
| affects them | picture_la_street_trees_by_species.csv | 20 |
| Earth & space | picture_exoplanets_by_discovery_method.csv | 11 |
Q1. One icon stands for how many? Who decided that? Q2. Which categories disappear at your chosen icon size? Q3. Walk your street. Which of these species is on it — and is there a gap where a tree should be?
Two different breaks, one shape.
The trees break at the top of the file. The largest row in Los Angeles's street tree inventory is VACANT - OK TO PLANT, at 116,720 — an empty planting site. It is not a tree. It is two and a half times the biggest species that is one (Crape Myrtle, 45,000).
Does it belong on a chart of "trees by species"? There is a real answer on both sides and the argument is the dive. Absence is data too — and here the absence is the biggest bar in the file, before anyone was asked to look for it.
The exoplanets break at the bottom. Transit has found 4,688; Disk Kinematics has found 1. At a sane icon size of 1 = 100 planets, seven of the eleven methods round to zero and vanish from the chart entirely.
A category that exists, is real, and cannot be drawn. The encoding created an absence.
1.5 · the donut — angle is read badly, and a donut cannot rank
| dataset | what it does | |
|---|---|---|
| affects them | donut_la_311_by_request_type.csv | slices too close to order |
| Earth & space | donut_quakes_by_depth_band.csv | one slice swallows the rest |
Q1. Put the slices in order, smallest to largest, without reading the numbers. Q2. Which pairs did you get wrong, and by how much? Q3. Bulky Items is 46.5% of everything Los Angeles is asked to do. Is that what you would have guessed the city spends its time on?
Both donut failure modes, side by side.
311 runs Bulky Items 46.5%, Graffiti 24.4%, then 7.9%, 7.5%, 4.5% — three slices nobody can rank by eye. Earthquakes run shallow 90.3%, intermediate 9.7%, and deep at 0.0%.
Deep earthquakes happen. There are some in the file. The donut renders them as nothing. Same lesson as the picture graph, arriving from the opposite direction.
The MAKE dive — every fifth session
They have judged five charts somebody else drew. Now they draw one.
The dataset is bar_la_311_by_council_district.csv — fifteen rows, no cleaning needed, and it is about the fifteen pieces of the city they live in.
Build it as a bar. Then build it again as a donut. Which one lets a person find their own district fastest? Which one did you enjoy more? Those are not the same question, and noticing that is the point.
Tool: Flourish, per ../../_planning/the-two-tools.md. Public data, so the rental's terms are satisfied — nothing here is collected from a student.
What rung 1 is missing
1.2 class-collected and 1.5 school day are still unbuilt, because they do not exist until a class collects them, and that is a scheduling decision rather than a sourcing one. Both are named in README.md as rung-1 entries and both stay open.
The substitutes above are real and public, so the rung runs today. But the first thing a ninth grader should learn about data is that a person made it, and the cheapest way to teach that is still to make them the person.
Provenance
Every dataset: SOURCES.md, with the four-part source test filled in. Publishers are the City of Los Angeles, the US EPA, the USGS, NOAA GML, and the NASA Exoplanet Archive.