Decimals (involuntarily) trimmed from values when loaded into environment - r

I'm working with R 3.6.1 in Rstudio 1.2.1335.
When I assign the following value from a column in my data frame, the values that have decimals in that column in the dataframe, get trimmed in the value I assign:
Dataframe$Column1 has values [368.121 376.436]
Value <-- Dataframe$Column1
And I run my code chunk;
The environment shows the column values as: Value num [1:2] 368 376
My decimals have gone and I need those. Why does this happen and is there a way to fix it?
EDIT:
Set_1.
380.283 332.108 327.405 371.570 325.832 345.583 396.377 367.020 428.980 389.524 379.597 407.483 456.271 312.084 391.198 345.813 406.229 346.450 459.307 392.321 337.638 429.377 353.705 377.512 384.921 346.471 411.855 368.406 386.921 397.797 322.416 412.042 383.240 381.244 440.021 372.444 399.301 345.395 359.865 355.449 314.270 453.173 329.055 299.674 351.675 324.334 425.205 437.013 513.334 436.452 335.658 422.669 300.030 287.893 380.611 297.890 351.203 317.065 350.824 269.149 389.509 467.375 399.065 354.954 465.086 353.615 336.454 372.067 424.167 389.172 357.799 321.663 353.633 388.465 342.489 353.487 398.721 416.194 383.376 355.553 398.667 339.722 316.240 383.894 453.429 351.443 460.038 348.860 304.085 258.921
264.107 241.861 278.548 455.216 393.201 348.211 359.426 427.194 391.599 381.335 340.558 369.617 351.342 318.718 338.960 386.547 388.872 283.943 340.501
Set_2:
380.603 332.100 327.391 371.540 325.826 345.602 396.386 367.029 428.949 389.545 379.584 407.454 456.276 312.093 391.414 345.861 406.235 346.259 459.284 392.334 337.626 429.283 353.539 377.568 384.941 346.491 411.820 368.253 386.816 397.723 322.337 412.020 383.158 381.331 440.066 372.361 399.210 345.438 359.948 355.425 314.271 453.169 328.751 299.701 351.388 324.371 425.219 436.906 513.384 436.475 335.508 422.661 300.036 287.908 380.453 297.306 351.275 317.206 351.165 269.122 389.499 467.402 399.136 354.943 465.057 353.593 336.549 372.079 424.062 389.119 357.753 321.758 353.650 388.599 342.285 353.507 398.682 416.289 383.309 355.456 398.816 339.681 316.273 383.898 453.418 351.395 460.027 348.731 304.111 258.452
264.298 241.829 278.297 455.104 393.228 348.117 359.645 427.096 391.526 381.260 340.474 369.791 351.061 318.780 338.949 386.458 389.030 284.093 340.512
Code:
plot(Set_1,Set_2,col = "red", xlab="Set_1", ylab = "Set_2",
main = "Comparison Set_1 and Set_2", type = 'p')
abline(fit5<-lm(Set_2~Set_1), col="blue")
r5<-round(summary(fit5)$adj.r.square, 4)
text(410,330, paste("R2=",r5))


The decimals aren't gone, they are just not shown in your enviroment. Try accessing the values by Value[1]. This clearly gives you your desired result 368.121.

