---
title: "Popcorn analysis"
---

## Quarto

Quarto enables you to weave together content and executable code into a finished document. To learn more about Quarto see <https://quarto.org>.

```{python}
from lets_plot import LetsPlot
LetsPlot.setup_html()
```

Testing plot

```{python}
#| column: page
from notebooks.popcorn import plt_filesize
outp, defs = plt_filesize.run()
outp
```

## Outline

- intro
- filesize
- unique installations reported from
- packages -> perhaps find new subcategories
  - global
  - relative (pkg/unique)
  - top packages
  - rare packages?
  - install distribution
- packages per time unit (find clever title, e.g. 'accumulated packages')
  - per year?
  - weekday
  - month of year (combine with weekday?)
- kernels
  - overall kernel version installations
  - kernels over time

- misc
  - missing days
  - moved days

- things we can't see (limitations)
  - packages on offer in the repositories
    - this could shed light on the bumps of users and relative package ownership
