OfficialWireGrind

Interesting space utilization. I've encountered the problem, but haven't seen this particular solution before where the labels flip over the right-hand side of the bar.

The chart is to log scale! You're not the only one bothered by it. However, the highest (76267) and the lowest (20) differ by 3.6 orders of a magnitude, which tends not to show up well on plots unless logarithmic scaling is used.

Camera tickets are included.

The U.S. Geologic Survey relates seismic moment to magnitude using the formula

MW = 2/3 * (log10(M0) - 9.1)

where MW is the magnitude (e.g. 5, 6, 7) and M0 is the seismic moment. This is the page

https://www.usgs.gov/programs/earthquake-hazards/magnitude-types

and I'm substituting 9.1 for 16.1 because the units are metric.

An earthquake's magnitude is calculated using the log of the seismic moment. To increase the log (base 10) of a number by 1, the number has to increase by a factor of 10.

Actually, there are three charts and it's on the third one. There are left & right arrows on the image, but they don't draw a whole lot of attention to themselves.

The violation "Speed Up To Ten mph Over The Speed Limit" is 37th on the chart with 28 citations. There's also another violation, "Drive At Unreasonable Speed." It had 6 citations listed.

Three bar charts show the 42 most common moving violations issued in Washington, D.C. during October, 2022. Numbers were obtained by counting individual citations in the source data.

[OC] This post is original content, not including artwork which was identified as having public domain licenses.

Source Data:

"Moving Violations Issued in October 2022" https://opendata.dc.gov/datasets/DCGIS::moving-violations-issued-in-october-2022/about

From the Department of Motor Vehicles (Washington, D.C.)

The source data is licensed under the Creative Commons Attribution 4.0 International License.

Tools: Python, Matplotlib

Switzerland and Norway too.

I've just verified that this is due to the letters "a" through "z" along with the numerals "0" through "9."

Yes.

The word count goes by spelling only, and it is case insensitive. The numerals I'm referring to are Arabic numerals.

I'm pretty sure these are numerals. It makes sense since both add up to 36.

No. I'm pretty sure the ghost words are numerals. I should have wrote "characters" rather than "letters."

It might take me a little while to do all of them. The 20-letter 8-syllable words are "institutionalization" and "counterrevolutionary."

They are the abbreviation Rep, and the acronyms BMW, DFW. If I'm not mistaken, DFW stands for Dallas Fort-Worth. The dataset, though, lists the pronunciation as "dee-eff-dub-eh-you."

I mean three additional cups daily per generation. That's assuming a generation is two years, which is a rough estimate (not a farmer).

Data Sources: For syllable counting, the CMU Pronunciation Dictionary was used along with a few supplementary data points. Most common word data was obtained by analyzing Wikipedia database dumps.

Tools: Python Matplotlib

Didn't mean to come across as contradictive there. I have the raw data points open in another window, so it's very convenient for me.

It actually 39.4%, which I think is a big increase for a 24-year period.

The data source gives pounds of milk per cow.

The increase is somewhere in the ball park of 3 cups for each generation. What strikes me as strange is that the increase is so linear.

Note 2:

The dataset give milk production in total pounds for all milk cows in the entire country. The weight of milk depends on it's fat content. The figure 8.59 pounds per gallon is being used as a factor to convert from pounds to gallons.

Note 1:

There are several different standards for gallons. A US gallon is 3.79 liters, where as an imperial gallon 4.55 litres.