home / csvconf

talks

Data source: https://csvconf.com/

1 row where abstract = "Journalists don’t write for other journalists—they write for the curious and community-minded public. In the same way, statistical journalism should not be a black box of visualizations and narrative meant only for data makers like us. Crafting data-driven stories for a general audience means giving readers an opportunity to interact with a fun and practical use case while explaining the interpretative thinking that lies under the hood of statistical methods. I am an undergraduate at Cal Poly that writes and builds interactive, data-driven publishings with a team of students. I'll walk you through how we ideate fascinating questions, make methods explainable, and use Jupyter Notebooks to share reproducible code." sorted by datetime descending

View and edit SQL

speaker

day

datetime

abstract

Link rowid title speaker time day room url datetime ▲ abstract image
44 Crafting Data-Driven Stories for the Everyday Reader Marisa Aquilina 2:00 PM May 9 2019 Fuller Hall https://csvconf.com/speakers/#marisa-aquilina 2019-05-09T14:00:00 Journalists don’t write for other journalists—they write for the curious and community-minded public. In the same way, statistical journalism should not be a black box of visualizations and narrative meant only for data makers like us. Crafting data-driven stories for a general audience means giving readers an opportunity to interact with a fun and practical use case while explaining the interpretative thinking that lies under the hood of statistical methods. I am an undergraduate at Cal Poly that writes and builds interactive, data-driven publishings with a team of students. I'll walk you through how we ideate fascinating questions, make methods explainable, and use Jupyter Notebooks to share reproducible code. https://csvconf.com/img/speakers-2019/maquilina.jpg

Advanced export

JSON shape: default, array, newline-delimited

CSV options:

CREATE TABLE [talks] (
   [title] TEXT,
   [speaker] TEXT,
   [time] TEXT,
   [day] TEXT,
   [room] TEXT,
   [url] TEXT,
   [datetime] TEXT,
   [abstract] TEXT,
   [image] TEXT
)
Powered by Datasette · Query took 12.192ms · Data source: https://csvconf.com/