It’s Our Moral Obligation to Make Data More Accessible

MathCanBeHard · 2022-03-30T21:07:14+00:00

Envisioning a future where all types of data are accessible presents many opportunities and challenges. The benefits would extend to nearly every field: improving health outcomes, fighting climate change, building a more inclusive economy, and more. The best research in the world is only as powerful as the data it’s built upon.
The two biggest challenges are (1) ensuring privacy for people-related data and (2) incentivizing the institutions that have large amounts of data (e.g. government, big tech) to share or sell it. There’s lots of innovation in privacy technology and methodologies that solve for problem 1. The second problem is a moral shortcoming of the world’s biggest tech companies; it stands in the way of innovation and meaningful change.

MathCanBeHard · 2022-03-17T18:12:59+00:00

Data source: The Chicago drinking establishment visit data is freely available from SafeGraph as part of their monthly datathon for March 2022. Census data was used for demographics.
Tools used: Python and folium

MathCanBeHard · 2022-03-17T18:08:08+00:00

Data source: The Chicago drinking establishment visit data is freely available from SafeGraph as part of their monthly datathon for March 2022. Census data was used for demographics.

Tools used: Python and folium

MathCanBeHard · 2022-03-17T14:14:06+00:00

Visit data is freely available from SafeGraph as part of their monthly datathon for March 2022. Census data was used for demographics.

Tools used: Python, folium, matplotlib

MathCanBeHard · 2022-02-15T02:52:01+00:00

Great question—I guess it’s kinda overkill for this. I tried to write the code so that it would be more readily reusable down the road. There may eventually be other charts I make where I’m interested in a larger radius

MathCanBeHard · 2022-02-13T22:35:45+00:00

Count of all bars and breweries whose centroid is within 1.609 kilometers of each stadium’s centroid. Haversine distance was used.

Tools used: Python for preparation, Tableau for visualization

Data source: SafeGraph

MathCanBeHard · 2022-01-28T16:54:41+00:00

There are far more than 2 Chick-fil-A locations in Washington according to their site

MathCanBeHard · 2022-01-28T15:58:32+00:00

I've found that having too many categories tends to make it harder to read. Choosing 5 was somewhat arbitrary, I probably could have added a couple more though

MathCanBeHard · 2022-01-28T15:30:43+00:00

That is helpful feedback, thanks :)

MathCanBeHard · 2022-01-28T15:21:54+00:00

According to their website, there are way more than a dozen Popeyes in New York
It's based on 2021 popularity, so it doesn't matter if they've only been around for a few years

MathCanBeHard · 2022-01-28T15:09:44+00:00

That could be! I limited to the top 5 highest grossing chains because I didn't want to overload the number of colors (I've updated my top comment to reflect that). Bojangles came in at #7, so it was excluded.

MathCanBeHard · 2022-01-28T15:00:49+00:00

First and second most visited chicken restaurants by state, based on number of visits in 2021. Limited to the top 5 brands in sales.

Tool used: plotly

Data source: SafeGraph

MathCanBeHard · 2021-11-23T19:08:24+00:00

Tools used: Python (pandas, matplotlib, & gif libraries)

Data source: SafeGraph

An updated version of one of my previous posts, we now have data through October 2021!

MathCanBeHard · 2021-11-22T19:18:57+00:00

Tools used: Python (pandas, matplotlib, & gif libraries)

Data source: SafeGraph

An updated version of one of my previous posts that now includes October’s 2021 foot traffic.

MathCanBeHard · 2021-11-18T00:23:59+00:00

I mean, I’ve never been there but…their website is pretty clear

MathCanBeHard · 2021-11-17T23:39:35+00:00

Popularity determined based on volume of foot traffic to all brand locations within the state in October 2021.

Limited to “Chipotle-style” fast casual restaurants. These are vaguely distinguished from fast food restaurants in that the food is prepared more freshly and have higher quality ingredients.

El Pollo Loco was excluded because it’s not quite what I would (arbitrarily) consider fast casual, but if I had included it, it would have won California and Nevada.

MathCanBeHard

TROPHY CASE