similar to: QUERY: correlation between two time series

Dear R-list users, I need to use strptime because I have to deal with date with hours and minutes. I read the manual for strptime and I also looked at many examples, but when I try to apply it to my code, I always encounter some problems. I try to change the default format, with no success. Why? How can I change the format? 1. init_day <- as.factor("2015-02-24-00-30")

I need to modify the graph of the autocorrelation. I tried to do it through plot.acf but with no success. 1. I would like to get rid of the lag zero 2. I would like to have numbers on the x-axis only at lags 12, 24, 36, 48, 60, ... Could anybody help me in this? Any help will be appreciated Thank you for your attention Stefano [[alternative HTML version deleted]]

Dear Jim and dear Enrico, thank you for your replies. Unfortunately your hints didn't solve my problem, and I am getting mad. Can I show you my whole process? I will be as quick as possible. I start from a data frame called Snow of the form year month day hh mm hs 2007 11 19 0 0 0.00 2007 11 19 0 30 0.00 2007 11 19 1 0 0.00 2007 11 19 1 30 0.00 2007 11 19 2 0 0.00 2007 11 19 2 30 0.00 2007 11

Dear list users, if within a function I first define a matrix mymat <- matrix(NA, nrow=m, ncol=n) and somewhere afterwards by mistake mymat <- c(1,2,3) this second command deletes the first one. How can I make sure that within the function mymat will always remain the matrix defined at the beginning, without possibility of changing it throughout the code? Secondly, is it possible to define

Dear R users, I have difficulty to create a list within a list. Example: with > A <- vector(mode="list", 4) I create a list of 4 elements: > A [[1]] NULL [[2]] NULL [[3]] NULL [[4]] NULL In each element of this list I can store, for example, a matrix: A[[1]] <- matrix ... I need each element of A to be a list (all the lists of the same length), and then store matrices

Dear list users, let me ask you this trivial question. I worked on that for a long time, by now. Suppose to have a data frame with NAs and to sum some columns with rowSums: df <- data.frame(A = runif(10), B = runif(10), C = rnorm(10)) df[1, ] <- NA rowSums(df[ , which(names(df) %in% c("A","B"))], na.rm=T) If all the elements of the selected columns are NA, rowSums

Hi Stefano, As the help page says: "The default for the format methods is "%Y-%m-%d %H:%M:%S" if any element has a time component which is not midnight, and "%Y-%m-%d" otherwise. This is because when the result is printed, it uses the default format. If you want a specified output representation: format(strptime(init_day, format="%Y-%m-%d-%H-%M"),"%Y-%M-%d

Dear R users, I have a txt file of the form 10092007 24.62 24.31 24.90 11092007 19.20 23.17 22.10 13092007 24.71 27.33 23.10 14092007 27.33 27.90 24.10 15092007 28.22 28.55 24.30 16092007 28.53 29.24 27.40 17092007 24.19 30.64 26.80 18092007 22.60 20.62 28.40 19092007 8.89 1.70 14.70 20092007 21.27 2.92 17.30 21092007 22.38 24.72 8.80 22092007 23.94 24.73 20.40 23092007 25.33 25.12 22.60

Dear R-users, suppose I have three dataframes like these df1: mydate min_temp 31032013 12 01042013 8 02042013 -999 df2: mydate min_temp 31032013 10 01042013 11 02042013 14 df3: mydate min_temp 31032013 4 01042013 3 02042013 5 where -999 means that the temperature data is not available (at the moment I cannot change it to NA because I am not the db administrator); suppose also that oggi is

What do you mean by "should not"? NULL means "missing object" in R. The result of the sum function is always expected to be numeric... so NA_real or NA_integer could make sense as possible return values. But you cannot compute on NULL so no, that doesn't work. See the note under the "Value" section of ?sum as to why zero is returned when all inputs are removed.

On 21/03/2018 11:44 AM, Stefano Sofia wrote: > Dear list users, > let me ask you this trivial question. I worked on that for a long time, by now. > Suppose to have a data frame with NAs and to sum some columns with rowSums: > > df <- data.frame(A = runif(10), B = runif(10), C = rnorm(10)) > df[1, ] <- NA > rowSums(df[ , which(names(df) %in%

Fwiw the engine behind geom_raster needs explicit observation-per-row form for input (with no structural normalization), so conversion to points is perfectly proper here, albeit confusing in context. (It's closer to what graphics devices actually use ultimately, but the expansion is laid out very early in ggplot2 because there's no standard for intermediate forms.) Cheers, Mike On Wed,

Dear R users, I need to produce rainfall maps using R. I know that this is possible, I looked though the web, I found the example below reported (the author is Andrew Tredennick). I would ask you if this is the most performing way to make rainfall maps; if yes would someone be able to give me an example of how file.asc and pointfile.csv should be? If no would somebody please show me another way

Dear list users, I have to aggregate wind direction data (wd) using a function that requires also a second input variable, wind speed (ws). This is the function that I need to use: my_fun <- function(wd1, ws1){ u_component <- -ws1*sin(2*pi*wd1/360) v_component <- -ws1*cos(2*pi*wd1/360) mean_u <- mean(u_component, na.rm=T) mean_v <- mean(v_component, na.rm=T) mean_wd

No. The empty sum is zero. Adding it to another sum should not change it. Nothing audacious about that. This is consistent; other definitions just cause trouble. -pd > On 21 Mar 2018, at 18:05 , Boris Steipe <boris.steipe at utoronto.ca> wrote: > > Surely the result of summation of non-existent values is not defined, is it not? And since the NA values have been _removed_,

Should not the result be NULL if you have removed the NA with na.rm=TRUE ? B. > On Mar 21, 2018, at 11:44 AM, Stefano Sofia <stefano.sofia at regione.marche.it> wrote: > > Dear list users, > let me ask you this trivial question. I worked on that for a long time, by now. > Suppose to have a data frame with NAs and to sum some columns with rowSums: > > df <-

Surely the result of summation of non-existent values is not defined, is it not? And since the NA values have been _removed_, there's nothing left to sum over. In fact, pretending the the result in that case is zero would appear audacious, no? Cheers, Boris > On Mar 21, 2018, at 12:58 PM, Jeff Newmiller <jdnewmil at dcn.davis.ca.us> wrote: > > What do you mean by

Hi, You might get more help from the R-sig-geo list, which is devoted to spatial topics. However. The *.asc file is an ArcGIS raster export format. You should use whatever the appropriate import commands are for your own gridded rainfall data. If you have a different format, you might or might not be able to import it directly with raster. ?raster will tell you more about the kinds of formats

Dear R-users, I have to deal with (txt) files of the form 10092007 24.62 24.31 24.90 11092007 19.20 23.17 22.10 13092007 24.71 27.33 23.10 14092007 27.33 27.90 24.10 15092007 28.22 28.55 24.30 16092007 28.53 29.24 27.40 17092007 24.19 30.64 26.80 18092007 22.60 20.62 28.40 19092007 18.89 21.70 14.70 20092007 21.27 22.92 17.30 21092007 22.38 24.72 18.80 22092007 23.94 24.73 20.40 23092007 25.33

I see: consistency with additive identity. That makes sense. Thanks. B. > On Mar 21, 2018, at 1:22 PM, peter dalgaard <pdalgd at gmail.com> wrote: > > No. The empty sum is zero. Adding it to another sum should not change it. Nothing audacious about that. This is consistent; other definitions just cause trouble. > > -pd > >> On 21 Mar 2018, at 18:05 , Boris