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fivethirtyeight
data
Jupyter Notebook2014–2024
fivethirtyeight / data

data

Data and code behind the articles and graphics at FiveThirtyEight

Creative & Media
Explore on GitHubRead Hacker News discussions
14Distinct people
14Mentions
0Explicit recommenders
17.5KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Data and code behind the articles and graphics at FiveThirtyEight

GitHub

Where it is used

No documented product use was verified in the last source check.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 2:04:58 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year14 dated mentions

Observed mentions: 2014-05-21 11:29:45 UTC to 2024-11-22 19:44:56 UTC.

02462014-01-01 00:00:00 UTC to 2015-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments20142015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 3 mentions; 1 submissions, 2 comments2017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 6 mentions; 1 submissions, 5 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20192020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2024

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20142014-01-01 00:00:00 UTC2015-01-01 00:00:00 UTC110
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC000
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC312
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC615
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC101
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC000
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC101
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC000
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC000
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC202

What Hacker News says

6 sources
simonw·Nov 14, 2017
A couple of demos: https://fivethirtyeight.datasettes.com/ contains SQLite versions of every CSV published by the FiveThirtyEight crew to https://github.com/fivethirtyeight/data I built a separate tool on top of pandas which can mass-convert CSVs to SQLite - https://github.com/simonw/csvs-to-sqlite - so building the database for https://fivethirtyeight.datasettes.com/ is now a one-liner: csvs-to-sqlite ~/fivethirtyeight/data fivethirtyeight.db https://parlgov.datasettes.com/ uses the SQLite database from http://www.parlgov.org/ - this is a more interesting demo as it includes things like SQL views - e.g. https://parlgov.datasettes.com/parlgov/view_election Both of these demos are served through Cloudflare - since the URL to each database incorporates a sha256 hash of the database contents, I can send a far-future cache expiry header
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on everything.
In Show HN: Datasette – Create and publish an API for SQLite databases
danso·Mar 28, 2017
I've worked as a journalist in which my (and many other data journalists') modus operandi was to publish the data. Often because the data was public record anyway. I now work in academia and the mentality is significantly different. Some of it is logistics -- I would say most traditional news organizations do not have the internal incentive or habit to figure out a way to publish data. Whereas with newer organizations, such as 538 [0] and Buzzfeed News [1], the data teams have editors to whom open-source and digital publishing is more the natural way of things. But in academia, there are also set rules and precautions governing every study. I haven't proposed any research yet but my understanding is that if your study requires collecting data from participants, the Institutional Review Board requires you to be very clear to participants a
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bout privacy and confidentiality and that you follow the guidelines to the letter. Additionally, there are datasets only available to academics that aren't available to non-academics (i.e. journalists), which speaks to the expectation that academics be very mindful about confidentiality promises. [0] https://github.com/fivethirtyeight/data [1] https://github.com/BuzzFeedNews/everything
In A researcher's response to people pointing out 150 errors in four of his papers

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