>- 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, May 6, 2021 2:37 PM
>To: R-help@r-project.org
>Subject: [R] Transforming data
>
>R Help F
rsday, May 6, 2021 2:37 PM
To: R-help@r-project.org
Subject: [R] Transforming data
R Help Forum
I am attempting to transform the data frame in Table 1 to the form shown in
Table 2. Any suggestions. I ve started by removing duplicate rows
Jeff
Table 1
Taxon
Importer
Guarouba gua
R Help Forum
I am attempting to transform the data frame in Table 1 to the form shown in
Table 2. Any suggestions. I�ve started by removing duplicate rows
Jeff
Table 1
Taxon
Importer
Guarouba guarouba
AE
Acipenser gueldenstaedtii
AE
Caiman crocodilus fuscus
AE
Caiman croc
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
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
LocationDateYear GW_Elevation
127(I)5/14/2006 2006 752.46
Hi everyone,
I´m a student and relatively new to R so apologies in advance if this
question seems stupid or obvious to you.
I have collected a dataset with about 60 species of diatoms (count data from
19 different sample sites) and environmental variables for each site
(salinity, pH, etc.). It´s al
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
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$curve <- as.factor(rep(1:6, each=length(seq(10,80, by=5
df$counts <- 3*df$T/df$conc + rnorm(df$T,0,2)
plot(counts~T, df)
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
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. The overdispersion and linearity of residulas on the normal Q-Q
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
My data look like this:
Col1
1
2
3
4
5
6
...
My questions are:
(1) How do I get it in the following format?
Col1 Col2
12
34
56
...
(2) How do I transform the data in 2 column format above back to the single
column format?
Thanks in advance for your reply!
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