Related

R Conditional Filling of Value based on Test of Existing Value

In brief, I have a large dataframe (~750,000 rows) most of which have a NA value in the "Age" field. I want to assign the values held in the "AcutalAge" and "InterpAge" field where the "Age" field is empty (prioritizing the "ActualAge" field first). The code snippet below is not working. Any thoughts? All of the fields are ints ranging from 0 to 150 or so.
for (r in seq_len(nrow(TreeData))){
if (is.na(TreeData[r,"Age"])){
TreeData[r,"Age"] <- TreeData[r,"ActualAge"]
}
# use InterpAge field if not a sample age tree or ActualAge tree
if (is.na(TreeData[r,"Age"])){
TreeData[r,"Age"] <- TreeData[r,"InterpAge"]
}
}
Sample Data:
"","Stand_ID","Plot_ID","StandPlot_ID","Tree_ID","District","PlotNumber","DBH","Ht","TreeStatus","Remeasurement","CrRatio","Species","Abbrev","b1","b2","b3","b4","b5","Age","Elevation","Slope","Latitude","Longitude","InterpAge","ActualSpec","ActualCD","ActualSite","ActualAge","DomSpec","Inv_Year","Disturbance","Treatment"
"1","D10P112103","R0","D10P112103R0",59,10,112103,0.551181390613437,6.23359592177868,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"2","D10P112103","R0","D10P112103R0",58,10,112103,0.472441218773127,5.24934407822132,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,10,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"3","D10P112103","R0","D10P112103R0",30,10,112103,0.433071109386563,4.92126,0,0,NA,"ABBA","bF",0.4358,1.065,-0.0179,-0.7497,0.0251,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"4","D10P112103","R0","D10P112103R0",7,10,112103,0.748031890613437,7.54593184355736,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"5","D10P112103","R0","D10P112103R0",41,10,112103,0.5905515,6.88976368711472,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"6","D10P112103","R0","D10P112103R0",17,10,112103,0.472441218773127,5.24934407822132,0,0,NA,"ABBA","bF",0.4358,1.065,-0.0179,-0.7497,0.0251,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"7","D10P112103","R0","D10P112103R0",20,10,112103,0.157480402346641,4.92126,0,0,NA,"ABBA","bF",0.4358,1.065,-0.0179,-0.7497,0.0251,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"8","D10P112103","R0","D10P112103R0",67,10,112103,0.354330890613437,4.92126,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"9","D10P112103","R0","D10P112103R0",47,10,112103,0.393701,5.90551184355736,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,10,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"10","D10P112103","R0","D10P112103R0",16,10,112103,0.472441218773127,5.57742815644264,0,0,NA,"ABBA","bF",0.4358,1.065,-0.0179,-0.7497,0.0251,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"11","D10P112103","R0","D10P112103R0",57,10,112103,0.1968505,4.59317592177868,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"12","D10P112103","R0","D10P112103R0",49,10,112103,0.669291718773127,6.88976368711472,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"13","D10P112103","R0","D10P112103R0",62,10,112103,0.393701,5.24934407822132,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"14","D10P112103","R0","D10P112103R0",36,10,112103,0.393701,5.24934407822132,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"15","D10P112103","R0","D10P112103R0",53,10,112103,0.1968505,4.59317592177868,0,0,NA,"ABBA","bF",0.4358,1.065,-0.0179,-0.7497,0.0251,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"16","D10P112103","R0","D10P112103R0",15,10,112103,0.354330890613437,4.92126,0,0,NA,"ABBA","bF",0.4358,1.065,-0.0179,-0.7497,0.0251,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"17","D10P112103","R0","D10P112103R0",63,10,112103,0.157480402346641,4.26509184355736,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"18","D10P112103","R0","D10P112103R0",43,10,112103,0.393701,5.24934407822132,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"19","D10P112103","R0","D10P112103R0",4,10,112103,0.472441218773127,5.90551184355736,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"20","D10P112103","R0","D10P112103R0",79,10,112103,0.433071109386563,5.90551184355736,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"21","D10P112103","R0","D10P112103R0",66,10,112103,0.236220609386563,4.59317592177868,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"22","D10P112103","R0","D10P112103R0",28,10,112103,0.472441218773127,6.23359592177868,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"23","D10P112103","R0","D10P112103R0",34,10,112103,0.118110304693282,4.26509184355736,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"24","D10P112103","R0","D10P112103R0",46,10,112103,0.236220609386563,4.92126,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"25","D10P112103","R0","D10P112103R0",21,10,112103,0.669291718773127,6.23359592177868,0,0,NA,"ABBA","bF",0.4358,1.065,-0.0179,-0.7497,0.0251,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"26","D10P112103","R0","D10P112103R0",81,10,112103,0.275590695306718,4.92126,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"27","D10P112103","R0","D10P112103R0",77,10,112103,0.1968505,4.59317592177868,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"28","D10P112103","R0","D10P112103R0",64,10,112103,0.157480402346641,4.26509184355736,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"29","D10P112103","R0","D10P112103R0",72,10,112103,0.472441218773127,5.90551184355736,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"30","D10P112103","R0","D10P112103R0",73,10,112103,0.354330890613437,5.24934407822132,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"31","D10P112