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zx8754

@zx8754.bsky.social

Analysis - Data - Analysis - Data - Volleyball - Father - #rstats #STEM #ProstateCancer

161 Posts146 Follower 982 Folgt

zx8754 @zx8754.bsky.social · last mo.

I was today years old when I learned base #Rstats has a helper function `example()`. Better late than never, and it's only been half a three decades give or take ...

Dirk Eddelbuettel@eddelbuettel.com · last mo.

I was today years old when I learned base #Rstats has a helper function `data.matrix()`. Better late than never, and it's only been three decades give or take ...

example(data.matrix) and head(data.matrix(penguins))

> example(data.matrix)

dt.mtr> DF <- data.frame(a = 1:3, b = letters[10:12],
dt.mtr+ c = seq(as.Date("2004-01-01"), by = "week", length.out = 3),
dt.mtr+ stringsAsFactors = TRUE)

dt.mtr> data.matrix(DF[1:2])
a b
[1,] 1 1
[2,] 2 2
[3,] 3 3

dt.mtr> data.matrix(DF)
a b c
[1,] 1 1 12418
[2,] 2 2 12425
[3,] 3 3 12432
>
> head(data.matrix(penguins))
species island bill_len bill_dep flipper_len body_mass sex year
[1,] 1 3 39.1 18.7 181 3750 2 2007
[2,] 1 3 39.5 17.4 186 3800 1 2007
[3,] 1 3 40.3 18.0 195 3250 1 2007
[4,] 1 3 NA NA NA NA NA 2007
[5,] 1 3 36.7 19.3 193 3450 1 2007
[6,] 1 3 39.3 20.6 190 3650 2 2007
>

zx8754 @zx8754.bsky.social · 9mo ago

#rstats plot of the day - "Listogram" by r2evans stackoverflow.com/a/79808261/6...

listogram plot - Histogram of three-letter words, with the words themselves shown on the plot.

zx8754 @zx8754.bsky.social · 10mo ago

"my default assumption is nothing is going to work" - @clauswilke.com

quote from the linked post: "my default assumption is nothing is going to work"

https://blog.genesmindsmachines.com/p/we-still-cant-predict-much-of-anything

zx8754 @zx8754.bsky.social · 10mo ago

set.seed((\(x) sum(x %% 10) + length(x))(as.integer(charToRaw("Forty-two")))) #rstats

Claus Wilke@clauswilke.com · 10mo ago

We need to have a conversation about random seeds. Don't use 42. blog.genesmindsmachines.com/p/if-your-ra...

The Institute of Cancer Research @icr.ac.uk · 10mo ago

Men with BRCA1 and BRCA2 mutations should get annual #ProstateCancer screening. The IMPACT trial finds BRCA1 carriers are 3 times more likely to have aggressive prostate cancers than non-carriers. Results from the international trial shared at @myesmo.bsky.social www.icr.ac.uk/about-us/icr...

zx8754 @zx8754.bsky.social · 10mo ago

#rstats easier to compare the ratios

$Barplots of population change ratios in "Most populous countries in Europe" 2000 vs 2025. R code for the plot: library(data.table) library(ggplot2) library(scales) d <- fread(" Rank,Country,y2000,y2025 1,Russia,146000000,144000000 2,Germany,82800000,84080000 3,Britain,59510000,69550000 4,France,59330000,66660000 5,Italy,57640000,59150000 6,Ukraine,49430000,38980000 7,Spain,40000000,49320000 8,Poland,38650000,38140000") d[, rate := y2025/y2000 ] d[, Country := factor(Country, levels = d[ order(rate), Country]) ] d[, lab := paste0(round(rate, 4), "\n", label_number(accuracy = 0.1, scale_cut = cut_short_scale())(y2025 - y2000)) ] d[, col := as.factor(sign(y2025-y2000)) ] ggplot(d, aes(Country, rate, label = lab, colour = col)) + geom_col(fill = "white", show.legend = FALSE, linewidth = 1.1) + geom_hline(yintercept = 1, colour = "blue", linetype = "dashed") + geom_text(vjust = 1.4, colour = "black") + scale_x_discrete(name = NULL) + scale_y_continuous(name = NULL, breaks = c(0, 1), limits = c(0, 1.3), expand = c(0, 0)) + scale_color_manual(values = c("-1"="red", "1" = "darkgreen")) + labs(title = "Most populous countries in Europe", subtitle = "2000 vs 2025", caption = "Source: @GEOMAPAS.GR | https://bsky.app/profile/simongerman600.bsky.social/post/3m2nz34kzyi27") + theme_minimal() + theme(panel.grid = element_blank()) ggsave("tmp.plot.jpeg", width = 8, height = 6)$

Simon Kuestenmacher@simongerman600.bsky.social · 10mo ago

The largest 25 countries in Europe in 2000 and 2025. Russia still the biggest but shrank by two million people.

zx8754 @zx8754.bsky.social · 11mo ago

#rstats #TIL I knew about tibble::tribble, but just discovered data.table::rowwiseDT. "creates a data.table object by specifying a row-by-row layout. This is convenient and highly readable for small tables."

