The question comes first

How does activity change over a year? This starter article uses an invented monthly series to demonstrate the publishing format. It is not a CO³ Labs result, a live feed, or a measurement of real users.

A useful analysis gives the reader a question, a figure, an interpretation, and enough context to challenge the conclusion. The notebook supports that story; it does not have to be the story itself.

Illustrative data · not live

Monthly activity

348example events in Dec
Source: an invented 12-month series included in the notebook. Select a bar or switch the time window. No real-world conclusions should be drawn from these values.

What the figure can tell us

In this constructed series, activity ends higher than it starts and has a small dip midway through the year. The shorter window makes recent changes easier to inspect.

Those observations describe the example. They do not explain a cause. A real post would identify the data source, collection method, missing values, and any changes in how activity was measured.

The reproducible bit

Python · inspect the code
monthly = [120, 145, 138, 182, 205, 194, 238, 260, 247, 302, 325, 348]
change = (monthly[-1] / monthly[0] - 1) * 100
print(f"Change across the example: {change:.1f}%")

Limitations are part of the result

Twelve invented observations cannot establish seasonality, statistical significance, or a causal effect. The percentage calculation is descriptive only.

For a real analysis, publish the input or a documented retrieval method, preserve the environment requirements, and include the steps that produce the chart. Avoid committing credentials or restricted datasets.

Demo coming soonA place for the work in motion.
A short walkthrough can sit alongside the analysis. No demonstration video has been attached to this example yet.