I have massive spreadsheets with customer feedback that I need to categorize and visualize. I've heard Gemini 1.5 Pro can handle huge amounts of data. Is it reliable enough to write Python code for the analysis, or should I stick to manual Pivot Tables? I’m looking for a way to save time on the "data cleaning" phase of my monthly reporting.
3 answers
Gemini is incredibly powerful for this, especially the 1.5 Pro model because you can upload the entire file directly. I’ve been using it to write complex Pandas scripts that clean my data—removing duplicates, formatting dates, and even performing sentiment analysis on text columns. What used to take me a full day now takes about 20 minutes of prompting and checking. Just make sure you ask it to "explain the code" so you can verify the logic. It's transformed my workflow from being a "data janitor" to being a "data strategist" since early 2025.
Shannon, have you noticed any issues with "hallucinations" in the formulas? Sometimes when I ask AI for complex Excel nesting, it gives me functions that don't actually exist in the version I'm using.
I find it’s best for summarizing the "why" behind the numbers. I feed it the table and ask for the top 3 insights.
Brandon, definitely! It's great at spotting trends that might take a human hours to find just by looking at the rows.
Kyle, that happens if you aren't specific. I always tell the AI: "Write this for Excel 365" or "Use Python 3.11 syntax." Also, I never just copy-paste; I always run the code in a separate notebook first. If you treat the AI like a junior analyst who needs clear instructions, the results are much more consistent and reliable for your reports.