Question

第一次在此发布信息，如果我错过了一些东西，对不起。我目前正在使用我的老老板的代码，他说我只需要将新的csv放入现有脚本中，一切就可以顺利运行。事实并非如此。我的目标是制作每种鱼类的图表，比较湿重和总长度以检查异常值。当我运行脚本时，它不会标记任何错误，但不会生成图形。任何帮助将不胜感激，我能够提供您可能需要的更多详细信息。

fishid<- read.csv(file="2018_fishidcheck.csv", header=T, na.strings = "NA")
fish<- read.csv(file="fish_2019_qaqc.csv", header=T, na.strings = "NA")
fish$FishID<-as.numeric(fish$FishID)

#create subset of fish (by species) to sample for both aging structures, based on size class
data1<- subset(fish, select = c(Common,FishID,TLmm))
data2<-subset(data1, !is.na(data1$FishID))
data2 <- transform(data2, bin = cut(TLmm, 17.5))
write.csv(data2, file = "fish_id_TL.csv")


#check for outliers in length-weight - 
SPClist <- unique(fish$Common)
#omit species that have only NA for WetWt 
#SPClist<-SPClist[-(32)] 


#Create a graph for each species by running through the species list
for(i in SPClist){

#Create a data subset for the species you'd like to create a boxplot for:
mydataSPC <- subset(fish, Common == i, select = 

c(ProjectID,ProjName,ProjType,ProjectID1,Effst,SiteID,Area,SampDate,
                      NameAbbrev, Common, LifeStage, FishID,TLmm, WetWT))


#Create a WetvsTL linear graphs for the species:
plotSPC = plot(WetWT~TLmm,data=mydataSPC, xlab = "Length (mm)", ylab =         
"Weight Wet (g)")
title((paste("Wetwt vs TL for species",i,"Individual Fish data")), 
cex.main = 0.75) 
text(mydataSPC$TLmm, mydataSPC$WetWT, mydataSPC$FishID, cex=0.6, pos=3, 
offset=0.4, col="red")

#Export the plot as a .jpg:
dev.copy(jpeg, filename= (paste(i,".jpg")))
dev.off();
}

编辑以包含一些数据

Common  FishID  TLmm    bin
35  Common Shiner   30  116 (114,137]
36  Common Shiner   31  96  (89.8,114]
37  Common Shiner   32  112 (89.8,114]
38  Common Shiner   33  96  (89.8,114]
39  Yellow Perch    34  248 (232,256]
40  Yellow Perch    35  226 (209,232]
41  Yellow Perch    36  208 (185,209]
42  Yellow Perch    37  207 (185,209]
43  Yellow Perch    38  204 (185,209]
58  Yellow Perch    15  177 (161,185]
59  Yellow Perch    16  213 (209,232]
60  White Sucker    17  291 (280,304]
64  Yellow Perch    18  245 (232,256]
65  Yellow Perch    19  197 (185,209]
123 Yellow Perch    46  165 (161,185]
124 White Sucker    47  226 (209,232]
125 White Sucker    48  226 (209,232]
126 White Sucker    49  200 (185,209]
127 White Sucker    50  228 (209,232]
129 White Sucker    20  470 (446,470]

图形未生成

0 个答案: