Oct 18, 2023
5 min

How to Use ChatGPT Prompts to Improve Your Data Visualization

PlotSet teamwriter

Harnessing the power of ChatGPT

ChatGPT is a familiar name that we have heard frequently lately. And for a good reason. This powerful language model developed by OpenAI has the potential to significantly enhance your data visualization projects. By using effective prompts, you can leverage the capabilities of ChatGPt to improve outcomes.

The following blog guides you on how to use ChatGPT prompts to elevate your data visualization game.

Prompts to use with ChatGPT

In the modern information age, providing an easy-to-understand visual representation of complex data is crucial. The success of a good data visualization is not only in the data but also in the presentation.

Through the power of ChatGPt prompts, you can enhance various aspects of your data visuals, from color palettes to font choices. You can even ask for the most suitable template for your dataset.

To enhance your data visualization project, here are 10 ways to use prompts:

1. Color palette enhancement

Prompt 1: "ChatGPT, suggest a set of colors ideal for a bar chart representing mocha coffee prices."

Response: "Certainly! Here are some colors inspired by mocha and the rich tones of coffee:
  • Espresso Brown: #4B3621
  • Creamy Latte: #D5A583
  • Whipped Cream White: #F5ECE3
  • Dark Cocoa: #2E1F13
  • Frothy Top: #F6E0C4

These colors will not only make your bar chart visually appealing but also resonate with the theme of mocha coffee."

Prompt 2: "ChatGPT, suggest a color palette for a climate change data visualization focusing on global warming over the last century."

Response: "Consider using a gradient from cool blues to warm oranges and reds, representing the shift in temperature."

Prompt 3: "ChatGPT, generate a color palette inspired by the autumn or Halloween season, suitable for data visualization."

Response: "Sure! Here's an autumn-inspired color palette:
  1. Burnt Orange: #D35400
  2. Golden Yellow: #F1C40F
  3. Deep Red: #A93226
  4. Olive Green: #808000
  5. Chocolate Brown: #8E44AD
  6. Midnight Blue (Halloween Touch): #2C3E50
  7. Ghostly Grey: #7F8C8D
  8. Pumpkin Spice: #F39C12
  9. Forest Green: #27AE60
  10. Pale Corn: #E8DAEF

These colors evoke the feelings of fall leaves, autumn skies, and Halloween themes, making them great for seasonal visualizations.

2. Font recommendation

Prompt 1: "ChatGPT, which font is suitable for a corporate financial report visualization?"

Response: "Opt for a sans-serif font like Arial or Inter for a clean, professional appearance."

Prompt 2: "Suggest a playful and readable font suitable for a chart showcasing children's toy sales."

Response: "Absolutely! For a chart on children's toy sales, I'd recommend the font 'Comic Sans MS.' While it's often joked about in the design community, it's undeniably playful and is designed to be easy for young readers. Another good option would be 'Baloo Bhai,' a vibrant and bubbly font that captures the essence of fun and playfulness, perfect for representing children's toys."

Prompt 3: "ChatGpt, suggest a bold and dynamic font appropriate for a sports-related chart."

Response: "Certainly! For a sports-related chart that requires a bold and dynamic feel, I'd recommend using 'Impact' or 'Bebas Neue.' Both fonts exude strength and modernity, making them ideal choices for capturing the energetic spirit of sports."

3. Template suggestions for specific data types

Prompt 1: "ChatGPT, I'm trying to display cereal companies' market share. Which visualization template would best convey this information?"

Response: "A pie chart or a donut chart would be effective for showing market shares of different cereal companies, as it visually represents the proportional segments of each company in the market. If you want to show trends over time, consider a stacked bar chart or area chart."

Prompt 2: "Which chart type would best visualize the correlation between age and salary in a dataset?"

Response: "A scatter plot would be ideal for visualizing the relationship between age and salary. It allows each data point to represent an individual's age and corresponding salary, providing a clear view of any trends or patterns between the two variables."

Prompt 3: "What is an effective way to display the distribution of customer feedback categorized as positive, neutral, and negative?"

