Alex Kraieski

@kraieski.dev

Laravel developer, data scientist, and accessibility advocate 🐘 TALL stack | PostGIS 📈 R + Tidyverse | Shiny NH, USA | Clemson University alum (Poli Sci) DM for freelance/consulting availability or to chat about whatever! https://kraieski.dev

A view out of a window with a black bear standing at the edge between a yard and forest.

A text from my health insurance company offering to let me pay $16 per month towards a $200 prescription

Depiction of vision with the eye condition keratoconus in a photo of times square at night. The depiction shows double vision that makes it hard to concentrate on things

Society if they pivoted to JSlop instead: a futuristic city with flying cars.

Screenshot from a router management screen showing that github telemetry was my most blocked domain in my home network.

Screenshot of Wired headline: OpenAI Backs Bill That Would Limit Liability for AI-Enabled Mass Deaths or Financial Disasters
The ChatGPT-maker testified in favor of an Illinois bill that would limit when AI labs can be held liable—even in cases where their products cause “critical harm.”

Candle chart of the SPY ticket made in R with the following code:

library(quantmod)
library(lightweightchartR)

symbols <- c('VT', 'QQQ', 'XLE', 'DGRO', 'GLD', 'SPY')
getSymbols(symbols, from = "2010-01-01", adjust = TRUE)

# this code here is a second chart not shown in screenshot
lwc_chart(VT, theme = "dark", type = "bar") |>
add_bbands(n = 20, sd = 2) |>
add_volume()

lwc_chart(SPY, theme = "dark") |>
add_bbands(n = 20, sd = 2) |>
add_volume()

Screenshot showing code and a generated negatively correlated scatter plot:

plotjs(x = mtcars$hp, y = mtcars$qsec,
main = "1/4 Mile Time vs. Horsepower",
xlab = "HP",
ylab = "Seconds")

The magic mouse from apple has a changing port on the bottom

A banner over a wood background that reads "Instrument wood texture pack: wood grain patterns from real instruments photographed for your design projects"

A screenshot of an article headline saying that Gen z is playing the economy like a casino.

Screenshot of a WSJ podcast about "for many kids on ADHD pills, it's the start of a drug cascade"

Spotify wrapped showing a top 0.1% fan stat for Metallica

A box for shipping a guitar that says ESP 50th anniversary

NYC mayoral election results for Staten Island. Cuomo 55.4%, Mamdani 22.7%, Silwa 21.3%

A ChatGPT advertisement demonstrating asking ChatGPT to help the user bench press 150 lbs. by the end of the year.

Line chart of homicides in Washington, DC from 2005 to 2024. Although homicides have been rising since 2012, it is unclear that a long-term uptrend exists, and homicides fell off drastically from a high in 2023

an R script being excuted an in an IDE. The plot changes at the end when the AI finishes creating a ggplot2 theme.

Code:
library(ellmer)
library(ggplot2)
library(ggthemeAI)

p <- ggplot(airquality, aes(Day, Temp)) +
geom_point(color = "#0074D9", size = 3) +
geom_smooth(method = "loess", se = FALSE, color = "#FF4136")
p

chat <- chat_anthropic(system_prompt = ggplot2_doc_prompt())

chat$register_tool(tool_list_fonts())

theme_prompt <- "like Doom 1993, pixel aesthetic, blood red highlights. All out Doom."
theme_doom <- make_ai_theme(chat,
theme_prompt = theme_prompt)
p + theme_doom()

Line chart comparing lap times of Russell (cyan) and Verstappen (orange) during the 2025 Canadian Grand Prix. Lap times are mostly similar but show sharp spikes for pit stops around laps 12 and 40ish and a safety car at the end.After the first stint, the lap times tend to trend down throughout the race for both.

a histogram with bright colors: Blue, pink, and yellow

screenshot showing part of a website UI with a chart and a sidebar where users can browse through a list of charts to view. On the screen is the "window" where the VoiceOver screenreader shows what it is reading. It demonstrates that the plot is accessible to users who use a screen reader.

a partial screenshot from Google's pagespeed insights with the suggestion "Avoid enormous network payloads." over 6,000 KiB of this is from WebAssembly binaries for R, the statistical programming language.

$screenshot of a code editor showing the following R code: library(quantmod) library(ggplot2) library(lubridate) startYear <- 2015 startDate <- paste0(startYear, '-01-01') getSymbols(c('spy', 'btc-usd'), from= startDate) # function factory that creates a scale function that only shows valid years. # try to keep code that could change in here! make_valid_year_scale_function <- function(start_year){ function(){ list( scale_x_continuous(breaks = seq(start_year, Sys.Date() |> year(), 1)), theme(panel.grid.minor.x = element_blank()) # use function after other theme funcs ) } } # this makes it so I can add scale_x_valid_years() to any plot scale_x_valid_years <- make_valid_year_scale_function(startYear)$

Lastly, RStudio now uses the RStudio project folder as the GitHub Copilot workspace root. Copilot suggestions are now more relevant, utilizing your project folder context.

