TEXT GUIDES
Guides for everyday text
Thirteen practical explainers for the situations behind the buttons: text copied from a PDF that arrives with broken lines, lists that contain repeats, headings with inconsistent capitalization, spreadsheets that need normalizing, and characters you cannot see. Each guide states the rule first, then the action.
Every guide is written by the same developer who builds the tool, so the described behavior matches what the buttons actually do. Start with the problem you have, or browse by category below.
Case
Choosing between sentence case and Title Case
The conventions behind sentence case, Title Case, uppercase and lowercase, and what an automatic converter can and cannot decide for you.
Title Case across style guides: AP, Chicago, APA and Wikipedia
Where the major title-case rules agree, where they diverge, and how to reconcile an automatic conversion with the guide you follow.
Lists
Removing duplicate lines from a list
Where duplicate list entries come from, what exact-duplicate matching means, and how to remove repeats while keeping the first occurrence.
Sorting lines and when ordering helps
Alphabetical sorting, the comparison the browser actually uses, the traps with numbers and accents, and when reversing order beats sorting.
Sort or reverse: choosing the right list operation
A decision guide for two operations that look similar and do very different things to the meaning of a list.
Spacing
Cleaning text pasted from PDFs, email and web pages
Why pasted text arrives with broken line breaks and double spaces, and how to clean spacing and blank lines without retyping a word.
Removing blank lines without breaking your document
What counts as a blank line, which blank lines carry meaning, and why one sometimes survives when you expected it to disappear.
Counting
Counting words, characters and lines accurately
How character, word and line counts differ, what each is used for, and where naive counting tools disagree with each other.
Word counts for essays and for web content
The word-count targets people actually work to, the counting conventions that change the number, and how to cut or expand a draft without losing meaning.
Data
Cleaning CSV-style data at the line level
What a line-based text tool can safely fix in a CSV file, what needs a real spreadsheet, and why quoted fields break line-level cleaning.
Normalizing text before it goes into a database
The case, spacing and format rules worth applying to a field before import, and the fields where normalizing would destroy the data.
Unicode
Unicode, emoji and why identical-looking text is not identical
Code points versus bytes, why one emoji can be several characters, and the normalization trap that makes two identical-looking lines fail to match.
Invisible characters: the whitespace that is not a space
Non-breaking spaces, zero-width characters and soft hyphens — what each one does, which ones this tool removes, and how to find them.