I created the website From Excel to Python because I saw that many people are struggling using Excel. They are suffering, they are not very happy, they complain about that, and they realize that it’s not very productive—and they are right.
Excel is super nice, I like it, but it has its limitations. Many people, especially accountants, many times I saw them doing a simple Excel file like it is its own software with 20 tabs and doing a VLOOKUP of a VLOOKUP. That is super heavy. However, we can do all this using Python. You take all the heavy files that you produce already, but you replicate that into Python in order to get things simplified, much faster, and start automating things.
The Catalyst: How a 90-Minute Report Became 30 Seconds
This all started when I was trying to help a friend who was taking 90 minutes to do simply one report. He was taking all the raw data, and it was taking him 90 minutes to produce that. That was just for one client—and he had many clients, so you can see the problem right away.
So I replicated everything he was doing in Excel into Python, and it only took him 30 seconds to reproduce it. You see all the economy that you have, all the time that goes back to productivity. That’s the full purpose.
The 15-Year Corporate Pattern
This is not the only case. During my corporate career, I was taking positions in many different companies, different sizes, and from different countries. It is always the same pattern: they have very large Excel files calling from different reports. They need just one column from one report, and another column from another report. To get to that file, they need to go to multiple folders to find them and do the VLOOKUP. It’s not friendly at all.
People are so tired of doing this type of job that they only do the surface—meaning they do the absolute minimum they need to do because it is very tedious. They simply do the report. But the way that I consider simply doing the report is just the surface, just the minimum. Of course, you cannot do more because it takes a lot of time.
The Shared Folder Nightmare: When Spreadsheets Break
Another big issue I saw repeatedly in my career is what happens when more than one person touches these files.
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Someone renames a tab, someone moves a file to another folder in SharePoint or OneDrive, or someone accidentally deletes a formula in row 452. Suddenly, the whole workbook breaks with #REF! errors everywhere. You spend the next three hours hunting down who touched what and trying to restore an older version.
Excel was never built to act as a database or an automated data pipeline. When you make the move from Excel to Python, your raw data files remain untouched and safe. Python simply reads the data, processes everything in memory following your exact script, and outputs the clean result. You never have to worry about broken formulas, corrupted workbooks, or accidental overwrites again.
Why Python Over “Black-Box” AI
If you think about this, you are not adding value. You are simply doing something that eventually AI can do.
One thing that I don’t like very much about AI for these types of things is because it is a black box. Many times people don’t know what the AI is doing, so they delegate to it and cross their fingers that everything is going to be exactly like that, hoping AI is not going to decide one day to change something. Because of that, people can make wrong decisions.
On the other side, when you have hard code like Python, you can be sure that you are always going to have the exact same procedure. Python is going to follow the same rules you defined. That is the beauty of this.
Moving Beyond the Surface to Real Business Value
What I find more fascinating is when you don’t only do what you are supposed to do—what I call the surface—but now, because you saved 89 minutes, you can go into deeper analysis. You can bring insights. You can bring better decisions to people.
That is when you start adding value by saying:
- “I recognize that here we can reduce some costs.”
- “Here we have a business opportunity.”
- “This is a way that we can increase revenue.”
That’s when you start being a valuable employee or a valuable manager, because you are not doing just the basics. (Again, AI can do the basics.) You need to add value, and that can only be done once you optimize your own processes.
You Don’t Need to Be a Software Engineer
Many Excel users tell me: “Fernando, Python is programming. I’m an accountant / analyst, not a software engineer.”
But here is the secret: if you already understand Excel formulas, you already understand data logic.
- When you do a
VLOOKUPorXLOOKUP, in Python you simply do amerge. - When you build a Pivot Table, in Python you do a
groupby. - When you apply an
IFstatement or filter a column, Python does it in one readable line of code.
You don’t need to learn computer science, game development, or web servers. You only need to learn the specific Python tools (like Pandas) that replicate and supercharge what you already do every single day in spreadsheets.
The 80/20 Reality: Stop Cleaning Data and Start Analyzing
This website, From Excel to Python, is all about helping Excel users that are frustrated with doing these reports every week or every month, taking forever, seeing Excel crash, and finding it difficult just to get the data. If a column changes, you don’t know what to do; if you need to do an executive report out of that, it gets even more complex.
This is what I have seen over the last 15 years: people running just to get the data and clean the data. In one company, I had to spend 80% of my time just to get the data and clean it. And I only had 20% left for the analysis! But the analysis was the real thing they needed: What’s happening with this data? Why is this happening?
Because getting the data was so tedious—80% of the time—you get tired. That is a big challenge. But if you remove that bottleneck with processes automated by Python that take just one minute to run, now your brain is fresh.
This is where you can start all the beautiful things that data analysis has, and once again, add value. When you add value, that is when you get a promotion, or when you can move to another company because you have more skills, your portfolio gets bigger, and you can show what you did.
Start Your Journey From Excel to Python
If you are ready to stop being a data janitor and start automating your weekly workload, explore the practical guides and tutorials on the From Excel to Python blog.
Take your first step today, and reclaim your time for the analysis that actually matters.
