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On May 6, 2021 1:13:16 PM PDT, Jeff Reichman wrote:
>R-help
>
>Never mind I figured out a working solution
>
>- remove duplicate
>- mutate a new column == 1
>- spread the data from long to wide
>- replace NA with 0's
R-help
Never mind I figured out a working solution
- remove duplicate
- mutate a new column == 1
- spread the data from long to wide
- replace NA with 0's
Not sure it’s the most elegant but gets the gob done
-Original Message-
From: R-help On Behalf Of Jeff Reichman
Sent: Thursday,
On Mon, Aug 20, 2018 at 2:17 PM David Doyle wrote:
>
> Hello everyone,
>
> I'm trying to generate tables of my data out of R for my report.
>
> My data is setup in the format as follows and the example can be found at:
> http://doylesdartden.com/R/ExampleData.csv
>
> LocationDateYe
d L. Carlson
Department of Anthropology
Texas A&M University
-Original Message-
From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of Rui Barradas
Sent: Monday, August 20, 2018 11:39 PM
To: David Doyle ; r-help@r-project.org
Subject: Re: [R] Transforming data for nice output table
Sor
Sorry, there is no need to subset the data frame,
reshape2::dcast(dta, etc)
will do the same.
Rui Barradas
On 21/08/2018 05:10, Rui Barradas wrote:
Hello,
One of those would be with package reshape2.
dta <- read.csv( "http://doylesdartden.com/R/ExampleData.csv";)
subdta <- dta[, c("Locat
Hello,
One of those would be with package reshape2.
dta <- read.csv( "http://doylesdartden.com/R/ExampleData.csv";)
subdta <- dta[, c("Location", "Year", "GW_Elevation")]
res <- reshape2::dcast(subdta, Location ~ Year, value.var = "GW_Elevation")
names(res)[-1] <- paste("GW_Elevation", names
If departing from base R into contributed territory, tidyr::spread is
well-suited to this.
library(dplyr)
library(tidyr)
dta <- read.csv( "http://doylesdartden.com/R/ExampleData.csv";
, header = TRUE
, as.is = TRUE
)
result <- ( dta # starting with
Hi David,
As you want the _values_ of Year from the initial data frame appended
to the _names_ of GW_Elevation, you can't do it the easy way:
dddf<-read.table(text="LocationDateYear GW_Elevation
127(I)5/14/2006 2006 752.46
119(I)5/14/2006 2006
Hello,
This is a very frequent question.
I could rewrite one or two answers taken from StackOverflow:
https://stackoverflow.com/questions/5890584/how-to-reshape-data-from-long-to-wide-format
But there you will have more options.
Hope this helps,
Rui Barradas
On 20/08/2018 20:17, David Doyl
On Apr 25, 2012, at 10:57 AM, Carly Huitema wrote:
Hello R-help list,
I would really appreciate help with my factoring problem.
My generated data is this:
df <- expand.grid(T=seq(10,80, by=5), conc=rep(c(1, 3, 7), 2))
df$curve <- as.factor(rep(1:6, each=length(seq(10,80, by=5
df$count
try this: (uses 'ave')
> df <- expand.grid(T=seq(10,80, by=5), conc=rep(c(1, 3, 7), 2))
> df$curve <- as.factor(rep(1:6, each=length(seq(10,80, by=5
> df$counts <- 3*df$T/df$conc + rnorm(df$T,0,2)
>
> plot(counts~T, df)
> df$zero <- ave(df$counts, df$curve, FUN = function(x) x - min(x))
>
> d
Mcdonald, Grant wrote:
>
> Dear sir,
>
> I am fitting a glm with default identity link:
>
>
>
> model<-glm(timetoacceptsecs~maleage*maletub*relweight*malemobtrue*femmobtrue)
>
> the model is overdisperesed and plot model shows a low level of linearity
> of the residuals.
>
> >> I don't
Here are some examples of the transformations that you can do:
> x <- 1:6
> x
[1] 1 2 3 4 5 6
> (z <- matrix(x, ncol=2, byrow=TRUE))
[,1] [,2]
[1,]12
[2,]34
[3,]56
> as.vector(z)
[1] 1 3 5 2 4 6
> as.vector(t(z))
[1] 1 2 3 4 5 6
>
On Sun, Mar 23, 2008 at 8:12 AM, jen
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