103","R0","D10P112103R0",55,10,112103,0.1968505,4.59317592177868,0,0,NA,"ABBA","bF",0.4358,1.065,-0.0179,-0.7497,0.0251,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"32","D10P112103","R0","D10P112103R0",32,10,112103,1.181103,8.53018368711472,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,10,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"33","D10P112103","R0","D10P112103R0",13,10,112103,0.236220609386563,4.92126,0,0,NA,"ABBA","bF",0.4358,1.065,-0.0179,-0.7497,0.0251,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"34","D10P112103","R0","D10P112103R0",12,10,112103,0.354330890613437,5.57742815644264,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"35","D10P112103","R0","D10P112103R0",70,10,112103,0.1968505,4.59317592177868,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"36","D10P112103","R0","D10P112103R0",75,10,112103,0.708661781226873,6.23359592177868,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"37","D10P112103","R0","D10P112103R0",82,10,112103,0.157480402346641,4.59317592177868,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"38","D10P112103","R0","D10P112103R0",40,10,112103,0.787402,7.54593184355736,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,10,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"39","D10P112103","R0","D10P112103R0",52,10,112103,0.551181390613437,5.57742815644264,0,0,NA,"ABBA","bF",0.4358,1.065,-0.0179,-0.7497,0.0251,10,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"40","D10P112103","R0","D10P112103R0",23,10,112103,0.748031890613437,6.23359592177868,0,0,NA,"ABBA","bF",0.4358,1.065,-0.0179,-0.7497,0.0251,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"41","D10P112103","R0","D10P112103R0",6,10,112103,0.314960804693282,5.24934407822132,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"42","D10P112103","R0","D10P112103R0",31,10,112103,0.314960804693282,4.92126,0,0,NA,"ABBA","bF",0.4358,1.065,-0.0179,-0.7497,0.0251,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"43","D10P112103","R0","D10P112103R0",45,10,112103,0.393701,4.92126,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"44","D10P112103","R0","D10P112103R0",35,10,112103,0.354330890613437,4.92126,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"45","D10P112103","R0","D10P112103R0",38,10,112103,0.1968505,4.59317592177868,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"46","D10P112103","R0","D10P112103R0",80,10,112103,0.1968505,4.59317592177868,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"47","D10P112103","R0","D10P112103R0",5,10,112103,0.1968505,4.59317592177868,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"48","D10P112103","R0","D10P112103R0",60,10,112103,0.472441218773127,5.57742815644264,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"49","D10P112103","R0","D10P112103R0",19,10,112103,0.748031890613437,6.88976368711472,0,0,NA,"ABBA","bF",0.4358,1.065,-0.0179,-0.7497,0.0251,10,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"50","D10P112103","R0","D10P112103R0",22,10,112103,0.866142218773127,7.87401631288528,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,10,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"51","D10P112103","R0","D10P112103R0",61,10,112103,0.354330890613437,5.24934407822132,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"52","D10P112103","R0","D10P112103R0",68,10,112103,0.1968505,4.59317592177868,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"53","D10P112103","R0","D10P112103R0",33,10,112103,0.236220609386563,4.59317592177868,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"54","D10P112103","R0","D10P112103R0",76,10,112103,0.551181390613437,5.90551184355736,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"55","D10P112103","R0","D10P112103R0",3,10,112103,0.9842525,7.54593184355736,0,0,NA,"ABBA","bF",0.4358,1.065,-0.0179,-0.7497,0.0251,10,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"56","D10P112103","R0","D10P112103R0",51,10,112103,0.157480402346641,4.59317592177868,0,0,NA,"ABBA","bF",0.4358,1.065,-0.0179,-0.7497,0.0251,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"57","D10P112103","R0","D10P112103R0",27,10,112103,0.393701,4.59317592177868,0,0,NA,"ABBA","bF",0.4358,1.065,-0.0179,-0.7497,0.0251,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"58","D10P112103","R0","D10P112103R0",48,10,112103,0.511811281226873,6.23359592177868,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"59","D10P112103","R0","D10P112103R0",18,10,112103,0.275590695306718,4.59317592177868,0,0,NA,"ABBA","bF",0.4358,1.065,-0.0179,-0.7497,0.0251,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"60","D10P112103","R0","D10P112103R0",65,10,112103,0.905512281226873,7.21784815644264,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,10,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"61","D10P112103","R0","D10P112103R0",14,10,112103,0.1968505,4.59317592177868,0,0,NA,"ABBA","bF",0.4358,1.065,-0.0179,-0.7497,0.0251,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"62","D10P112103","R0","D10P112103R0",10,10,112103,0.669291718773127,7.21784815644264,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,10,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"63","D10P112103","R0","D10P112103R0",25,10,112103,0.118110304693282,4.26509184355736,0,0,NA,"ABBA","bF",0.4358,1.065,-0.0179,-0.7497,0.0251,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"64","D10P112103","R0","D10P112103R0",24,10,112103,0.393701,4.92126,0,0,NA,"ABBA","bF",0.4358,1.065,-0.0179,-0.7497,0.0251,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"65","D10P