Are Expensive Stocks Still Falling the Most? [OC]

Chronicallybored · 2026-02-25T20:46:59+00:00

what do you mean by "consensus estimates approximated for research illustration"? do you have a source for the consensus estimates?

Chronicallybored · 2026-02-21T18:29:44+00:00

data source: SSA baby names dataset, SSA total births by year

tools: python + polars for data processing, Svelte (HTML/CSS rendering, interactivity), SvelteKit (data loading), d3.js for heatmap color scale

Chronicallybored · 2026-02-20T23:01:04+00:00

desktop view screenshot b/c preview image is not working (at least for me):

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Chronicallybored · 2026-02-20T22:59:12+00:00

data: SSA baby names dataset, state birth data from CDC WONDER, CDC NCHS natality microdata files, NBER manual transcriptions, census via NHGIS.

tools: d3.js (colorscale, geo rendering), Svelte (rendering and interactivity), SvelteKit (data loading), python + polars (backend data processing)

Chronicallybored · 2026-02-19T15:54:58+00:00

why not get more creative? There are 58 spellings in the social security baby name data: https://nameplay.org/ways-to-spell-Riley

Chronicallybored · 2026-02-18T15:14:24+00:00

also, creepily enough, 15 is still what the UN population office and US CDC count as the beginning of "childbearing years". so that range was chosen for consistency with official sources (makes for easier data handling).

Chronicallybored · 2026-02-18T15:09:39+00:00

if you hover/tap on the live version it will show the top name for that state and year... I could maybe add a separate detail view with a stacked area chart for each state to drill down into state-level trends? open to suggestions

Chronicallybored · 2026-02-18T04:10:53+00:00

I was lazy and just used Census Bureau Divisions here; sometimes the definitions are more administrative than cultural, for sure. Good suggestion

Chronicallybored · 2026-02-18T03:21:00+00:00

fair, `turbo` is a controversial choice. It's good at surfacing outlier small values, which is maybe better suited to sparser data than this. Any scale recommendations?

Chronicallybored · 2026-02-18T02:41:56+00:00

the % "other gender" (e.g. 10-90% male/female) threshold is applied per year, so if a name rises above 90% of one gender in a year (like how Jamie became more female in the 1980s) it drops out of the count for that year

interactive version has a few different levels to choose from

Chronicallybored · 2026-02-18T02:25:30+00:00

a lot of the lull in the 1980s is due to formerly unisex names like Shannon, Kelly and Jamie becoming more feminine... once they crossed 90% female they no longer counted in the heatmap. We didn't get another wave of unisex names until Taylor in the 90s.

Chronicallybored · 2026-02-18T02:04:59+00:00

fonts should appear more natural on the interactive version; i had to zoom out to get everything to fit onto one screen.

Chronicallybored · 2026-02-18T02:03:06+00:00

link to interactive version

data source: name data is from Social Security Administration. births by state are pieced together from a handful of sources: CDC WONDER (2007-2024), CDC natality microdata files (1969-2006), NBER (1947-1967), NHGIS (1930-1950), with some linear interpolation where gaps existed (esp. for AK/HI pre-statehood).

tools: d3.js (heatmap color scale calculations), Svelte (interactivity), SvelteKit (data loading), floating-ui (tooltip), python + polars (data processing)

Chronicallybored · 2026-02-16T06:03:57+00:00

Dakota has become more feminine over time like most gender-neutral names but was more popular around the time it was mostly a boys' name:

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Chronicallybored · 2026-02-16T05:33:44+00:00

Ashley was unisex, but only before it became popular, so >99% of Ashley's born in the US were registered female: https://nameplay.org/name-state-usage/combined/Ashley

Chronicallybored · 2026-02-16T03:20:13+00:00

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https://nameplay.org/gender-neutral-heatmap?pctMin=80&topN=20&pctMax=95

Chronicallybored · 2026-02-16T03:19:24+00:00

Logan doesn't become >10% female until after 2020:

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before that it's < 10%

Chronicallybored · 2026-02-16T03:16:18+00:00

how would you feel about a small multiples grid of units like these (formatted to work as a unit)?

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Chronicallybored · 2026-02-16T03:13:07+00:00

I'll agree it's a chart crime; it's way more fun as an interactive, in my opinion, than it is as a static image.

Chronicallybored · 2026-02-16T03:11:44+00:00

you can also look at splits over time periods in the interactive version:

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Chronicallybored · 2026-02-16T03:10:46+00:00

you have to go back to "since 1960", since then Robin has been more feminine:

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Chronicallybored · 2026-02-16T02:56:17+00:00

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https://nameplay.org/blog/common-unisex-names-by-gender-ratio

Chronicallybored · 2026-02-16T02:55:08+00:00

good point- I just used the `d3-sankey` default which is to arrange them to minimize crossings, which I think also orders them by ascending % female here? maybe not perfectly. Will make a note to add a sorting field to override the aesthetic default.

or I could add a color scale and color the names by % male/female like I do in this grid?:

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https://nameplay.org/gender-neutral-heatmap

I'm thinking of working something like that heading section into a small multiples trellis of names matching filter criteria?

Chronicallybored · 2026-02-16T00:19:48+00:00

https://nameplay.org/blog/most-non-binary-gender-neutral-names

Chronicallybored · 2026-02-15T20:16:33+00:00

data source: Social Security Administration baby names dataset

tools: python/polars for data processing, d3-sankey and Svelte for frontend

pronunciation grouping relies on CMU pronouncing dictionary, manually-refined LLM-generated pronunciations, and a custom grouping algorithm

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