My R script run with Knitr generates a statistic summary of electrode pairs
accompanied with plots. The problem is that knitr does not render plots in
correct sections. In section for pair A knitr do not wait for plot and
start to evaluate code for output summary for pair B. So in section B knitr
p
> On 06 Jun 2016, at 05:20 , Duncan Murdoch wrote:
>
> On 05/06/2016 2:13 PM, Bert Gunter wrote:
>> Nope, Ted. I asked for a O(log(n)) solution, not an O(n) one.
>
> I don't think that's possible with a numeric vector. Inserting an entry at a
> random location is an O(n) operation, since you
Hi Michu,
What document type do you generate? I usually make just html and have no
problems. If you create a pdf, please remember this is done through LaTeX
and your problem could arise from the floats of LaTeX.
For other output I have no idea.
Hope this helps
Ulrik
Michu Kom schrieb am Mo., 6
Hi
> -Original Message-
> From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of Ek Esawi
> Sent: Sunday, June 5, 2016 2:54 PM
> To: r-help@r-project.org
> Subject: [R] Reading and converting time data via read.table
>
> Hi All--
>
>
>
> I am relatively new to R. I am reading a cs
Hi Doug,
ggplot lets you map variables to aesthetics in a few different ways,
including passing to variable names as strings to aes_string. See
?aes_string for details.
Best,
Ista
On Jun 6, 2016 1:03 AM, "Jim Lemon" wrote:
> Yes, I see what you want. I can't run this myself as my work computer
Hi All,
I merged two datasets:
ds_merge1 <- merge(x = ds_bw_customer_4_match, y =
ds_zww_customer_4_match,
by.x = "customer", by.y = "customer",
all.x = TRUE, all.y = FALSE)
R created a new dataset with the variables customer.x and customer.y. I
would like to merge these two variable back
I am using ChainLadder package for statistical analysis of a run-off triangle
with I=17 and J=14. When I use BootChainLadder() it appears on R console
"Number of origin periods has to be equal or greater then the number of
development periods". But I have origin periods greater then developmen
>
> Hi,
> I have recently made similar scatter plot.
> Suppose you have a data frame "data.csv" and the first column is not
> what you want to plot but rather something informative such as ID, Class,
> Group, etc which might not be your case (but would be very nice if you want
> to color yo
You loop through each
Sent from my iPhone
> On Jun 6, 2016, at 8:29 AM, g.maub...@weinwolf.de wrote:
>
> Hi All,
>
> I merged two datasets:
>
> ds_merge1 <- merge(x = ds_bw_customer_4_match, y =
> ds_zww_customer_4_match,
> by.x = "customer", by.y = "customer",
> all.x = TRUE, all.y = FALSE
You loop through each row but during each iteration you assign a value to the
entire "mismatch" column. The last value assigned was 1.
Sent from my iPhone
> On Jun 6, 2016, at 8:29 AM, g.maub...@weinwolf.de wrote:
>
> Hi All,
>
> I merged two datasets:
>
> ds_merge1 <- merge(x = ds_bw_custome
Hi
Not sure if this is the most effective or general solution but
Here you get 2 if the value is same in both columns, 1 if it is only in one
column and the other is NA and 0 if there is mismatch of values.
temp <- (ds_test[,2] %in% ds_test[,1])+(ds_test[,1] %in% ds_test[,2])
here you get 0 if
On Mon, 6 Jun 2016, Kumar Mainali wrote:
I am trying to use unionSpatialPolygons() of maptools to eliminate sliver
in species range. I want to dissolve tiny sliver polygons in a shapefile to
bigger polygons as "Eliminate (Data Management)" of ArcMap does. Whereas I
can dissolve polygons that hav
X-Originating-<%= hostname %>-IP: [217.155.205.190]
Dear Georg
I find it a bit surprising that you end up with customer.x and
customer.y. Can you share with us a toy example of two data.frames which
exhibit this behaviour?
On 06/06/2016 13:29, g.maub...@weinwolf.de wrote:
Hi All,
I merged
Oh, good point! I was thinking only of the comparisons to identify the
insertion location.
--Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Sun, Jun 5, 20
Hi all,
After fitting a random slope and random intercept model using lme
function, I want
to test whether each of the fixed slopes is equal to zero (The output of
model is below).
Can this be done (testing each individual slope) using multcomp package?
Thanks much for the help.
Hanna
> sum
Hi Michael
it is simple
set.seed(111)
let=sample(letters[1:10],6, replace=T)
dat1<-data.frame(let=let, customer=sample(1:10,6, replace=T))
let=sample(letters[1:10],6, replace=T)
dat2<-data.frame(let=let, customer=sample(1:10,6, replace=T))
merge(dat1, dat2, by.x="let", by.y="let", all=T)
Of cour
Dear All,
I am doing something extremly basic (and I do not claim at all there
is no other way to achieve the same): I have a list of numbers and I
would like to split them up into clusters.
This is what I do: I see each number as a 1D vector and I calculate
the euclidean distance between them.
