I once confidently predicted AI would handle the grunt work of data science, freeing us humans for the 'real thinking.' Eight years later, I'm eating my words—but not in the way you'd expect.

Turns out AI isn't just crunching the numbers—it's interpreting them too. The machine didn't just want the appetizer; it came for the main course.

And that's actually great news. Data interpretation shouldn't be locked behind specialized degrees or job titles. Whether you're analyzing marketing metrics or trying to make sense of a confusing chart in your creative project, having ChatGPT translate the numbers into insights democratizes what was once exclusive territory (use it to improve your creative process).

Just remember: while ChatGPT gives you a solid starting point for understanding data, it's not infallible (see tips for making ChatGPT more accurate). For decisions that really matter, double-check its work—the same way you'd verify any first draft.

Here's how to use ChatGPT's new powers of data analysis.

How to Upload Charts for ChatGPT Data Analysis

The process for inputting a chart or diagram for ChatGPT data analysis follows the same steps as for image analysis: Simply navigate to the chat box (on desktop or mobile) and click the paperclip icon to upload your file.

ChatGPT's data analysis capabilities extend beyond charts and images—you can upload various data formats, such as Excel spreadsheets, CSV files, and text-based data sets, for interpretation.

Read more: ChatGPT can see, hear, and speak now — here's how to make the best of it

Technical Capabilities of ChatGPT in Data Analysis

ChatGPT's data analysis prowess is driven by its large language model capabilities, which allow it to generate and execute Python code. This feature enables users to perform complex operations like merging datasets, error checking, and outlier detection via natural language commands.

• Python code execution for data tasks
• Natural language commands for data manipulation

These functionalities enhance data accessibility, making intricate tasks more manageable for users without deep technical expertise. For more details, see ChatGPT Advanced Data Analysis.

File Type and Data Size Limitations

ChatGPT supports a variety of file types, including CSV, Excel, and text-based datasets, facilitating diverse data analysis needs. However, users should be mindful of data size and complexity for optimal performance.

• Supports CSV, Excel, and text-based files
• Optimal performance with simplified datasets

This ensures that ChatGPT delivers accurate insights, even when handling sizable datasets. Learn more about its capabilities here.

ChatGPT Data Analysis: Interpreting Chart Information

Struggling to interpret a chart? Upload it to ChatGPT, and it will summarize key findings, highlight trends, and provide insights—making complex data easier to understand.

When I tested it on a demo of Buzzsprout's downloads analytics chart, it did a pretty good job.

When I tested it with a Buzzsprout downloads analytics chart, ChatGPT accurately summarized key insights, identifying a total of 3,331 downloads in the last 30 days. It correctly interpreted the chart's purpose—showing daily download trends.

ChatGPT highlighted noticeable peaks and troughs, indicating variability in daily downloads. It correctly identified two spikes in activity and suggested possible causes—such as new episode releases or increased promotional efforts—providing valuable context to the data.

It noted that there was a consistent base level of downloads each day too, and suggested that this might be a result of a consistent listener base for the podcast—a stat I wouldn't have thought to look at immediately, but an interesting observation.

ChatGPT also suggested additional areas for deeper analysis, such as identifying reasons behind low download days, spotting day-of-week trends, and comparing data across different time frames (last 7 days, last 90 days, all time) to provide a broader context.

Overall, I was impressed with ChatGPT’s ability to interpret straightforward data visualizations. However, when I tested it with a complex marketing dashboard containing multiple metrics, inconsistencies appeared—it misinterpreted some figures, likely due to the volume of information (learn why ChatGPT struggles with math).

To improve accuracy, simplify the input whenever possible—providing focused data sets helps ChatGPT generate more reliable insights (avoid common ChatGPT mistakes).

Effective Questions for ChatGPT Chart Analysis

Given a chart, you can ask ChatGPT specific questions about it too. To test it with the Buzzsprout graph, I told ChatGPT that I did a marketing push on Tuesday the 7th and asked if it worked. ChatGPT gave me a positive response, noting that there was indeed a significant spike in downloads on that day.

