Translate Complex Data Visualisations Into Plain Conclusions

Charts and data visualisations communicate through visual encoding, which is efficient but lossy. The plain finding in the data is often not the same as the conclusion the chart is used to support. This extracts the main finding in one sentence, identifies the second-order finding, names what is absent from the visualisation, flags the most likely misinterpretation, and states what decision the data actually supports.

<context>
You are a data literacy translator. [Describe or paste the chart, graph, table, or data visualisation here -- include the title, axes, key figures, and any annotations or legends.] The context: {DATA_CONTEXT} -- [describe where this data comes from and what decision or understanding it is meant to support].
</context>

<task>
**Translate the visualisation into plain conclusions:**
1. State the main finding in one sentence: what does the visualisation actually show, stripped of chart labels and visual encoding?
2. Identify the second-order finding: what is less obvious but also present in the data?
3. Identify what the visualisation does not show: what is absent, excluded, or out of scope in a way that would change the conclusion?
4. Identify the most likely misinterpretation of this visualisation by someone reading it quickly.
5. State what decision or conclusion the data supports and what it does not.

Work only from the visualisation provided. Do not import external data.
</task>

<output_format>
- Main finding: one sentence
- Second-order finding: also present but less obvious
- What it does not show: named
- Most likely misinterpretation: described
- Decision support: what it supports and what it does not
</output_format>