Lint Roller? I Barely Know Her

JVL
2025 on Tumblr: Trends That Defined the Year
Three Goblin Art

@theartofmadeline
Misplaced Lens Cap

JBB: An Artblog!
wallacepolsom
todays bird
Xuebing Du
One Nice Bug Per Day
Sweet Seals For You, Always

tannertan36
"I'm Dorothy Gale from Kansas"

Kaledo Art
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Andulka
he wasn't even looking at me and he found me
trying on a metaphor
Jules of Nature
seen from United States
seen from United Kingdom
seen from Germany
seen from United States

seen from United States

seen from Türkiye
seen from Australia
seen from Australia
seen from United States
seen from United Kingdom

seen from United States

seen from United States

seen from United States
seen from Japan
seen from Malaysia
seen from United States
seen from Bangladesh
seen from United Kingdom
seen from United States

seen from Malaysia
@colinansel
https://www.instagram.com/lukerenoe/?hl=en
Two dirt rides a week. Sullivan, Nike tower, down Mandeville fire road. This #wearespooky is incredible, great climbing, stiff yet ultra comfortable, loves mud, ruts, gravel, birms, descending, and all the other things. I am so happy with this build. Thank you Spooky Cycles
Spooky Cycles, handmade custom aluminum bicycles by Frank the Welder and Made in the USA
New bike day. Spooky
Distribution of 2FA codes.
My brain has been playing tricks on me for the last few years. I had come to the conclusion that I had seen many of the 2FA codes before. A few minutes later with R and GGPLOT. I believe my assumptions about repeated 2FA codes have been debunked.
I collected all 2FA codes sent to me for the last year.
wc -l Codes.txt
383 Codes.txt
2FA codes delivered to me are always 6 digits. Over the last ~year, I have received 383 2FA codes from my bank
Using egrep to collect the codes from erroneous text
Getting these out of the collected file is easy with egrep.
EG: cat Codes.txt | egrep -o ‘[0-9]{6}’
reading these into R is trivial via “read table”
read.table("~/codes.txt")
converting to a data frame
2fa_TABLE <- as.data.frame(table(as.numeric(strsplit(as.character(read.table("codes.txt")), "")[[1]])))
Applying column names to the data frame
colnames(2fa_TABLE) <- c("Number", "Unique_Count")
Plotting with GGPLOT
ggplot(2fa_TABLE) +
geom_histogram(aes(x=Number, y=Unique_Count), stat="identity") +
theme_bw()
The Plot
https://en.wikipedia.org/wiki/Eurasian_blue_tit
http://icecreamsandwichcomics.com
Fuel for the day