112103","R0","D10P112103R0",74,10,112103,0.629921609386563,6.88976368711472,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"66","D10P112103","R0","D10P112103R0",42,10,112103,0.314960804693282,4.92126,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"67","D10P112103","R0","D10P112103R0",1,10,112103,2.755907,10.4986881564426,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"68","D10P112103","R0","D10P112103R0",39,10,112103,0.511811281226873,6.56168,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"69","D10P112103","R0","D10P112103R0",26,10,112103,0.433071109386563,5.57742815644264,0,0,NA,"ABBA","bF",0.4358,1.065,-0.0179,-0.7497,0.0251,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"70","D10P112103","R0","D10P112103R0",83,10,112103,0.314960804693282,4.92126,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"71","D10P112103","R0","D10P112103R0",56,10,112103,0.275590695306718,4.92126,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"72","D10P112103","R0","D10P112103R0",54,10,112103,0.157480402346641,4.59317592177868,0,0,NA,"ABBA","bF",0.4358,1.065,-0.0179,-0.7497,0.0251,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"73","D10P112103","R0","D10P112103R0",71,10,112103,0.314960804693282,4.92126,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"74","D10P112103","R0","D10P112103R0",9,10,112103,0.433071109386563,5.57742815644264,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"75","D10P112103","R0","D10P112103R0",84,10,112103,0.669291718773127,5.90551184355736,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"76","D10P112103","R0","D10P112103R0",8,10,112103,0.275590695306718,4.92126,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"77","D10P112103","R0","D10P112103R0",11,10,112103,0.433071109386563,59.05512,0,0,NA,"ABBA","bF",0.4358,1.065,-0.0179,-0.7497,0.0251,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"78","D10P112103","R0","D10P112103R0",69,10,112103,0.157480402346641,4.26509184355736,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"79","D10P112103","R0","D10P112103R0",50,10,112103,0.1968505,4.59317592177868,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"80","D10P112103","R0","D10P112103R0",44,10,112103,0.393701,5.24934407822132,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"81","D10P112103","R0","D10P112103R0",2,10,112103,0.354330890613437,4.92126,0,0,NA,"ABBA","bF",0.4358,1.065,-0.0179,-0.7497,0.0251,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"82","D10P112103","R0","D10P112103R0",78,10,112103,0.157480402346641,4.26509184355736,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"83","D10P112103","R0","D10P112103R0",29,10,112103,0.0787402011733204,4.26509184355736,0,0,NA,"ABBA","bF",0.4358,1.065,-0.0179,-0.7497,0.0251,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"84","D10P112103","R0","D10P112103R0",37,10,112103,0.393701,5.57742815644264,0,0,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2012,NA,NA
"85","D10P112103","R1","D10P112103R1",33,10,112103,0.708661781226873,6.56168,0,1,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2016,NA,NA
"86","D10P112103","R1","D10P112103R1",48,10,112103,1.02362256245375,8.2021,0,1,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2016,NA,NA
"87","D10P112103","R1","D10P112103R1",70,10,112103,0.748031890613437,6.56168,0,1,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2016,NA,NA
"88","D10P112103","R1","D10P112103R1",76,10,112103,1.06299271877313,7.87401631288528,0,1,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2016,NA,NA
"89","D10P112103","R1","D10P112103R1",71,10,112103,0.629921609386563,6.56168,0,1,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2016,NA,NA
"90","D10P112103","R1","D10P112103R1",72,10,112103,0.826772062453747,7.87401631288528,0,1,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2016,NA,NA
"91","D10P112103","R1","D10P112103R1",7,10,112103,1.61417406245375,11.48294,0,1,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2016,NA,NA
"92","D10P112103","R1","D10P112103R1",111,10,112103,0.551181390613437,6.23359592177868,0,1,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2016,NA,NA
"93","D10P112103","R1","D10P112103R1",114,10,112103,0.236220609386563,4.59317592177868,0,1,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2016,NA,NA
"94","D10P112103","R1","D10P112103R1",34,10,112103,0.629921609386563,6.23359592177868,0,1,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2016,NA,NA
"95","D10P112103","R1","D10P112103R1",74,10,112103,1.25984321877313,9.18635184355736,0,1,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2016,NA,NA
"96","D10P112103","R1","D10P112103R1",42,10,112103,0.511811281226873,5.57742815644264,0,1,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2016,NA,NA
"97","D10P112103","R1","D10P112103R1",102,10,112103,0.393701,5.57742815644264,0,1,NA,"ABBA","bF",0.4358,1.065,-0.0179,-0.7497,0.0251,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2016,NA,NA
"98","D10P112103","R1","D10P112103R1",110,10,112103,0.472441218773127,5.57742815644264,0,1,NA,"ABBA","bF",0.4358,1.065,-0.0179,-0.7497,0.0251,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2016,NA,NA
"99","D10P112103","R1","D10P112103R1",5,10,112103,0.629921609386563,8.2021,0,1,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,NA,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2016,NA,NA
"100","D10P112103","R1","D10P112103R1",10,10,112103,1.49606378122687,10.8267718435574,0,1,NA,"PIMA","bS",0.1324,1.1955,-0.0061,-1.2545,-0.0943,14,246,5,49.0973055553436,55.6901944446564,10,"bSbF",3,"M",10,"bS",2016,NA,NA

