Numbers Around Us

A field guide to thinking with data

Beyond numbers.
Into meaning.

Practical ideas for people who write code, build dashboards, and ask better questions of their data.

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01

Data Science

From messy inputs to readable code.

↗ 02

Business Intelligence

Make your metrics mean something.

↗ 03

Data Philosophy

Question the assumptions underneath.

↗

The notebook

Ideas worth opening.

All articles ↗

Data Science

Business Intelligence

Data Philosophy

Less scrolling. More solving.

Get your hands into the data.

Explore challenge solutions and turn a tricky problem into a clearer way of thinking.

Explore the challenges ↗

# Small steps. Clear intent.
data |>
  tidyr::drop_na() |>
  dplyr::count(category) |>
  dplyr::arrange(desc(n))

# Less noise. More understanding.

The practitioner’s perspective

Good data work starts with better questions.

What does this number mean? Who trusts it? What decision does it support?

Numbers Around Us connects analytical craft with the thinking that makes it useful. For analysts, developers, engineers — and anyone who wants to see past the surface.

Meet the writer on Medium ↗