I Reformatted 500 Spreadsheet Names by Hand Before Discovering Case Converters

Updated on May 6, 2026

It was a Tuesday afternoon, the kind where the coffee has gone cold and you're too deep into a task to get up and reheat it. I had a spreadsheet in front of me — 500 rows of product names exported from our old inventory system — and every single name was in ALL CAPS. BRASS FITTING 3/4 INCH ELBOW. COPPER PIPE TYPE L 10FT. PVC REDUCER BUSHING SCHEDULE 40. Five hundred of them, shouting at me from the screen.

The new system needed them in Title Case. Not optional — the import validator would reject anything that didn't match the format. My manager had already emailed twice asking when the migration would be done.

So I did what any reasonable person does when they don't know better: I started typing.

The Manual Phase (I Don't Like Thinking About This)

I double-clicked the first cell. Deleted the all-caps text. Typed it out again properly: Brass Fitting 3/4 Inch Elbow. Moved to the next row. Did it again. And again.

By row 40, my fingers had developed a rhythm I wasn't proud of — backspace, type, Tab, backspace, type, Tab. I had a podcast playing. I told myself this was "mindless work" and that I could multitask. I could not multitask. You cannot actually listen to a podcast while manually reformatting text; your brain keeps dropping one or the other.

Around row 70, I made my first mistake. I typed Pvc Reducer Bushing Schedule 40 instead of PVC Reducer Bushing Schedule 40. The acronym problem. Title Case doesn't actually mean every word gets capitalized the same way — "PVC" should stay "PVC," not become "Pvc." This meant I couldn't even zone out; I had to actively read each name for abbreviations.

By row 90, I had been at this for over an hour. At this rate, the math said I'd finish sometime late Wednesday. I had other things due Wednesday.

The First "Solution" (That Wasn't)

I remembered Excel had a PROPER() function. I'd used it once years ago. I typed =PROPER(A2) into an adjacent column, dragged it down, and felt the brief, electric joy of watching 500 cells transform instantly.

Then I looked at the results.

Pvc Reducer Bushing Schedule 40. There was that acronym problem again, now at scale. 3/4 Inch was fine. But L 10Ft — the function had capitalized the "F" in "10Ft" because it followed a number, treating the whole thing as a new word boundary. Type L became Type L which was actually fine, but Ph Balance for a cleaning chemical product became Ph Balance instead of pH Balance.

The formula had traded one set of errors for a different set of errors. I spent another 45 minutes manually fixing the PROPER() output. I was now deeper in the hole than when I started because I'd introduced new mistakes I had to hunt down.

I pushed back from the desk. Walked to the kitchen. Made tea I didn't want. Came back.

The Conversation That Changed the Afternoon

I vented to a colleague on Slack — one of those messages where you're not really asking for help, just complaining into the void. Something like: "why does excel PROPER() not understand acronyms, I have 500 rows, kill me."

She replied in about thirty seconds: "have you tried an online case converter? there are like five good free ones, you paste the whole column and it does it instantly"

I had not tried that. I had not even considered that this category of tool existed.

She sent me a link. I went to the site, saw a plain text box, and felt skeptical in the way you feel skeptical about something that looks too simple. I copied all 500 product names from the spreadsheet — just the raw text, one per line — and pasted them in. Selected "Title Case." Clicked convert.

Half a second.

All 500 names, reformatted, stacked in the output box.

I sat there for a moment doing nothing. Then I copied the output, pasted it back into the spreadsheet, and did a quick scan. The acronym issue was still there — any tool doing pure Title Case will have that problem — but the bulk of the work was done. I now had maybe 15 names that needed manual touch-ups for abbreviations like PVC, PH, RPM, and BTU. Fifteen, not five hundred.

Total time from paste to finished: maybe four minutes, including the fixes.

What I Actually Learned About These Tools

After that afternoon, I spent some time actually understanding how case conversion tools work, because I was annoyed at myself for not knowing about them sooner and wanted to make sure I understood them properly going forward.

The most useful ones handle more than just Title Case and UPPERCASE and lowercase. The case types that come up constantly in real work are:

  • Title Case — for product names, headings, proper nouns. Most tools capitalize every word; smarter ones skip short prepositions like "of," "in," "the."
  • Sentence case — only the first letter of the first word capitalized, like a normal sentence. Useful for descriptions, meta text, alt text.
  • camelCase — first word lowercase, subsequent words uppercase, no spaces. This is what developers need for variable names: productNameLong.
  • PascalCase — same as camelCase but the first word is also capitalized: ProductNameLong. Used for class names in most programming languages.
  • snake_case — all lowercase, spaces replaced with underscores: product_name_long. Database columns, Python variables, file names.
  • kebab-case — all lowercase, spaces replaced with hyphens: product-name-long. URL slugs, CSS class names, HTML attributes.
  • SCREAMING_SNAKE_CASE — all caps with underscores: PRODUCT_NAME_LONG. Constants in most languages.

The reason this matters is that the same underlying text often needs to exist in multiple forms simultaneously. A product might have a display name in Title Case for the UI, a slug in kebab-case for the URL, a variable name in camelCase in the JavaScript, and a database column in snake_case. Before I understood these tools, I was doing each transformation by hand every time. The right tool lets you paste once and convert to whichever form you need.

The Workflow I Actually Use Now

After that spreadsheet incident, I started paying attention to how often I was doing manual text reformatting. Turned out: constantly. Copying a client's company name from a PDF (all caps in their letterhead) into a CRM field. Taking column headers from a database export and turning them into readable labels for a report. Converting a list of filenames from underscore format to something presentable.

My current approach for bulk conversions: copy the raw text (whole columns, whole lists, whatever), paste into a case converter, select the right case type, copy output, paste back. The whole operation takes under a minute for any volume of text. I've done it with 2,000 rows. Same speed.

For one-off conversions where I'm writing code, I've started using tools that sit right in the browser or as small desktop utilities, so I don't have to navigate to a website each time. The friction reduction matters — if it takes eight clicks to get to the tool, I'll sometimes talk myself into just typing it manually "this once," which is how you end up spending an hour on something that should take thirty seconds.

The other habit I've built: when I'm the one creating data that other people will need to reformat, I try to export or provide it in a consistent, clean case to begin with. Whoever receives a spreadsheet from me gets Sentence case or Title Case, not whatever chaotic capitalization the source system used. It takes me ten seconds to run it through a converter before sending. It saves the next person from having my Tuesday afternoon.

The Part I Still Do Manually (And Why)

Acronyms, proper nouns, and brand names. No automated tool handles these correctly without a custom dictionary, and setting that up takes longer than just fixing the exceptions by hand. If I have a list with "PH," "BTU," "NASA," "iPhone," or any brand that has its own weird capitalization rules, I make a pass at the end to fix those manually.

Fifteen exceptions out of five hundred rows is a reasonable tradeoff. The tool does 97% of the work; I do 3%. Before I knew about these tools, I was doing 100% of the work and doing it slower and introducing more errors.

The spreadsheet that started all this took me a total of about three and a half hours the hard way. I've since redone a similar migration — different client, different data, roughly the same volume — in twenty minutes. Same task. Completely different experience.

The cold coffee on my desk that Tuesday would have appreciated me figuring this out sooner.