Create a data.table row-wise
Aliases: rowwiseDT

Keywords:

### ** Examples

rowwiseDT(
A=,B=, C=,
1, "a",2:3,
2, "b",list(5)
)
A B C
<num> <char> <list>
1: 1 a 2,3
2: 2 b 5

You can define a tibble row-by-row with tribble():

tribble(
~x, ~y, ~z,
"a", 2, 3.6,
"b", 1, 8.5
)
#> # A tibble: 2 × 3
#> x y z
#> <chr> <dbl> <dbl>
#> 1 a 2 3.6
#> 2 b 1 8.5

zx8754 @zx8754.bsky.social · 11mo ago

#rstats pipe help, where is this from? I am guessing it is "modify and re-assign". %<+% Google didn't help, Gemini says it is invalid R code or it is a regex. ChatGPT says it is from ggplot, searching GitHub didn't help. But found this function ggplot2::`%+replace%`(), are they related?

zx8754 @zx8754.bsky.social · last yr.

As base::rbind also takes more than two dataframes as input, I expected at least the same from dplyr::bind_rows. And bind_rows handles rownames, factor levels, and mismatched column names better. #rstats

$#list of dfs set.seed(1); listOfDfs <- lapply(1:3, \(i){ mtcars[ sample(1:nrow(mtcars), 4), ]}) #input as list do.call(rbind, listOfDfs) bind_rows(listOfDfs) #input as dataframe rbind(listOfDfs[[ 1 ]], listOfDfs[[ 2 ]], listOfDfs[[ 3 ]]) bind_rows(listOfDfs[[ 1 ]], listOfDfs[[ 2 ]], listOfDfs[[ 3 ]])$

Ben Harrap@bharrap.bsky.social · last yr.

Just in case anyone else also didn't realise this, you only need to use dplyr::bind_rows() once for multiple inputs. As in: df1 |> bind_rows(df2, df3, df4) instead of: df1 |> bind_rows(df2) |> bind_rows(df3) |> bind_rows(df4) Sometimes it pays to read the documentation 😅 #rstats

zx8754 @zx8754.bsky.social · last yr.

I love waffle charts, but this can be done with points. #rstats #ggplot

set.seed(2025)

d1 <- data.frame(expand.grid(1:50, 1:50))
d1$hot <- factor("no", levels = c("no", "yes"))
d1[ sample(seq(nrow(d1)), 1), "hot" ] <- "yes"
d1$time <- factor("before", levels = c("before", "today"))

d2 <- data.frame(expand.grid(1:50, 1:50))
d2$hot <- factor("no", levels = c("no", "yes"))
d2[ sample(seq(nrow(d2)), 100), "hot" ] <- "yes"
d2$time <- factor("today", levels = levels(d1$time))

library(ggplot2)

ggplot(rbind(d2, d1), aes(Var1, Var2, colour = hot)) +
geom_point() +
facet_wrap(vars(time)) +
scale_colour_manual(values = c("no" = "grey90", "yes" = "red"), guide = "none") +
theme_void()

Voilà: Francis Gagnon@chezvoila.com · last yr.

Nice use of a waffle chart to show probability. 📊

zx8754 @zx8754.bsky.social · last yr.

#rstats base ?`$`

$library(dplyr) library(purrr) library(bench) set.seed(42) create_df <- function(rows, cols) { out <- replicate(cols, runif(rows, 1, 100), simplify = FALSE) out <- setNames(out, rep_len(letters, cols)) as.data.frame(out) } results <- press( rows = c(1000, 10000, 100000), cols = c(100, 1000, 10000), { d <- create_df(rows, cols) mark( d$f, d %>% .$f, d %>% pull(f), d %>% pluck("f"), min_iterations = 100 ) } ) ggplot2::autoplot(results)$ bench::mark output plot

Ilya Kashnitsky@ikashnitsky.phd · last yr.

#rstats TIL: if you need to grab one column from a data.frame/tibble as a vector, `purrr::pluck` is roughly an order of magnitude faster than `dplyr::pull`; you only have to quote the column name

Unit: microseconds
expr min lq mean median uq max
purrr::pluck 6.0 7.5 10.29280 8.2 10.8 1827.9
dplyr::pull 56.2 66.9 93.01648 71.3 91.3 9222.4
neval
10000
10000

zx8754 @zx8754.bsky.social · last yr.

In case you are wondering about #rstats base: 1.0.0 = 1195 vs 4.5.0 = 1286

John Holbein@johnholbein1.bsky.social · last yr.

Stata users will get a kick out of this: @statacorp.bsky.social v1.0 (released January 1985) only had these 44 commands. Source: stata-journal.com/sj5-1.html

zx8754 @zx8754.bsky.social · last yr.

#rstats base and purrr alternatives

$df <- read.table(text = "stu_id race1 race2 race3 race4 race5 race6 100 0 0 0 0 0 1 101 1 0 0 0 0 0 102 0 1 0 0 0 1", header = TRUE) f <- function(...){ ix <- which(c(...) == 1) if(length(ix) == 1) ix else 7L } #base apply(df[, -1], 1, f) # [1] 6 1 7 #to create new column #df$race <- apply(df[, -1], 1, f) #purrr pmap_int(df[, -1], f) # [1] 6 1 7 #to create new column # df <- df %>% # mutate(race = pmap_int(select(., -1), f))$

Crystal Lewis@cghlewis.bsky.social · last yr.

