如何在r studio的多个excel工作表上使用脚本
我有一个相当长的脚本，至less对我来说，但我在R是新的。
看起来像这样
#DATA IS LOADED library(xlsx) df=read.xlsx2("/Users/emiliemariafalkkallenbach/Documents/Norsk_Institut_for_vandforskning/Chase_DK.xlsx",sheetIndex=1) df[df==""]<- NA df=data.matrix(df) df=data.frame(df) attach(df) Phyto=df[,1:6] Submerged=df[,7:12] Benthic=df[13:18] # PHTYOPLANKTON #making of boundaries a<-(ifelse(P_Resp<=0,(1-P_Acdev),1/(1+P_Acdev))) b=(0.95+a)/2 c=2*ab d=2*ca #Weighted boundaries e=0.95*P_weight e=sum(e) f=b*P_weight f=sum(f) g=a*P_weight g=sum(g) h=c*P_weight g=sum(g) i=d*P_weight i=sum(i) #EQR weighted j=P_EQR*P_weight j=sum(j) #complete l <- ifelse(is.na(rowSums(Phyto)),1,0) m=sum(l) #SUBMERGED VEGETATION #Overall assesment y=ifelse(m<=0,j,"") z=ifelse(y!="NA",0,(ifelse(y>f,1,(ifelse(y>g,2,(ifelse(y>h,3,(ifelse(y>i,4,5))))))))) #making of boundaries a.sub<-(ifelse(S_Resp<=0,(1-S_Acdev),1/(1+S_Acdev))) a.sub=sum(a.sub) b.sub=(0.95+a.sub)/2 b.sub=sum(b.sub) c.sub=2*a.sub-b.sub c.sub=sum(c.sub) d.sub=2*c.sub-a.sub d.sub=sum(d.sub) #Weighted boundaries e.sub=0.95*S_weight e.sub=sum(e) f.sub=b.sub*S_weight f.sub=sum(f) g.sub=a.sub*S_weight g.sub=sum(g) h.sub=c.sub*S_weight h.sub=sum(h) i.sub=d.sub*S_weight i.sub=sum(i) #EQR.sub weighted j.sub=S_EQR*S_weight j.sub=sum(j.sub) #complete.sub l.sub <- ifelse(is.na(rowSums(Submerged)),1,0) m.sub=sum(l.sub) #Overall Assesment q.sub=m.sub*0.75 y.sub=ifelse(m.sub<=0,j.sub,"") z.sub=ifelse(y.sub!="NA",(ifelse(y.sub>f.sub,1,(ifelse(y.sub>g.sub,2,(ifelse(y.sub>h.sub,3,(ifelse(y.sub>i.sub,4,5)))))))),0) BENTHIC INVERTEBRATES #making of boundaries a.ben<-(ifelse(B_Resp<=0,(1-B_Acdev),1/(1+B_Acdev))) b.ben=(0.95+a.ben)/2 c.ben=2*a.ben-b.ben d.ben=2*c.ben-a.ben #Weighted boundaries e.ben=0.95*B_weight e.ben=sum(e.ben) f.ben=b.ben*B_weight f.ben=sum(f.ben) g.ben=a.ben*B_weight g.ben=(sum(g.ben)) h.ben=c.ben*B_weight h.ben=sum(h.ben) i.ben=d.ben*B_weight i.ben=sum(i.ben) #EQR weighted j.ben=B_EQR*B_weight #Complete l.ben <- ifelse(is.na(rowSums(Benthic)),1,0) m.ben=sum(l.sub) #ChkAccDev n.ben=ifelse(B_Resp>0,0.53,1.1) o.ben=ifelse(B_Acdev<0.15,-1,0) p.ben=ifelse(B_Acdev>n.ben,1,o.ben) #Overall Assesment q.ben=m.ben*0.75 y.ben=ifelse(m.ben<1,j.ben,"") z.ben=ifelse(y.ben!