Response: "A pie chart or a doughnut chart would be suitable for visualizing the distribution of customer feedback in categories of positive, neutral, and negative. This type of visualization provides a clear proportionate view of each category in relation to the whole."

4. Asking for captions/descriptions

Prompt 1: "ChatGPT, I need a snappy journalistic caption for a stacked area chart that depicts the 50-year trends in real hourly wages. Can you help?"

Response: "Climbing the Wage Ladder: Half a Century of Real Hourly Earnings Evolution."

Prompt 2: "Can you craft a compelling journalistic caption for a line chart showcasing the upward trend of global temperatures?"

Response: "Warming Waves: The undeniable ascent of global temperatures through the years."

Prompt 3: "Could you provide a catchy caption for a bubble chart that juxtaposes cities based on their population size and GDP?"

Response: "Cities of Influence: Picturing Population & Prosperity in One Bubble Landscape."

5. Enhancing accessibility

Prompt 1: "ChatGPT, how can I make my chart on global literacy rates accessible for color-blind viewers?"

Response: "Incorporate patterns in addition to colors, and consider tools like Color Oracle to test your visuals."

Prompt 2: "ChatGPT, can you provide hex color codes suitable for a color-blind-friendly chart?"

Response: "Of course! Here are some color-blind-friendly hex codes:
  1. Blue: #0072B2
  2. Orange: #E69F00
  3. Sky Blue: #56B4E9
  4. Yellow: #F0E442 5 Vermilion: #D55E00
  5. Reed Purple: #CC79A7

Remember, when designing for color-blindness, it's not just about the colors but also about the patterns, labeling, and contrasts you use."

Prompt 3: "Can you outline the best practices to ensure a line chart is accessible for individuals with visual impairments?"

Response: "Certainly! Here are some best practices to make a line chart accessible for those with visual impairments:
  • High Contrast: Use high-contrast colors for lines against the background to make them stand out.
  • Thicker Lines: Use bolder line weights to make them more distinguishable.
  • Clear Labels: Ensure labels are large, legible, and in a readable font.
  • Use Patterns: Besides color, consider using patterns to differentiate between lines.
  • Interactive Elements: If digital, provide hover or touch effects that describe data points in detail.
  • Alternative Text: Include descriptive alternative text for charts in digital formats to be read by screen readers.
  • Audio Descriptions: Consider providing an audio description of the main insights from the chart.
  • Tactile Charts: For printed materials, consider tactile graphics where lines can be felt.
  • Legends: Make legends clear and place them close to the relevant data.
  • Avoid Overcrowding: Too many lines or data points can be overwhelming; keep it simple

By keeping these best practices in mind, you can make your line chart more inclusive and accessible to a wider audience."

6. Data transparency and sourcing

Prompt: "ChatGPT, when creating visualizations, I want to ensure that viewers understand the sources and reliability of my data. What strategies can I implement to communicate this information effectively within the visualization itself?"

Response: "To effectively communicate the sources and reliability of data within your visualization, consider the following strategies:
  • Source Annotation: Always include a clear, concise note at the bottom or side of your visualization specifying where the data originated. This can be a simple statement like "Data Source: World Health Organization" or a more detailed citation if needed.
  • Confidence Intervals: If applicable, add confidence intervals or error bars to your charts. This gives viewers an idea of the reliability and variability of the data points.
  • Interactive Tooltips: If your visualization is digital and interactive, consider adding tooltips that appear when users hover over specific data points. These tooltips can provide additional information about the data source, collection method, or reliability metrics.
  • Data Reliability Key: Create a key or legend that describes the reliability metrics or symbols you use. For instance, you could use different symbols (like a circle, triangle, or square) to indicate data points from different sources or with varying levels of reliability.
  • Narrative Box: If space permits, add a small narrative or information box that briefly explains the data collection process, any potential biases, the methodology used, and any other factors that might influence data reliability.
  • Hyperlink to Full Report: Especially for digital visualizations, provide a hyperlink or QR code that directs viewers to the complete data report or source. This allows those interested to delve deeper and understand the context and reliability better.
  • Transparency about Limitations: Always be transparent about any limitations or potential biases in your data. This not only adds credibility to your visualization but also fosters trust with your audience.

