Files, folders, and file types

Why it matters

A lab notebook export, a CAD drawing, a CSV of sensor readings, a Python script: technical work produces files, and lots of them. If you cannot find last Tuesday's results, or you send a colleague final_v2_REAL.docx instead of the right version, the work slows down and mistakes creep in. Good file habits are one of the easiest professional skills to learn, and people notice them.

The core idea: a tree of folders

Storage is organised as a tree. At the top is a root (C:\ on Windows, / on macOS and Linux). Folders (also called directories) contain files and other folders. The full address of a file is its path:

Windows:      C:\Users\sam\Projects\bridge-survey\data\2026-10-14-strain.csv
macOS/Linux:  /Users/sam/Projects/bridge-survey/data/2026-10-14-strain.csv

Windows uses backslashes \, macOS and Linux use forward slashes /. Programs, scripts and the command line all find files by their path, so where a file lives matters.

File names and extensions

The part after the last dot is the extension. It tells the OS (and you) what kind of data is inside and which program should open it. Turn extensions on so you can always see them: in Windows File Explorer choose View > Show > File name extensions; on macOS go to Finder > Settings > Advanced > Show all filename extensions.

Formats you will meet often:

Plain text vs binary. A .csv or .py file is plain text: open it in any editor and you can read it. A .xlsx or .png is binary: it only makes sense to the right program. Plain text formats are easier to share, compare and keep for years, which is why so much technical data uses them.

Renaming report.pdf to report.docx does not convert it. It only changes the label, and the file will fail to open. To convert, use "Save as" or "Export" in a program.

Worked example: a project folder

Here is a simple layout that works for a course, a lab project or a small analysis:

bridge-survey/
  README.md            what this project is, who owns it, how to use it
  data/
    raw/               original files, never edited
    processed/         cleaned copies made from raw
  docs/
    2026-10-14-site-visit-notes.md
  analysis/
    clean_strain.py
  output/
    2026-10-20-strain-summary.pdf

The rules behind it:

• Keep raw data untouched. Work on copies so you can always start again.
• Date first, in ISO format (YYYY-MM-DD). Files then sort in time order automatically.
• No spaces or special characters. Use lowercase words joined with hyphens or underscores: site-visit-notes.md, not Site Visit Notes (new!!).md. Command-line tools and scripts handle these names without trouble.
• Describe the content, not the version. Avoid final, final2, latest. Use dates, or proper version history (cloud documents and Git, later in this course and in Git & the Command Line).
• A short README tells future-you and teammates what is in the folder.

Backups

Files are lost to dead drives, theft, accidental deletion and ransomware. A common rule of thumb is 3-2-1: three copies of important data, on two different kinds of storage, with one copy off-site (for example a cloud service). At minimum, keep important work in a synced cloud folder or back it up to an external drive regularly. At work, follow your employer's storage rules: client or patient data often may only be stored in approved places.

Common mistakes

• Saving everything to the Desktop or Downloads folder and never filing it.
• Hidden extensions, so invoice.pdf.exe looks like invoice.pdf (a classic malware trick).
• Editing the only copy of raw data.
• Spaces and symbols in names that break scripts later.
• Changing an extension to "convert" a file.

Quick recap

• Files live in a tree of folders; a path is a file's full address.
• Extensions tell you the format. Turn them on.
• Use dated, lowercase, hyphenated names and a standard project layout with a README.
• Keep raw data read-only and back up with the 3-2-1 idea.

Try it

Open the Do tab and set up a real project folder for this course.