similar to: Create new data frame with conditional sums

Under the hood, sapply() is also a loop (at the interpreted level). As is lapply(), etc. -- Bert On Sun, Oct 15, 2023 at 2:34?AM Jason Stout, M.D. <jason.stout at duke.edu> wrote: > > That's very helpful and instructive, thank you! > > Jason Stout, MD, MHS > Box 102359-DUMC > Durham, NC 27710 > FAX 919-681-7494 > ________________________________ > From: John

Well, here's one way to do it: (dat is your example data frame) Cutoff <- seq(0, .15, .01) Pop <- with(dat, sapply(Cutoff, \(p)sum(Totpop[Pct >= p]))) I think there must be a more efficient way to do it with cumsum(), though. Cheers, Bert On Sat, Oct 14, 2023 at 12:53?AM Jason Stout, M.D. <jason.stout at duke.edu> wrote: > > This seems like it should be simple but I

This seems like it should be simple but I can't get it to work properly. I'm starting with a data frame like this: Tract Pct Totpop 1 0.05 4000 2 0.03 3500 3 0.01 4500 4 0.12 4100 5 0.21 3900 6 0.04 4250 7 0.07 5100 8 0.09

Dear Jason, The code could look something like: dummyData = data.frame(Tract=seq(1, 10, by=1), ?? ?Pct = c(0.05,0.03,0.01,0.12,0.21,0.04,0.07,0.09,0.06,0.03), ?? ?Totpop = c(4000,3500,4500,4100,3900,4250,5100,4700,4950,4800)) # Define the cutoffs # - allow for duplicate entries; by = 0.03; # by = 0.01; cutoffs <- seq(0, 0.20, by = by) # Create a new column with cutoffs dummyData$Cutoff

If one makes the reasonable assumption that Pct is much larger than Cutoff, sorting Cutoff is the expensive part e.g O(nlog2(n) for Quicksort (n = length Cutoff). I believe looping is O(n^2). Jeff's approach using findInterval may be faster. Of course implementation details matter. -- Bert On Mon, Oct 16, 2023 at 4:41?AM Leonard Mada <leo.mada at syonic.eu> wrote: > > Dear

Dear Jason, I do not think that the solution based on aggregate offered by GPT was correct. That quasi-solution only aggregates for every individual level. As I understand, you want the cumulative sum. The idea was proposed by Bert; you need only to sort first based on the cutoff (e.g. using an ordered factor). And then only extract the last value for each level. If Pct is unique, than you

Después del "gather()" puedes hacer un "arrange()" que es una ordenación. Y dentro de "arrange()" le indicas la variable por la que ordenas (no hacen falta comillas)... Lo ordenará alfabéticamente. Saludos, Carlos Ortega www.qualityexcellence.es El mar., 19 feb. 2019 a las 13:47, Antonio Rodriguez Andres (< antoniorodriguezandres70 en gmail.com>) escribió:

Dear R-users, I am trying to add some text in a textbox to all panels in the following example file. Using the panel-function, I can add a white rectangle with panel.rect but then I have to fit in the text into the box by hand and it will not automatically be centered. Does anyone know how to add the text centered with a white box around it automatically? Is there something like panel.textbox for

> gather(pobla, key = year, value = totpop, year60:year63) Country year totpop 1 Afghanistan year60 8996351 2 Albania year60 1608800 3 Algeria year60 11124888 4 Andorra year60 13411 Gracias Carlos Antonio On Tue, 19 Feb 2019 at 12:54, Carlos Ortega <cof en qualityexcellence.es> wrote: > Sí, tienes varias formas. > > Mira la función

Hi All, I'm hoping someone can help me with a relatively simple problem. Take the following dataset: ID Diabetes ESRD HIV Contact 1 0 0 NA 0 2 1 0 NA 0 3 NA 1 0 0 4 0 NA 0 1 5 1 1 1 0 I want to generate a

https://bugzilla.mindrot.org/show_bug.cgi?id=937 Patric Stout <patric.stout at gmail.com> changed: What |Removed |Added ---------------------------------------------------------------------------- CC| |patric.stout at gmail.com --- Comment #1 from Patric Stout <patric.stout at gmail.com> 2011-09-10

Estimados miembros de la comunidad de R Tengo el siguiente formato en un fichero csv que corresponde a datos de la población para un conjunto de países y para un rango amplio de años. Pais 1960 1961 1962 1963 Albania vvvvv vvvv Algeria vvvvv vvvv Me gustaría pasarlo a la siguiente forma Pais Año Poblacion Albania 1960 vvv Albania 1961 vvvv Albania

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I have population data (?totpopE?) at the census tract level (?GEOID?), which are nested within Precincts (?Precinct?). Please see below my data structure. I used the code to sum population data per precinct: inters <- inters %>% group_by(Precinct) %>% mutate(TotalPop = sum(totpopE) ) However, said code produced too large sums because each census tract (?GEOID?) has multiple

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