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.", room = "Fuller Hall" and time = "2:00 PM" sorted by time descending

View and edit SQL

time

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 7.257ms · Data source: https://csvconf.com/