This worked like a charm (thanks #DennyChen):
setDT(TreeData)[is.na(Age), Age:= ActualAge]
setDT(TreeData)[is.na(Age), Age:= InterpAge]

According to the answer post by #UnsoughtNine :
After setDT(), the table TreeData had been changed to a data.table object.
There is no need to setDT() again in the secong line of code.
It can also work with combining %>% pipe operator in magrittr package :
setDT(TreeData)[is.na(Age), Age:= ActualAge] %>%
.[is.na(Age), Age:= InterpAge]

How to correct the output generated through str_detect/str_contains in R

I just have a column "methods_discussed" in CSV (link is https://github.com/pandas-dev/pandas/files/3496001/multiple_responses.zip)
multi<- read.csv("multiple_responses.csv", header = T)
This file having values name of family planning methods in the column name like:
methods_discussed
emergency female_sterilization male_sterilization iud NaN injectables male_condoms -77 male_condoms female_sterilization male_sterilization injectables iud male_condoms
I have created a vector of all but not -77 and NAN of 8 family planning methods as:
method_names = c('female_condoms', 'emergency', 'male_condoms', 'pill', 'injectables', 'iud', 'male_sterilization', 'female_sterilization')
I want to create new indicator variable based on the names of vector (method_names) in the existing data frame multi2, for this I used (I)
for (abc in method_names) {
multi2[abc]<- as.integer(str_detect(multi2$methods_discussed, fixed(abc)))
}
(II)
for (abc in method_names) {
multi2[abc]<- as.integer(str_contains(abc,multi2$methods_discussed))
}
(III) I also tried
for (abc in method_names) {
multi2[abc]<- as.integer(stri_detect_fixed(multi2$methods_discussed, abc))
}
but the output is not matching as expected. Probably male_sterilization is a substring of female_sterilization and it shows 1(TRUE) for male_sterilization for female_sterlization also. It is shown below in the Actual output at row 2. It must show 0 (FALSE) as female_sterilization is in the method_discussed column at row 2. I also don't want to generate any thing like 0/1 (False/True) (should be blank) corresponding to -77 and blank in method_discussed (All are highlighted in Expected output.
Actual Output
Expected Output
No error in code but only in the output.

