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You will need to say what you mean by "join". It's not a standard term with a 
universally agreed upon meaning within R.

If you have 5 data frames, each with 5 rows, and it makes sense that after 
joining you should have one data frame with 25 rows and the same number of 
columns, then rbind() is probably what you want.

If you have 5 data frames, each with 5 rows, and it makes sense that after 
joining you should have one data frame with 5 rows, and more columns, then 
merge() is probably what you want.

But some of your code suggests you have a somewhat complex data structure, so 
it's hard to say.

extract() is not a base R function; when asking for help one should indicate 
where non-base functions come from.

-Don

--
Don MacQueen
Lawrence Livermore National Laboratory
7000 East Ave., L-627
Livermore, CA 94550
925-423-1062
Lab cell 925-724-7509
 
 
On 4/8/18, 3:47 PM, "R-help on behalf of Lara Dutra Silva" 
<r-help-boun...@r-project.org on behalf of laradutrasi...@gmail.com> wrote:

    Hello,
    
    I gather data from 5 objects and 5 data. frames and  would like to join
    information.
    
    join:  pb_SM + pb_T + pb_P + pb_F + pb_SJ = total_pb
    
    
    join: sdmdata_SM + sdmdata_T + sdmdata_P + sdmdata_F + sdmdata_SJ
    =total_sdmdata
    code:
    rbind, merge?
    
    total_pb<-   ??
    
    total_sdmdata<-   ??
    
    
    1
    
    absvals_SM <- extract(grid_present_SM, absences_10000)
    
    presvals_SM <- extract(grid_present_SM, LSM)
    
    pb_SM <- c(rep(1, nrow(presvals_SM), rep(0, nrow(absvals_SM)))
    
    sdmdata_SM <- data.frame(cbind(pb_SM, rbind(presvals_SM, absvals_SM))
    
                                                ######
    2
    
    absvals_T <- extract(grid_present_T, absences_10000)
    
    presvals_T <- extract(grid_present_T, LT)
    
    pb_T <- c(rep(1, nrow(presvals_T), rep(0, nrow(absvals_T)))
    
    sdmdata_T <- data.frame(cbind(pb_T, rbind(presvals_T, absvals_T))
    
                                              ######
    
    3
    
    absvals_P <- extract(grid_present_T, absences_10000)
    
    presvals_P <- extract(grid_present_P, LP)
    
    pb_P <- c(rep(1, nrow(presvals_P), rep(0, nrow(absvals_P)))
    
    sdmdata_P <- data.frame(cbind(pb_P, rbind(presvals_P, absvals_P))
    
                                    ######
    
    4
    
    absvals_F <- extract(grid_present_F, absences_10000)
    
    presvals_F <- extract(grid_present_F, LF)
    
    pb_F <- c(rep(1, nrow(presvals_F), rep(0, nrow(absvals_F)))
    
    sdmdata_F <- data.frame(cbind(pb_F, rbind(presvals_F, absvals_F))
    
    
                               ######
    
    5
    
    absvals_SJ <- extract(grid_present_SJ, absences_10000)
    
    presvals_SJ <- extract(grid_present_SJ, LSJ)
    
    pb_SJ <- c(rep(1, nrow(presvals_SJ), rep(0, nrow(absvals_SJ)))
    
    sdmdata_SJ <- data.frame(cbind(pb_SJ, rbind(presvals_SJ, absvals_SJ))
    
    
    Regards,
    
    Silva
    
    
    
    
    
    
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