Remember, the ultimate goal is to make your visualization both informative and trustworthy. By clearly indicating sources and reliability, you enhance the viewer's understanding and confidence in the presented data."

7. Best practices for geospatial data

Prompt 1: "ChatGPT, how should I best visualize the mortality rates of coronary heart disease across various countries on a global map?"

Response: "For effectively displaying coronary heart disease mortality rates across different countries on a world map, a 'Choropleth Map' is highly recommended. This type of map uses varying shades of a color (often from light to dark) to indicate the mortality rates. Countries with higher rates will be depicted with darker shades, while those with lower rates will have lighter shades. This gives a clear visual representation of the regions with the highest and lowest mortality rates. To enhance comprehension, consider integrating interactive tooltips that display specific rate values upon hovering. Ensure you select a color-blind friendly palette and incorporate a detailed legend for maximum clarity and accessibility."

Prompt 2: "What is an effective method to depict a company's sales distribution across different continents globally?"

Response: "To effectively represent a company's global sales distribution across continents, you can use a 'Proportional Symbol Map'. In this type of visualization, symbols (often circles) of varying sizes are placed on each continent to represent the volume of sales. The larger the symbol, the higher the sales in that particular continent. For a clearer distinction, you can also color-code the symbols based on the sales range. Pairing this with interactive tooltips can offer more detailed information, such as exact sales figures, when a user hovers over a symbol. Ensure to include a legend that explains the symbol sizes and, if used, the color gradation."

8. Advice on data normalization and transformation

Prompt 1: "I have a number of people behind bars for each country. How can ّ visualize this data that compares countries fairly?

Response: “Calculate the number of people behind bars per capita for each country. Divide the number of people behind bars by the total population of the country to get a standardized metric that accounts for population differences.”

Prompt 2: "ChatGPT, I'm working on visualizing GDP growth rates for countries with diverse economies. How can I normalize the data to ensure a fair comparison?"

Response: "When visualizing GDP growth rates of countries with differing economic scales, it's essential to focus on the 'percentage growth rate' rather than absolute GDP values. This ensures that you're comparing the relative change in GDP, which normalizes the data. For example, a 5% growth in a smaller economy might represent a much smaller absolute value compared to a larger economy, but it tells you the rate at which each economy is expanding. Additionally, consider providing context with supplementary data, such as GDP per capita or purchasing power parity (PPP), to give a fuller picture of each country's economic standing. Using consistent scales and clear labeling will further enhance the clarity of your visualization."

Prompt 3: "ChatGPT, I have a dataset with a few extremely high outliers. What transformation technique would you recommend to handle these and make the data more interpretable?"

Response: "For datasets with extreme outliers, applying a 'logarithmic transformation' is a common technique. Converting the data to a log scale compresses the larger values and spreads out the smaller ones, making outliers less pronounced and the data more manageable. This helps in visualizing the data in a way that reveals patterns without being overly influenced by the outliers. However, when presenting or interpreting the transformed data, it's essential to clearly indicate that a logarithmic scale is in use and to understand the implications of this transformation for any subsequent analysis or conclusions."

9. Guidance on emphasizing anomalies and outliers in datasets

Prompt: "ChatGPT, I'm working on a visualization of food inflation data worldwide, and there are certain regions where the inflation rates have surged dramatically. What techniques would you suggest for drawing attention to these regions in my visualization?"