A screenshot showing a form UI in a CMS for entering R code for data and a plot that will be viewed on the website's fontend

The video depicts a website UI where there is a sidebar menu with a with a selection of plots, and the plot displayed changes as the user selects them in that menu. At the end, the browser developer tools are opened to reveal that a whole bunch of R packages were actually loaded behind the scenes.

A snippet R code to load Donald Trump's "Truths"

library(httr2)

req <- request('https://truthsocial.com/api/v1/accounts/107780257626128497/statuses?exclude_replies=true&with_muted=true')

# change user agent
req <- req_user_agent(req,
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.3")

resp <- req_perform(req)

data <- jsonlite::fromJSON(resp_body_string(resp), flatten = TRUE)

Boxplot comparing Luka Dončić’s free throws attempted per game in 2025 with two teams: the Dallas Mavericks and the Los Angeles Lakers. The Mavericks boxplot is in dark blue, showing a median around 6, with a wider interquartile range and two high outliers near 15 and 16 free throws. The Lakers boxplot is in orange, with a higher median around 9 or 10 and a more compressed distribution overall, extending from about 3 to 13 attempts. This suggests Dončić attempted more free throws per game, on average, when playing for the Lakers compared to the Mavericks.

A color-coded map that attempts to show where on track Liam Lawson and Yuki Tsunoda are fast relative to each other. The color scale shows both as blue, making the map hard to read.

Line chart titled “Sergio Perez Q1 Performance (2021)” with a subtitle: “W/ Liam Lawson 2025 Comparison.” The chart tracks Perez’s Q1 qualifying pace relative to Max Verstappen over 22 races. The y-axis shows Q1 lap time as a percentage of Verstappen’s (from ~99.5% to 101.5%), and the x-axis represents race numbers 1 through 22.

A jagged green line shows Perez’s race-by-race pace. His times mostly range between 100% and 101% of Verstappen’s, with fluctuations and occasional dips below 100%. A black dashed line labeled “Lawson average 2025” sits just above the 101% mark, providing a reference point.

Most of Perez’s Q1 performances in 2021 are faster than the Lawson average, with several races showing Perez within 0.5% of Verstappen’s time. One notable spike (race 11) puts Perez close to Lawson’s 2025 average, but overall, Perez generally qualifies closer to Verstappen.

Line chart titled “RBR #2 Driver Q1 Performance (2019)” showing how Red Bull Racing’s second drivers—Pierre Gasly and Alexander Albon—performed in Formula 1 Q1 qualifying sessions compared to Max Verstappen. The y-axis represents Q1 lap time as a percentage of Verstappen’s time (from 99% to 107%), and the x-axis shows race numbers from 1 to 12.

Gasly’s data points (blue line with dots) appear in races 1–12, showing a fairly consistent performance between 100% and 102.5% of Verstappen’s times, with small fluctuations. Albon’s data (red line with dots) begins around race 5 and overlaps with Gasly between races 5 and 9. Albon has one large spike around race 4 (over 106%), suggesting a notable qualifying deficit in that event. Otherwise, Albon generally performs slightly closer to Verstappen’s times than Gasly.

A black dashed horizontal line is labeled “Lawson average 2025” and is set at about 101.5%, serving as a benchmark for comparison. Most of Albon’s and Gasly’s data points fall below this line, suggesting Lawson (in 2025) was, on average, further from Verstappen’s Q1 pace than either Gasly or Albon in 2019.

A legend below the chart indicates red is for Albon and blue is for Gasly.

A denim jacket with several band patches sewn on. On one side, there's a Metallica "Ride the Lightning." On the other side, there are patches for Rage Against the Machine, System of a Down, and Slipknot

$echo '++++++++++[>++++++<-]>++++++++++++++++++++++++++.+++++++++++++++++++.++++++++++.----------.+++++++++++.------------------------------------------------------------------------------------.+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++.+++++++.-----------------.++++++++.----.++++++++++++++.--------.--.-----------------------------------------------------------.++++++++++++++++++++++++++++++++++++++++++++++++++++++.+.+++++++++++++++++.' | perl -e '$code=<>;@t=(0)x1e4;$p=0;for($i=0;$i<length($code);$i++){$_=substr($code,$i,1);$p++if$_ eq">";$p--if$_ eq"<";$t[$p]++if$_ eq"+";$t[$p]--if$_ eq"-";print chr$t[$p]if$_ eq".";$t[$p]=ord(getc)if$_ eq",";if($_ eq"["){$t[$p]||do{$d=1;do{$i++;$d++if substr($code,$i,1)eq"[";$d--if substr($code,$i,1)eq"]"}while$d}}if($_ eq"]"){$t[$p]&&do{$d=1;do{$i--;$d++if substr($code,$i,1)eq"]";$d--if substr($code,$i,1)eq"["}while$d;$i--}}}'$