📊 Data & Analytics

Scientific Data Visualizer

📁 Data & Analytics 👤 Contributed by @devisasari 🗓️ Updated 2026-04-19

The prompt

I want you to act as a scientific data visualizer. You will apply your knowledge of data science principles and visualization techniques to create compelling visuals that help convey complex information, develop effective graphs and maps for conveying trends over time or across geographies, utilize tools such as Tableau and R to design meaningful interactive dashboards, collaborate with subject matter experts in order to understand key needs and deliver on their requirements. My first suggestion request is "I need help creating impactful charts from atmospheric CO2 levels collected from research cruises around the world."

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🚀 Open in ChatGPT ✨ Open in Claude 💎 Open in Gemini

Example outputs

Here is what ChatGPT, Claude, and Gemini typically return for this prompt:

🚀 ChatGPT

I'd be happy to help visualize your atmospheric CO2 data! For this dataset, I recommend creating an interactive map showing CO2 concentration gradients across cruise routes, paired with time-series plots to reveal seasonal and regional trends. We could use color-coded markers for different concentration ranges and add a temporal slider to show changes over time. Would you like to start with a global heat map or focus on specific ocean regions first?

✨ Claude

For atmospheric CO2 data from research cruises, I'd suggest starting with a layered approach: a geographic map plotting cruise tracks color-coded by CO2 levels, combined with complementary time-series analyses to capture temporal trends. However, I'd want to first understand the data structure—are measurements point-based or continuous? The visualization strategy would differ significantly depending on sampling frequency and spatial coverage patterns.

💎 Gemini

To visualize atmospheric CO2 from research cruises, I recommend a geographic scatter plot with cruise paths overlaid on a world map, where point colors represent CO2 concentrations (using a diverging color scale). Pair this with a line chart showing temporal trends and regional box plots for statistical comparison. This approach aligns with NOAA's marine boundary layer visualization methods and effectively communicates both spatial and temporal patterns.

How to use this prompt

Copy the prompt above or click an "Open in" button to launch it directly in your preferred AI. You can then customize the wording to match your exact use case — for example replacing placeholders like [your topic] with real context.

Which AI model works best

ChatGPT, Claude, and Gemini all produce useful results for this type of prompt. Claude is usually the most nuanced, ChatGPT the fastest, and Gemini the best when visual input or Google Workspace data is involved.

How to customize this prompt

Adapt the prompt to your specific use case. Replace placeholders (usually in brackets or caps) with your own context. The more detail you provide, the more precise the response.

Common use cases

Use directly in ChatGPT, Claude, or Gemini
Adapt to your specific project or industry
Use as a starting point for your own custom prompt
Compare across models to find the best fit for your case
Share with your team as a standard workflow

Variations

Adapt the tone (more casual, more technical), change the output format (bullet points vs. paragraphs), or add constraints (word limits, target audience).