Response: "To emphasize regions with dramatic surges in food inflation, consider the following visualization techniques:
  • Highlighting with Color: Use a contrasting color to make the affected regions stand out from the rest. This will immediately draw the viewer's attention to these areas.
  • Annotations: Add text labels or arrows pointing to the highlighted regions, giving brief descriptions or specific inflation rates to provide context.
  • Interactive Tooltips: If your visualization is interactive, employ tooltips that display detailed information about food inflation rates when a user hovers over or clicks on a particular region.
  • Zoomed Insets: For regions with extreme inflation rates, create a zoomed-in inset map. Position this inset adjacent to the main map to provide a detailed perspective of that region.
  • Adjust Visualization Scale: If using a choropleth map, consider adjusting the color scale so that regions with high inflation rates are distinctly colored, making them easy to identify.
  • Use a Secondary Axis: If the data has multiple metrics and the surge in inflation pertains to a specific food item or category, consider using a secondary axis or a side-by-side comparison to emphasize that particular metric.
  • Emphasize Design Elements: Utilize graphical elements like drop shadows, bolding, or borders to make the regions with high inflation rates stand out visually.

Remember, while drawing attention is essential, it's crucial to maintain the integrity of the data. Ensure that any emphasis doesn't misrepresent the data or mislead the viewer."

10. Optimizing for mobile

Prompt 1: "ChatGPT, how can I ensure my bar chart on yearly expenses is mobile-friendly?"
Response: "Stack bars vertically, ensure touch-friendly interactivity, and use responsive design principles."

Prompt 2: "How can I optimize a detailed line chart for better clarity and comprehension on mobile screens?"
Response: "To enhance the clarity of a detailed line chart on a mobile device, consider implementing the following adjustments:

  • Simplify the Data: For mobile presentation, prioritize key data points or trends. Consider showing averages or rolling averages instead of granular daily values.
  • Increase Line Thickness: Ensure the line is easily visible against the background, especially on smaller screens.
  • Responsive Design: Use a responsive charting library that adapts to different screen sizes and orientations.
  • Limit Data Series: On a small screen, it's challenging to differentiate between multiple data series. Stick to one or two main series and consider using other visualization types for additional data.
  • Enlarge Data Point Markers: Make markers for significant points larger or use different shapes to make them stand out.
  • Interactive Tooltips: Use tooltips that appear upon tapping, providing additional information about the specific data point.
  • Vertical Orientation: Given the portrait orientation of most mobile usage, design the chart to be taller rather than wider. Limit Legend and Axis Labels: Use abbreviations, icons, or interactive legends to avoid clutter. Ensure axis labels are concise yet clear.
  • Use High Contrast Colors: This ensures that lines and data points are distinguishable from the background and each other, even in bright conditions or on low-resolution screens.
  • Interactive Zooming and Panning: Allow users to zoom into areas of interest and pan across the timeline to inspect details as needed.

By tailoring the line chart to the unique constraints of mobile screens, you can provide users with an efficient and informative visual experience."

Is there any other way to perfect visualization using ChatGPT prompts

The answer is yes. Basically, you can ask ChatGpt anything. You should also bear in mind that although the response it provides you might be accurate enough, it might not be suitable for your database or visualization. So, make sure to analyze the response before applying.

Let’s see what other ways you have to seek help from ChatGPT:

  • Creating comparative visualizations for different audiences
  • Keeping the balance between the aesthetics and functionality
  • Seeking advice on using backgrounds and white spaces effectively
  • Inquiring about visualizing uncertainty or data with a margin of error
  • Inquiring about using storytelling techniques within data visualizations
  • Seeking advice on emphasizing the most critical data points or findings
  • Asking for guidance on effective use of icons and symbols
  • Asking for techniques to improve clarity and declutter your charts
  • Asking for advice on optimizing visualization for different mediums
  • Seeking interactivity and animation recommendations for dynamic visualizations

One final note

By incorporating ChatGPT prompts into your data visualization process, you can create more engaging, informative, and accessible graphics. If you need help refining and enhancing your visual data presentations, ChatGPT can be a useful tool.

Now, imagine combining this great source of knowledge and information with our straightforward and efficient data visualization templates! With Plotset, you can choose the best template for your datasets and, with the help of ChatGPT, turn it into a compelling visualization.

Give it a try now!

We, the PlotSet team, are enthusiastic to spice up your storytelling world using data visualization, and we will show you how to do so through various blogs. If you’re into data journalism or you just want to present your data to an audience, we strongly suggest taking a look at what we have prepared for you here. Enjoy reading!

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