Use case 01
Use it when you want to begin exploratory analysis work without writing the first draft from scratch.
Citizen Data ScientistExploratory AnalysisBeginnerSingle prompt
Plain English Data Summary AI Prompt
Summarize this dataset in plain English for someone who has never seen it before. Write the summary as if you are explaining it to a colleague in a 5-minute conversation — not a... Copy this prompt template, run it in your AI tool, and use related prompts to continue the workflow.
Prompt text
Summarize this dataset in plain English for someone who has never seen it before.
Write the summary as if you are explaining it to a colleague in a 5-minute conversation — not a technical report.
Cover:
1. What this dataset is about — one sentence that a non-technical person would understand
2. The scale — how much data is here? Put it in relatable terms (e.g. '12,000 rows — roughly one row for every customer who visited last year')
3. The time range — what period does this cover and is that enough to spot trends?
4. The key columns — the 4–5 most important columns and what they tell us
5. The data quality in plain terms — not statistics, but a verdict: 'mostly complete', 'some gaps in a few areas', or 'significant holes that need fixing'
6. The headline finding — is there one thing that immediately stands out as interesting or concerning?
7. What you would do first if this were your dataset — one specific next step
Rules:
- No bullet points that list statistics without meaning
- Every number must have context ('23% of rows have missing values in the discount column — that is nearly 1 in 4 rows')
- End with a single sentence: 'The most important thing to know about this dataset is: [sentence].'When to use this prompt
Use case 02
Use it when you want a more consistent structure for AI output across projects or datasets.
Use case 03
Use it when you want prompt-driven work to turn into a reusable notebook or repeatable workflow later.
Use case 04
Use it when you want a clear next step into adjacent prompts in Exploratory Analysis or the wider Citizen Data Scientist library.
What the AI should return
The AI should return a structured result that covers the main requested outputs, such as What this dataset is about — one sentence that a non-technical person would understand, The scale — how much data is here? Put it in relatable terms (e.g. '12,000 rows — roughly one row for every customer who visited last year'), The time range — what period does this cover and is that enough to spot trends?. The final answer should stay clear, actionable, and easy to review inside a exploratory analysis workflow for citizen data scientist work.
How to use this prompt
1
Open your data context
Load your dataset, notebook, or working environment so the AI can operate on the actual project context.
2
Copy the prompt text
Use the copy button above and paste the prompt into the AI assistant or prompt input area.
3
Review the output critically
Check whether the result matches your data, assumptions, and desired format before moving on.
4
Chain into the next prompt
Once you have the first result, continue deeper with related prompts in Exploratory Analysis.
Frequently asked questions
What does the Plain English Data Summary prompt do?+
It gives you a structured exploratory analysis starting point for citizen data scientist work and helps you move faster without starting from a blank page.
Who is this prompt for?+
It is designed for citizen data scientist workflows and marked as beginner, so it works well as a guided starting point for that level of experience.
What type of prompt is this?+
Plain English Data Summary is a single prompt. You can copy it as-is, adapt it, or use it as one step inside a larger workflow.
Can I use this outside MLJAR Studio?+
Yes. The prompt text works in other AI tools too, but MLJAR Studio is the best fit when you want local execution, visible Python code, and reusable notebooks.
What should I open next?+
Natural next steps from here are Data Quality Red Flags, Find the Patterns, My First Dataset Exploration.