When I asked how many downloads occurred on a specific day, ChatGPT estimated the peak at around 400 downloads but struggled to accurately read the corresponding date. Its image analysis currently has difficulty interpreting text that isn’t perfectly horizontal.

Tip: If you notice it having trouble reading the text, you can ask it to rotate the graph and then read it. More on that later.

When asked whether the podcast's download stats were 'good,' ChatGPT provided a nuanced response, explaining that success depends on factors such as podcast age, audience reach, episode frequency, and marketing efforts. It also emphasized that engagement metrics matter—not just total downloads.

Using ChatGPT to Analyze Different Diagram Types

ChatGPT can also interpret and answer questions about common kinds of diagrams, like organizational charts.

I tested ChatGPT’s ability to analyze organizational charts using the Des Moines Public Schools Org Chart. It successfully identified departments and determined hierarchical relationships, such as whether the Internal Audit department fell under Financial Services.

However, I noticed that when asking multiple questions, ChatGPT sometimes stopped explicitly referring to the uploaded image, leading to incorrect answers. To ensure accuracy, prompt it to reanalyze the image rather than relying on its internal assumptions.

ChatGPT can also analyze the logical flow of diagrams, such as flowcharts. It has a basic understanding of how different elements connect, making it useful for interpreting complex workflows and relationships.

You can use this as a way to input a workflow or process into ChatGPT instead of trying to explain it in words.

Tip: ChatGPT can also write Python code to do more sophisticated image processing.

ChatGPT Data Visualization Analysis and Design Tips

ChatGPT has a solid grasp of data visualization best practices. If you're preparing charts for a presentation, it can recommend the most effective visualization type based on your data, helping you communicate insights more clearly.

When I gave it three chart options to represent four quarters of gross margin data and asked which one was the best, it gave a nuanced recommendation to present it as a column chart, followed by a line chart (which, it noted, might be misleading because it implies a continuous change in the gross margin quarter to quarter), and lastly a bar chart, noting that this is not really best practice and mostly useful if comparison is the main goal of your analysis. Overall, I thought it was a pretty good recommendation.

Given raw data, ChatGPT can generate a graph using Python code. When I asked it to pull data from a Tableau marketing dashboard, it successfully created a graph but mislabeled the units—demonstrating its capabilities while highlighting the need for human validation.

When prompted to enhance visual appeal, ChatGPT made useful adjustments, such as formatting marketing spend in dollars, centering labels, and adding gridlines for better readability.

From there you can ask it to make specific changes you want, such as alternating different colors.

One of the best aspects of ChatGPT's visualization tool is its ability to provide constructive feedback. While it tends to be optimistic, it won't hesitate to point out design flaws—offering practical suggestions for improvement.

When I asked for feedback on my rudimentary flow chart above, it gave a lot of constructive criticism, including that it "lacks visual appeal" and it could be "streamlined to reduce visual clutter."

Improving ChatGPT Chart Reading with Proper Rotation

When using ChatGPT's image interpretation tools, ensure the text in your diagrams is as close to horizontal as possible. The current model struggles with reading angled or distorted text, which can impact accuracy.

But there's an easy fix: You can specifically ask it to try rotating the image to better read it.

Key Takeaways: ChatGPT for Data Analysis

Uploading diagrams and charts allows you to input complex information into ChatGPT for analysis. While it’s not perfect, its ability to interpret and generate insights makes it a valuable tool for data exploration. As AI advances, its capabilities in graph analysis and interpretation will only improve.

FAQs

Can ChatGPT integrate with cloud storage services like Google Drive?

Yes, ChatGPT can integrate with cloud storage services such as Google Drive and Microsoft OneDrive, allowing users to upload files directly for analysis. However, users should prioritize data security and comply with privacy guidelines when uploading sensitive information. For more information, visit OpenAI's insights.

How does ChatGPT handle large datasets?

While ChatGPT can process large datasets, it's recommended to simplify complex data for better performance. This approach helps ensure that ChatGPT provides accurate and reliable insights, even with substantial data sizes. More information is available at Narrative's guide.