bibliography_bursty = html`<table class="bibliography">
<tr><td style="width: 3em;">1805</td><td>Adrien-Marie Legendre, <em>Nouvelles méthodes pour la détermination des orbites des comètes</em> <a href="https://archive.org/details/nouvellesmthode00legegoog/page/n10">archive.org</a><blockquote>Pioneers the method of least squares to balance the errors in astronomical observations; rivals Gauss’s claim to priority.</blockquote></td></tr>
<tr><td>1865</td><td>Gregor Mendel, “Versuche über Pflanzenhybriden” <a href="http://www.gutenberg.org/files/40854/40854-h/40854-h.htm">gutenberg.org</a>; trans. Druery, Bateson and Blumberg “Experiments in Plant Hybridization” <a href="http://www.mendelweb.org/Mendel.html">mendelweb.org</a>
<blockquote>Mendel’s work, establishing the action of dominant and recessive factors through pea plant experiments, languished in obscurity, and he died unknown in 1888. It was unknown to Darwin, who tended to side with Lamarck’s belief that characteristics acquired over a lifetime were inheritable, and to Galton, who doubted that they were. In early 1900, three botanists — the Dutch Hugo de Vries, German Carl Correns, and Austrian Erich von Tschermak — each published their rediscovery of Mendel. This soon settled the debate, demonstrating that inheritable genetic material was fixed at birth and unchanged over a lifetime. Lamarck had offered hope that striving would be passed down biologically; Mendel was taken by eugenicists to mean that it was useless to try to educate people from “poor stock” when the next generation would just have to start over. (<a href="https://en.wikipedia.org/wiki/Transgenerational_epigenetic_inheritance">Epigenetics</a> has since complicated the biological inheritance issue.)</blockquote>
</td></tr>
</table>
`
import {radio, text} from "@jashkenas/inputs"
One platform to build and deploy the best data apps
Experiment and prototype by building visualizations in live JavaScript notebooks. Collaborate with your team and decide which concepts to build out.
Use Observable Framework to build data apps locally. Use data loaders to build in any language or library, including Python, SQL, and R.
Seamlessly deploy to Observable. Test before you ship, use automatic deploy-on-commit, and ensure your projects are always up-to-date.