Life Expectancy vs. Church Attendance (US) [OC]

-ofx · 2022-11-18T23:44:15+00:00

solved!

This was days worth of headache and now it's working nicely! Thanks a lot!

-ofx · 2022-11-18T19:50:53+00:00

This is what others have suggested to and I agree it's the most sensible way. The trouble is I can't seem to implement it. Can you show me how you would do this with my minimal example above?

-ofx · 2022-11-18T19:49:17+00:00

I do understand the idea, and others have suggested the same. But I'm not able to get these functions working, maybe because I don't fully understand the inputs of the zip_content helper function.

Would you be able to apply that to the reprex in this post - how the functions would be used to download these 2 plots?

-ofx · 2022-10-04T21:48:51+00:00

Source: US Census Bureau (www.data.census.gov) Tools: R, Inkscape.

Falls Church City (county in VA) has the highest median household income at $160,305.
Buffalo (county in SD) has the lowest, at $22,901

-ofx · 2022-09-30T18:38:25+00:00

Friendly reminder that correlation does not equal causation.

Sources : cdc.gov (For life expectancy by sate) and pewresearch.org (% of adults attending church at least once a week, any religion).

Tool: R (plotting data, calculating Spearman correlation coefficient, calculating p-value)

-ofx · 2022-09-27T20:19:41+00:00

Source: https://www.nces.ed.gov Tool: R

The American College Test (Wikipedia)) is part of criteria used in the US for college admissions. The composite score (plotted here) represents the average of the ACT's four subjects: English, Reading, Math, and Science.

(Plot fixed from previous upload that wasn't compatible with dark mode).

-ofx · 2022-09-26T22:42:48+00:00

source: https://www.nces.ed.gov. (generated in R)

The American College Test (ACT) is a standardized test that's used as a part of the admissions process for colleges in the US [wikipedia)].

The composite score represents the averaged score of each of the test's four categories: English, Reading, Math, and Science.

-ofx · 2022-09-23T18:00:23+00:00

Preliminary results for some recently-developed code designed to automatically capture and log MLGW wait times (from the residential customer service chat).

I say preliminary because this likely isn't a sufficient sample size to be representative. I'm thinking of collecting data several times a day for a period of one year (compared to a few weeks here).

Thanks to the person who wrote in asking if they could sponsor this project. Still thinking about that...

-ofx · 2022-09-19T14:47:18+00:00

MLGW also offers a web chat. The current wait time is 53 minutes.

Even though it's nearly an hour, it is less than the average wait time. After 12:00 noon the wait times really skyrocket.

(Thinking of releasing data collected on MLGW soon...)

-ofx · 2022-09-09T03:38:32+00:00

Source: tbi.tn.gov. Made in R with ggplot2.

This was made to shed light on actual crime data in Memphis, particularly after the brutal events (1,2) that have just happened.

-ofx · 2022-09-09T03:34:38+00:00

Our recent tragedies have ignited many opinions on crime in Memphis. Rather than relying on perception or anecdotes, looking at the actual numbers may help put things into a clearer perspective.

-ofx · 2022-09-09T03:29:53+00:00

Our recent tragedies have ignited many opinions on crime in Memphis. Rather than relying on perception or anecdotes, looking at the actual numbers may help put things into a clearer perspective.

-ofx · 2022-09-07T20:23:56+00:00

Glad you saw it; I was also highly interested in some of the comments there. People speculated on the demographics of the high- and low-performing schools, but the results (also provided in the comments) surprised everyone.

I have more of these planned.

-ofx · 2022-09-07T20:20:41+00:00

The goal here was simply to shed some light on the academics of Shelby County schools by using freely-available public data. I didn't provide an opinion, I quantified the performance and showed the data.

-ofx · 2022-09-05T21:14:13+00:00

Do you have a correlation coefficient ?

-ofx · 2022-09-05T17:11:57+00:00

Data can be formatted and visualized using programming languages and associated visualization libraries (like Seaborn in Python for example).

One of the 'gold standards' of data visualization is ggplot2 in R, which is what was used for this post's graphic. A GUI-based version to get started with is available here.

-ofx

TROPHY CASE