library(readxl)
library(DT)
library(dplyr)
library(reshape2)
library(data.table)
library(tidyr)
setwd("C:/Users/subas/Syncplicity/MyProjects_IMP/MY_Papers_V2/TRB 2021/00_Topics/XML")
dat1 <- read_excel("SHRP2_032020.xlsx", sheet="fin00")
dat2 <- dat1[,c("title", "abstract", "year", "serial", "publisher")]
dat2a <- dat2[!duplicated(dat2[,c(1:5)]),]
dat2a$non_na <- 3- apply(dat2a, 1, function(x) sum(is.na(x)))
# use aggregate to create new data frame with the maxima
dat2b <- aggregate(non_na ~ title, dat2a, max)
# then simply merge with the original
dat2c <- merge(dat2b, dat2a)
dim(dat2c)
dat4 <- dat1[,c("title", "term", "subject_area", "author")]
dat4a <- dat4[!duplicated(dat4[,c(1:4)]),]
dat5 = melt(dat4a, id.vars = c("title" ))
dat6 = dat5[complete.cases(dat5), ]
dat7= dat6 %>% group_by(title, variable) %>% mutate(rowind = row_number())
dat2e <- dat1[,c("title", "year")][complete.cases(dat1[,c("title", "year")]), ][!duplicated(dat1[,c("title", "year")][complete.cases(dat1[,c("title", "year")]), ][,c(1:2)]),]
dat8= left_join(dat7, dat2e, by="title")