I'm often asked to recode multiple dummy coded race variables into a single variable so I thought I would share 2 different ways you might do this in #rstats. I'm sure there are many more ways. 😉

zx8754 @zx8754.bsky.social · last yr.

#rstats

meme:

Her: Babe please stop keeping 173 tabs open
Me: One of them has an R error from 3 weeks ago I'm still debugging

Usili (Talia) 🏳️‍⚧️@usili.bsky.social · last yr.

. @gigansprogress.bsky.social @linkplumeria.bsky.social @sodrock.bsky.social @sharonk.bsky.social

zx8754 @zx8754.bsky.social · last yr.

Use a string in facet_grid to get a "title" facet_grid(dose ~ "len") #rstats #ggplot

ToothGrowth |>
ggplot(aes(x = dose, y = len)) +
geom_boxplot(aes(fill = supp)) +
labs(y = NULL) +
theme_bw() +
facet_grid(dose~"len")

https://stackoverflow.com/a/79597025/680068

zx8754 @zx8754.bsky.social · last yr.

#rstats base and tidy having a chat (this is not a dig to anyone, use whatever works)

$# tidy: count 1s on subset of columns # base: try this colSums(mtcars[, c("vs", "am", "gear", "carb") ] == 1) # tidy: but I don't want quotes... # base: ok, cols by index colSums(mtcars[, 8:11 ] == 1) # tidy: but I want to see column names! # base: ok, let's use expressions colSums(mtcars[, as.character(substitute(list(vs, am, gear, carb)))[ -1 ] ] == 1) # tidy: oh no, too many nested brackets, my head hurts! # base: wrap into a fucntion count_ones_base <- function(data, ...) { colSums(mtcars[, as.character(substitute(list(...)))[ -1 ] ] == 1) } count_ones_base(mtcars, vs, am, gear, carb) # tidy: but I like pipes, weird function names like quos, # and to be loud !! about it !!! # base: ok. library(dplyr) library(tidyr)$

Kelly Bodwin@kellybodwin.com · last yr.

New unhinged #rstats rant about NSE just dropped: 🔗 kbodwin.github.io/paRticles/po... tl;dr - some cute (?) tricks for iterating over unquoted columns see below to skip the stream-of-consiousness blog and go straight to code snippets

zx8754 @zx8754.bsky.social · last yr.

Love it! Borrowing Alex's idea, here is my attempt #rstats #crayon #inkgolf

$library(crayon) # 4 dark blue, 3 lighter blue, 2 pink, 1 red cat( sapply(c("blue4","blue3","blue2","blue1", "royalblue3","royalblue1","cadetblue1", "deeppink3","deeppink1","red3"), \(i) make_style(i)(".")) )$

Alex Selby-Boothroyd@alexselbyb.bsky.social · last yr.

Love this. Here's my attempt at global temperature change, 1850-2024 ✒️⛳️

zx8754 @zx8754.bsky.social · last yr.

#rstats version

Google: rstats a day keeps stata away meaning

AI response: "RStats a day keeps Stata away" is a humorous way of saying that if you regularly use the R statistical programming language, you'll be less likely to rely on Stata, another statistical software package. It implies that consistent practice and knowledge of R can make it your primary tool, reducing the need for Stata.

Greg Jenner (Historian)@gregjenner.bsky.social · last yr.

Someone on Threads noticed you can type any random sentence into Google, then add “meaning” afterwards, and you’ll get an AI explanation of a famous idiom or phrase you just made up. Here is mine

• Al Overview
The idiom "you can't lick a badger twice" means you can't trick or deceive someone a second time after they've been tricked once. It's a warning that if someone has already been deceived, they are unlikely to fall for the same trick again.
Here's a more detailed explanation:
• Licking: "Licking" in this context means to trick or deceive someone.
• Badger: The badger is a wild animal, and the phrase likely originates from the historical sport of badger baiting where dogs were used to harass

zx8754 @zx8754.bsky.social · last yr.

my current state: import #squeakycleandata from #excel to #rstats youtu.be/vxdQov7gses

Please stop sending me your datasets.

YouTube video by Darren Dahly

youtu.be

zx8754 @zx8754.bsky.social · last yr.

#rstats #ggplot version of this interesting approach data and codes are at gist.github.com/zx8754/85d0c...

R ggplot version of alternative to stacked bar plot.

link to code for the plot:

https://gist.github.com/zx8754/85d0c669a3048eb58d7c58a11eaef9a2

Daniel Marsh-Patrick@dm-p.nz · last yr.

I saw a really neat take on an alternative approach for stacked bar charts in #Tableau over on the Flerlage Twins blog. Naturally, I wanted to try it for #VegaLite and #Deneb in #PowerBI, so I wrote up how I might approach it (with some downloadable stuffs): deneb-viz.github.io/blog/stacked...

zx8754 @zx8754.bsky.social · 3y ago

Hello world!