You can add word boundaries to fix that issue.
multi<- read.csv("multiple_responses.csv", header = T)
method_names = c('female_condoms', 'emergency', 'male_condoms', 'pill', 'injectables', 'iud', 'male_sterilization', 'female_sterilization')
for (abc in method_names) {
multi[abc]<- as.integer(grepl(paste0('\\b', abc, '\\b'), multi$methods_discussed))
}
multi[multi$methods_discussed %in% c('', -77), method_names] <- ''

How to check if subset is empty in R

I have a set of data with weight with time (t), I need to identify outliers of weight for every time (t), after which I need to send a notification email.
I'm using bloxplot($out) to identify the outliers, it seems to work, but I'm not sure if:
It's the correct way to use the boxplot?
I can't detect if the boxplot has no outlier or if its empty (or maybe, I'm using a wrong technique)
Or possibly the subset itself is empty (could be the root cause)
For now, I just need to trap the empty subset and check if out variable is empty or not.
Below is my R script code:
#i am a comment, and the compiler doesn't care about me
#load our libraries
library(ggplot2)
library(mailR)
#some variables to be used later
from<-""
to<-""
getwd()
setwd("C:\\Temp\\rwork")
#read the data file into a data(d) variable
d<-read.csv("testdata.csv", header=TRUE) #file
#get the current time(t)
t <-format(Sys.time(),"%H")
#create a subset of d based on t
sbset<-subset(d,Time==t)
#identify if outlier exists then send an email report
out<-boxplot(sbset$weight)$out
if(length(out)!=0){
#create a boxplot of the subset
boxplot(sbset$weight)
subject = paste("Attention: An Outlier is detected for Scheduled Job Run on Hour ",t)
message = toString(out) #sort(out)
}else{
subject = paste("No Outlier Identified")
message = ""
}
email<-send.mail(from=from,
to=to,
subject=subject,
body=message,
html=T,
smtp=list(host.name = "smtp.gmail.com",
port = 465,
user.name = from,
passwd = "", #password of sender email
ssl = TRUE),
authenticate=TRUE,
send=TRUE)
DATA
weight,Time,Chick,x
42,0,1,1
51,2,1,1
59,4,1,1
64,6,1,1
76,8,1,1
93,10,1,1
106,12,1,1
125,14,1,1
149,16,1,1
171,18,1,1
199,20,1,1
205,21,1,1
40,0,2,1
49,2,2,1
58,4,2,1
72,6,2,1
84,8,2,1
103,10,2,1
122,12,2,1
138,14,2,1
162,16,2,1
187,18,2,1
209,20,2,1
215,21,2,1
43,0,3,1
39,2,3,1
55,4,3,1
67,6,3,1
84,8,3,1
99,10,3,1
115,12,3,1
