> > > https://stat.ethz.ch/mailman/listinfo/r-help
> > > PLEASE do read the posting guide
> > http://www.R-project.org/posting-guide.html
> > > and provide commented, minimal, self-contained, reproducible code.
> >
>
> [[alternative HTML versio
n profusion of dummies" :)
>>
>> +1
>>
>> John Kane
>> Kingston ON Canada
>>
>>
>> > -Original Message-
>> > From: r.tur...@auckland.ac.nz
>> > Sent: Fri, 11 Sep 2015 12:22:38 +1200
>> > To: dwinsem...@comcast.net
>
t; GA", " HAWAII",
" ILL", " IND", " IOWA", " KANS", " KY", " LA", " MASS",
" MD", " MICH", " MINN", " MO", " NC", " NEBR", " NEV", " NJ
Dear all,
I have 3-hourly temperature data from 1970-2010 for 122 cities in the US. I
would like to bin this data by city-year-week. My idea is if the
temperature for a particular city in a given week falls within a given
range (-17.78 & -12.22), (-12.22 & -6.67), ... (37.78 & 43.33), then the
cor
; old CentOS to have modern versions of software and all its dependencies.
>
> Best regards,
> Eric
>
> Shouro Dasgupta writes:
>
> Dear all,
>>
>> I have access to an IBM IDataplex Cluster with CentOS v.6.2. R 3.2.1 is
>> currently installed. I was
Dear all,
I have access to an IBM IDataplex Cluster with CentOS v.6.2. R 3.2.1 is
currently installed. I was wondering if there was any way to install RGDAL
on it? Thanks!
Sincerely,
Shouro
[[alternative HTML version deleted]]
__
R-help@r-pro
________
> > R-help r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> > and provide
quot;FIPS",all.X=T, all.y=T)
>
> also note that all.X should be all.x and you might want to use FALSE for
> one or both of those
>
>
>
> On Tue, May 5, 2015 at 11:40 AM, Shouro Dasgupta wrote:
>
>> Hello,
>>
>> Thank you for your reply. My original data
ub.com/davidbrae/swmap
>
>
>
> On Tue, May 5, 2015 at 11:00 AM, Shouro Dasgupta wrote:
>
>> I am trying to plot data by FIPS code using county shapes files.
>>
>> library(data.table)
>> > library(rgdal)
>> > library(colourschemes)
>> > li
I am trying to plot data by FIPS code using county shapes files.
library(data.table)
> library(rgdal)
> library(colourschemes)
> library(RColorBrewer)
> library(maptools)
> library(maps)
> library(ggmap)
I have data by FIPS code which looks like this:
>
>
> dput(head(max_change))
> structure(lis
http://stats.stackexchange.com/questions/7268/how-to-aggregate-by-minute-data-for-a-week-into-hourly-means
On Wed, Mar 11, 2015 at 12:19 PM, Kuma Raj wrote:
> I have a measurement that was taken in 15 minutes or more and want to
> aggregate it by hour. How could I do that?
>
> Sample data is fou
n value
> })
>
> bigDT <- rbindlist(myDTs) # rbind all the data.tables together
>
> # then you should be able to do:
>
> mean.temp <- bigDT[, list(temp.mean=lapply(.SD, mean),
>by=c("FIPS","year","month"), .SDcols=c("temp&q
I have climate data for 20 years for US counties (FIPS) in csv format, each
file represents one year of data. I have extracted the data and reshaped
the yearly data files using melt();
for (i in filelist) {
> tmp1 <- as.data.table(read.csv(i,header=T, sep=","))
> tmp2 <- melt(tmp1, id="FIPS")
:01 AM, Shouro Dasgupta wrote:
> Thank you very much for your reply. I really appreciate it. I apologize
> for the HTML version, I have made modifications and replied to your
> questions/comments below. Thanks again
>
>
>
> tmp1 <- structure(list(FIPS = c(1001L, 1003L, 1
First recode the * in NA: death.dat$v3[death.dat$v1==*] <- NA
Include this in your model: na.rm=TRUE
Or you could create a new dataset: newdata <- na.omit(death.dat)
Shouro
On Fri, Dec 19, 2014 at 11:12 AM, aoife doherty
wrote:
>
> Hi all,
>
> I have a data set like this:
>
> Test.cox file
ek numbers is
> risky. I would recommend using a Date or POSIXt type to make the timestamps
> computable, and then find the date corresponding to the beginning of the
> week that the timestamp falls into. Then aggregate grouping on those time
> values. Unfortunately, the specific way you go
I am trying to compute max, min, and mean from Global Circulation Models
(GCM) for the US. The data is in 3-hour blocks for 2026-2045 and 2081-2100.
Sample Data:
tmp1 <- structure(list(FIPS = c(1001L, 1003L, 1005L), X2026.01.01.1 =
c(285.5533142,
285.5533142, 286.2481079), X2026.01.01.2 = c(283.
17 matches
Mail list logo
