i have several data frames following structure:
january february march april id b id b id b id b 1 4 4 1 2 3 3 9 7 1 4 3 2 3 5 2 2 7 2 2 4 4 6 2 3 6 8 4 9 9 2 3 5 4 7 8 i bring them 1 single data frame contains ´na´ missing id' , there corresponding attributes. results has might like:
id jana janb feba febb mara marb apra aprb 1 4 4 2 3 na na 4 3 2 3 5 2 7 2 4 3 5 3 6 8 na na 9 7 na na 4 7 8 9 9 na na 6 2 given data:
id<-c(1,2,3,4) a<-c(4,3,6,7) b<-c(4,5,8,8) jan<-data.frame(id,a,b) id<-c(1,2,4) a<-c(2,2,9) b<-c(3,7,9) feb<-data.frame(id,a,b) id<-c(3,2) a<-c(9,2) b<-c(7,4) mar<-data.frame(id,a,b) id<-c(1,4,2) a<-c(4,6,3) b<-c(6,2,5) apr<-data.frame(id,a,b) what have tried:
test <- rbind(jan, feb,mar,apr) test <- rbind.fill(jan, feb, mar,apr)
you can use merge within reduce.
first, let's prepare list data , change column names jana, janb, feba, ...
list_df <- list( jan = jan, feb = feb, mar = mar, apr = apr ) list_df <- lapply(names(list_df), function(name_month){ df_month <- list_df[[name_month]] names(df_month)[-1] <- paste0(name_month, names(df_month)[-1]) df_month }) reduce merge of them.
reduce(function(x, y) merge(x, y, = "id", = true), list_df) 
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