138,14,3,1
163,16,3,1
187,18,3,1
198,20,3,1
202,21,3,1
42,0,4,1
49,2,4,1
56,4,4,1
67,6,4,1
74,8,4,1
87,10,4,1
102,12,4,1
108,14,4,1
136,16,4,1
154,18,4,1
160,20,4,1
157,21,4,1
41,0,5,1
42,2,5,1
48,4,5,1
60,6,5,1
79,8,5,1
106,10,5,1
141,12,5,1
164,14,5,1
197,16,5,1
199,18,5,1
220,20,5,1
223,21,5,1
41,0,6,1
49,2,6,1
59,4,6,1
74,6,6,1
97,8,6,1
124,10,6,1
141,12,6,1
148,14,6,1
155,16,6,1
160,18,6,1
160,20,6,1
157,21,6,1
41,0,7,1
49,2,7,1
57,4,7,1
71,6,7,1
89,8,7,1
112,10,7,1
146,12,7,1
174,14,7,1
218,16,7,1
250,18,7,1
288,20,7,1
305,21,7,1
42,0,8,1
50,2,8,1
61,4,8,1
71,6,8,1
84,8,8,1
93,10,8,1
110,12,8,1
116,14,8,1
126,16,8,1
134,18,8,1
125,20,8,1
42,0,9,1
51,2,9,1
59,4,9,1
68,6,9,1
85,8,9,1
96,10,9,1
90,12,9,1
92,14,9,1
93,16,9,1
100,18,9,1
100,20,9,1
98,21,9,1
41,0,10,1
44,2,10,1
52,4,10,1
63,6,10,1
74,8,10,1
81,10,10,1
89,12,10,1
96,14,10,1
101,16,10,1
112,18,10,1
120,20,10,1
124,21,10,1
43,0,11,1
51,2,11,1
63,4,11,1
84,6,11,1
112,8,11,1
139,10,11,1
168,12,11,1
177,14,11,1
182,16,11,1
184,18,11,1
181,20,11,1
175,21,11,1
41,0,12,1
49,2,12,1
56,4,12,1
62,6,12,1
72,8,12,1
88,10,12,1
119,12,12,1
135,14,12,1
162,16,12,1
185,18,12,1
195,20,12,1
205,21,12,1
41,0,13,1
48,2,13,1
53,4,13,1
60,6,13,1
65,8,13,1
67,10,13,1
71,12,13,1
70,14,13,1
71,16,13,1
81,18,13,1
91,20,13,1
96,21,13,1
41,0,14,1
49,2,14,1
62,4,14,1
79,6,14,1
101,8,14,1
128,10,14,1
164,12,14,1
192,14,14,1
227,16,14,1
248,18,14,1
259,20,14,1
266,21,14,1
41,0,15,1
49,2,15,1
56,4,15,1
64,6,15,1
68,8,15,1
68,10,15,1
67,12,15,1
68,14,15,1
41,0,16,1
45,2,16,1
49,4,16,1
51,6,16,1
57,8,16,1
51,10,16,1
54,12,16,1
42,0,17,1
51,2,17,1
61,4,17,1
72,6,17,1
83,8,17,1
89,10,17,1
98,12,17,1
103,14,17,1
113,16,17,1
123,18,17,1
133,20,17,1
142,21,17,1
39,0,18,1
35,2,18,1
43,0,19,1
48,2,19,1
55,4,19,1
62,6,19,1
65,8,19,1
71,10,19,1
82,12,19,1
88,14,19,1
106,16,19,1
120,18,19,1
144,20,19,1
157,21,19,1
41,0,20,1
47,2,20,1
54,4,20,1
58,6,20,1
65,8,20,1
73,10,20,1
77,12,20,1
89,14,20,1
98,16,20,1
107,18,20,1
115,20,20,1
117,21,20,1
40,0,21,2
50,2,21,2
62,4,21,2
86,6,21,2
125,8,21,2
163,10,21,2
217,12,21,2
240,14,21,2
275,16,21,2
307,18,21,2
318,20,21,2
331,21,21,2
41,0,22,2
55,2,22,2
64,4,22,2
77,6,22,2
90,8,22,2
95,10,22,2
108,12,22,2
111,14,22,2
131,16,22,2
148,18,22,2
164,20,22,2
167,21,22,2
43,0,23,2
52,2,23,2
61,4,23,2
73,6,23,2
90,8,23,2