I
Yes, see ?rle, as Jim indicated.
Just wanted to add that there is an rpy2 package that enables you to
use R within python, which may mean that you do not need to translate
your python code. Or at least not all of it.
Cheers,
Bert
Bert Gunter
"The trouble with having an open mind is that people k
Hi David,
Hi Petr,
many thanks for your help. With your hints I got the idea how I could do
it and I came up with this solution:
-- cut --
#---
# Module: t_merge_variables.R
# Author: Georg Maubach
# Dat
Looking at your overall goal to plot multiple columns, you can use a simple
loop with expand.grid():
> set.seed(42)
> adl1 <- matrix(sample.int(9), 3, 3)
> colnames(adl1) <- letters[1:3]
> lbls <- colnames(adl1)
>
> ncols <- ncol(adl1)
> colnos <- as.matrix(expand.grid(1:ncols, 1:ncols))
> coln
I would probably do it this way,
tmp <- list(data.frame(name="sample1", red=20),
data.frame(name="sample1", green=15),
data.frame(name="sample2", red=10),
data.frame(name="sample2", green=30))
fun1 <- function(df) data.frame(name=df$name, color=names(df)[2],
va
I think your problem is that pvclust looks for clusters between variables and
you have only one variable. When you transpose data_mat, you have a single row
and dist cannot calculate a distance matrix on a single row:
> dist(t(data_mat))
dist(0)
I was going to suggest package NbClust since ther
Thank you, Roger. I cannot fix the upstream processes to eliminate
generation of these problems. So, I need to deal with the data I got.
I tried various online resources including
https://gist.github.com/mstrimas/1b4a4b93a9d4a158bce4 and tried:
setScales()
set_RGEOS_dropSlivers(TRUE)
set_RGEOS_poly
Hanna,
If you are interested in whether effect of time varies across individuals,
why don't you fit a model with the predictors (time*individual) as fixed
effects rather than random?
On Mon, Jun 6, 2016 at 10:57 AM, li li wrote:
> Hi all,
> After fitting a random slope and random intercept mod
Hello specialist,
I have a matrix in which there are NA,0,1 and 2 in each columns.
I wanna replace NAs with special proportion of 0,1 or 2 !
for example in df<- matric(df, nrow=50, ncol=100)
If in one column the number of NAs = 10 , # of 0=50 , #of 1=25 and # of
2=15
I want to replace 5 of 10 N
Maybe you can use something like this
In this way, almost your proportion of 0, 1 and 2 will be maintained
m <- matrix(sample(c(NA, 0:2), size = 50*100, replace = TRUE), nrow = 50,
ncol = 100)
trunc(prop.table(apply(m, 2, table), 2) * colSums(is.na(m)), 0)
m[is.na(m)] <- unlist(apply(trunc(prop.t
AstraZeneca, a leading pharmaceutical company, has an exciting opportunity
for an R-developer within its Quantitative Clinical Pharmacology (QCP)
group. The position is a 6-12 month contract position which will integrate
R programming knowledge, capabilities and prowess towards pharmacometric
analy
Sidenote:
When you do imputation in this way all your inference (error
estimates, goodness of fit, confidence intervals, etc.) will be wrong
and misleading, as you are creating "information" from nothing.
If this comment is irrelevant, please ignore.
Cheers,
Bert
Bert Gunter
"The trouble with h
This should be posted on the r-sig-jobs email list.
Cheers,
Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Mon, Jun 6, 2016 at 3:25 PM, wrote:
> AstraZe
Thanks Evan and Gabriel for the reply. I think it might help me make the
question clearer if I show the data and the model here (I actually asked
questions related to this data before but I still need some help). The data
looks like the following:
response individual time method
1102.9
Hi Michu,
it is not I problem I am familiar with, sorry. Maybe someone else on this
list or at the knirt google group can help you further.
Best,
Ulrik
On Mon, 6 Jun 2016 at 10:36 Michu Kom wrote:
> Hello,
>
> HTML looks much nicer :) ... but still problem is not solved :/ still
> having mixed
Hi Michael,
yes, I was astonished about this behaviour either. I have worked with SPSS
a lot - and that works different.
I would like to share some of my data. Can you tell me how I can dump a
dataset in a way that I can post it here as text?
Kind regards
Georg
Von:Michael Dewey
An:
Hi Petr,
I would like to describe the data situation in brief:
I have an business warehouse dataset (referred to as BW data) containing
sales and an ERP customer master data dataset with additional information
(referred to as ERP data). Though customer IDs and customer names are
identical due
Dear R-list users,
I have the following data frame, called MteBove:
posix_datesnowtemp
...
2010-01-20 23:30:00 45 NA
2010-01-02 00:30:00 10-2.7
2010-01-20 03:00:00 45 NA
2010-01-20 03:30:00 44 NA
2010-01-20 04:00:00 44 NA
2010-01-20 04:30:00 44 NA
2010-01-20 05:00:00 44 NA
2010-01-20 05:30
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