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Since the aggregate S3 method for class formula already has got na.action = na.omit, ## S3 method for class 'formula' aggregate(formula, data, FUN, ..., subset, na.action = na.omit) I think that to deal with NA's, it is enough: aggregate(Value~ID, dta, max) Moreover, passing na.rm = FALSE/TRUE is "don't care": aggregate(Value~ID, dta, max, na.rm=FALSE)

My? thanks to Bill Dunlap and??Giorgio Garziano for? their help.?? It is greatly appreciated.? I works so well, wow. Carl Sutton CPA [[alternative HTML version deleted]]

Generically: http://rseek.org/?q=predictive+maintenance and among those: https://rpubs.com/Simionsv/97830 http://blog.revolutionanalytics.com/2016/03/predictive-maintenance.html -- Best, GG This Communication is Ericsson Confidential. We only send and receive email on the basis of the term set out at http://www.ericsson.com/email_disclaimer [[alternative HTML version deleted]]

Guessing that you may want to take a look at: http://adv-r.had.co.nz/Expressions.html https://www.opencpu.org/ Anyway, as David wrote, that it is too vague for specific hints. -- Best, GG [[alternative HTML version deleted]]

Some tutorials and examples may help. http://www.zoology.ubc.ca/~kgilbert/mysite/Miscellaneous_files/R_MakingMaps.pdf http://coulmont.com/cartes/rcarto.pdf https://pakillo.github.io/R-GIS-tutorial/ http://www.milanor.net/blog/maps-in-r-plotting-data-points-on-a-map/ https://www.youtube.com/watch?v=PTti7OMbURo https://www.nceas.ucsb.edu/scicomp/usecases/CreateMapsWithRGraphics -- Best, GG

Please see updates to df2 assignment as shown below. library(xts) # primary #library(tseries) # Unit root tests library(ggplot2) library(vars) library(grid) dt_xts<-xts(x = 1:10, order.by = seq(as.Date("2016-01-01"), as.Date("2016-01-10"), by = "1 day")) colnames(dt_xts)<-"gdp" xmin<-min(index(dt_xts))

You may investigate a solution based on regular expressions. Some tutorials to help: http://www.regular-expressions.info/rlanguage.html http://www.endmemo.com/program/R/grep.php http://biostat.mc.vanderbilt.edu/wiki/pub/Main/SvetlanaEdenRFiles/regExprTalk.pdf https://rstudio-pubs-static.s3.amazonaws.com/74603_76cd14d5983f47408fdf0b323550b846.html

idvalues <- data.frame (ID = c(1, 1, 2, 2, 3, 4, 4, 4, 5, 5), Value = c(0.69, 0.31, 0.01, 0.99, 1.00, NA, 0,1, 0.5, 0.5)) aggregate(Value~ID, data=idvalues, max) ID Value 1 1 0.69 2 2 0.99 3 3 1.00 4 4 1.00 5 5 0.50 -- Best, GG [[alternative HTML version deleted]]

Starting from this data frame: my.df <- data.frame(num = 1:5, let = letters[1:5]) > my.df num let 1 1 a 2 2 b 3 3 c 4 4 d 5 5 e > and inserting a blank row (NAs row) for each one of my.df rows. na.df <- data.frame(num = NA, let = NA) my.df <- do.call(rbind, apply(my.df, 1, function(x) {rbind(x, na.df)})) > my.df num let 1 1 a 2 <NA>

df1 <- data.frame(ID = c(1,1,2,2,3,3,4,4,5,5), A = c(1,0,5,1,1,NA,0,3,2,7), B = c(2,3,NA,3,4,NA,1,0,5,NA)) df2 <- data.frame(ID = c(1,2,3,4,5), A = c(1,6,1,3,9), B = c(5,3,4,1,5)) m <- match(df1$ID, df2$ID) sel <- c("A", "B") for (i in 1:nrow(df1)) { df1[i,sel] <-

Hi, I was able to replicate the solution as suggested by William in case of data.frame class, not in case of data.table class. In case of data.table, I had to do some minor changes as shown below. library(data.table) a <- 1:10 b <- c("a","b","c","d","e","f","g","h","i","j") c <- seq(1.1,