="NA",ifelse(y.ben>f.ben,1,(ifelse(y.ben>g.ben,2,(ifelse(y.ben>h.ben,3,(ifelse(y.ben>i.ben,4,5))))))),0) #Final assesment Z=max(na.omit(c(z,z.sub,z.ben))) #Overall assesment SCORE=(ifelse(Z<=1 && Z<2,"HIGH",(ifelse(Z>=2 && Z<3,"GOOD",(ifelse(Z>=3 && Z<4,"MODERATE",(ifelse(Z>=4 && Z<5,"BAD",(ifelse(Z>=5,"POOR","NA")))))))))) SCORE #Pie Chart library('plotrix') Phyto=33.3 Submerged=33.3 Benthic=33.3 total=100 Slices1=c=(1) total=100 iniR=0.2 Slices1=c=(1) pie(1, radius=iniR, init.angle=90, col=c('white'), border = NA, labels='Overall') colors=c(ifelse(z<=1,"blue", ifelse(z<=2,"green",ifelse(z<=3,"yellow",ifelse(z<=4,"orange",ifelse(z<=5,"red","red"))))), ifelse(z.sub<=1,"blue", ifelse(z.sub<=2,"green", ifelse(z.sub<=3,"yellow",ifelse(z.sub<=4,"orange",ifelse(z.sub<=5,"red","red"))))),ifelse(z.ben<=1,"blue", ifelse(z.ben<=2,"green", ifelse(z.ben<=3, "yellow", ifelse(z.ben<=4,"orange",ifelse(z.ben<=5,"red","red")))))) floating.pie(0,0,c(Phyto, Submerged, Benthic),radius=5*iniR, startpos=pi/2, col=colors,border=NA) Slices1=c=(1) total=100 iniR=0.2 # initial radius colorst=c(ifelse(Z<=1,"blue", ifelse(Z<=2,"green",ifelse(Z<=3,"yellow",ifelse(Z<=4,"orange",ifelse(Z<=5,"red","red")))))) floating.pie(0,0,c(total),radius=3*iniR, startpos=pi/2, col=colorst,border=NA) angles=as.numeric(c(-10,75,80)) pie.labels(0,0,angles,c("Phyto","Submerged","Benthic"),radius=1, bg="white") pie.labels(0,0,0,c("Overall Assessment"),radius=-0.3) 我猜这没关系，我的脚本里面写了什么。 目前它只运行在Excel中的第一张，但我有几个，并希望在所有这些运行它们。
结果应该是这样的一张桌子
z z.sub z.ben Z Pie-chart (only if possible) Sheet 1 0 NA NA High Sheet 2 ... ... ... ... Sheet 3 ... ... ... ...
如果这是一个普通的问题，我很抱歉！
希望有人能够帮助
谢谢！
读取xls的更好方法是使用图书馆的readxl 。
# remove "#" if you don't have these libraries installed already # install.packages("readxl") # faster excel reader # install.packages("data.table") # faster everything, in this case rbindlist library(readxl) library(data.table) sheets = 1:5 # index numbers or names of the sheets you want to read readmysheets = function(sheets) { df = read_excel(file="myexcel.xls", sheets) } myfiles = lapply(sheets, readmysheets) # apply the indices/names on the readmysheets function # you now have a list: str(myfiles) # bind the separate sheets together together = rbindlist(myfiles, fill = T)
将你的脚本的主体包装成一个“for”循环。 你有几个这样做，这里有两个。
# pre-allocate an object to write to out <- matrix(rep(NA, numsheets * numcols), ncols = numcols)) for (i in 1:nsheets) { df=read.xlsx2(".../Chase_DK.xlsx", sheetIndex = i) #... do calculations out[, i] <- c(z, z.sub, z.ben, Z) } # second way, no need to pre-allocate anything sapply(1:nsheets, FUN = function(x) { df=read.xlsx2(".../Chase_DK.xlsx", sheetIndex = x) #... do calculations out <- c(z, z.sub, z.ben, Z) # specify what you wish the function to return return(out) # sapply will try to simplify the combined result on its own })