Your first use of boxplot is unnecessarily creating a plot, you can use
out <- boxplot.stats(sbset$weight)$out
for a little efficiency.
You are interested in the presence of rows, but length(sbset) will return the number of columns. I suggest instead nrow or NROW.
if (NROW(out) > 0) {
boxplot(sbset$weight)
# ...
} else {
# ...
}

WGCNA - error in modulePreservation(): duplicated row.names not allowed

I'm having some problems with the modulePreservation function of WGCNA (https://www.rdocumentation.org/packages/WGCNA/versions/1.63/topics/modulePreservation). When I use it with my multiData dataframes (gene expression from case and control groups), I'm having a error of duplicated row.names. In the past, I was able to perform this step with no problems at all.
(Ps. multiExpr = multiData ; control_colors = multiColor)
> modulePreservation(multiExpr, control_colors, dataIsExpr=T, referenceNetworks=1, nPermutations=100, randomSeed=1, quickCor=0, verbose=3, networkType="unsigned")
.checking data for excessive amounts of missing data..
Flagging genes and samples with too many missing values...
..step 1
Flagging genes and samples with too many missing values...
..step 1
..unassigned 'module' name: grey
..all network sample 'module' name: gold
..calculating observed preservation values
Error in `.rowNamesDF<-`(x, value = value) :
duplicate 'row.names' are not allowed
In addition: Warning message:
non-unique values when setting 'row.names': ‘A1CF’, ‘A2M’, ‘AADAC’, ‘AARS’, ‘AASDHPPT’, ‘ABCA12’, ‘ABCA3’, ‘ABCA4’, ‘ABCA8’, ‘ABCB11’, ‘ABCB4’, ‘ABCB9’, ‘ABCC1’, ‘ABCC3’, ‘ABCC6’, ‘ABCD2’, ‘ABCD4’, ‘ABCE1’, ‘ABCF3’, ‘ABCG1’, ‘ABCG2’, ‘ABHD10’, ‘ABHD2’, ‘ABHD4’, ‘ABHD6’, ‘ABI2’, ‘ABL1’, ‘ABL2’, ‘ACAA2’, ‘ACACA’, ‘ACACB’, ‘ACAD10’, ‘ACAD8’, ‘ACADL’, ‘ACADSB’, ‘ACADVL’, ‘ACAN’, ‘ACAP1’, ‘ACAT1’, ‘ACBD3’, ‘ACBD4’, ‘ACCN3’, ‘ACD’, ‘ACE2’, ‘ACHE’, ‘ACIN1’, ‘ACO2’, ‘ACOT7’, ‘ACOT8’, ‘ACOT9’, ‘ACOX3’, ‘ACOXL’, ‘ACPP’, ‘ACR’, ‘ACRV1’, ‘ACSF2’, ‘ACSL3’, ‘ACSL5’, ‘ACSL6’, ‘ACSM3’, ‘ACTB’, ‘ACTC1’, ‘ACTL6B’, ‘ACTL7A’, ‘ACTL8’, ‘ACTN2’, ‘ACTN3’, ‘ACTR1A’, ‘ACTR2’, ‘ACTR3B’, ‘ACTR5’, ‘ACTR8’, ‘ACVR1’, ‘ACVRL1�� [... truncated]
I already checked the row.names and colnames of my multiExpr files, and all are unique values:
sum(duplicated(row.names(multiExpr$Control$data)))
sum(duplicated(row.names(multiExpr$Case$data)))
sum(duplicated(colnames(multiExpr$Control$data)))
sum(duplicated(colnames(multiExpr$Case$data)))
My R version is R version 3.5.1 (2018-07-02)

It seems to be a bug in signedKME()
I've proposed a fix at https://www.biostars.org/p/339950/

Import data into R - argument is empty

I am trying to use a R package called GOSemSim, it requires to import a lot of data into variables with a specific format like this:
data1 = c("one", "two", "three")
data2 = c("A", "B", "C")
When the list of data that I try to import into a variable is longer than 293 then I get the following error message:
argument 293 is empty
THere are no error with the "" or comma, I computed it with linux, it does not matter what data it is.
This is really weird basically, I tried on two computers with no luck. I tried to import it as a CSV file but the R package won't allow it.
Anyone knows why you cannot import more than 293 data?
Update:
Here is the code and my data at the same time, it is a one liner in R which has never been a problem for me!
OQ = c("GO:0000003", "GO:0000070", "GO:0000077", "GO:0000079", "GO:0000082", "GO:0000086", "GO:0000122", "GO:0000212", "GO:0000226", "GO:0000278", "GO:0000279", "GO:0000280", "GO:0000724", "GO:0000725", "GO:0000819", "GO:0000910", "GO:0001932", "GO:0002118", "GO:0002121", "GO:0002165", "GO:0003002", "GO:0003006", "GO:0006022", "GO:0006030", "GO:0006040", "GO:0006139", "GO:0006259", "GO:0006260", "GO:0006261", "GO:0006267", "GO:0006270", "GO:0006275", "GO:0006277", "GO:0006281", "GO:0006302", "GO:0006304", "GO:0006305", "GO:0006306", "GO:0006310", "GO:0006323", "GO:0006325", "GO:0006342", "GO:0006351", "GO:0006355", "GO:0006357", "GO:0006366", "GO:0006464", "GO:0006468", "GO:0006479", "GO:0006725", "GO:0006807", "GO:0006928", "GO:0006950", "GO:0006974", "GO:0006996", "GO:0007010", "GO:0007017", "GO:0007018", "GO:0007049", "GO:0007051", "GO:0007059", "GO:0007062", "GO:0007067", "GO:0007076", "GO:0007088", "GO:0007093", "GO:0007095", "GO:0007098", "GO:0007126", "GO:0007127", "GO:0007131", "GO:0007140", "GO:0007141", "GO:0007143", "GO:0007154", "GO:0007155", "GO:0007156", "GO:0007259", "GO:0007266", "GO:0007275", "GO:0007276", "GO:0007281", "GO:0007282", "GO:0007292", "GO:0007304", "GO:0007307", "GO:0007346", "GO:0007350", "GO:0007365", "GO:0007367", "GO:0007379", "GO:0007389", "GO:0007399", "GO:0007400", "GO:0007417", "GO:0007420", "GO:0007423", "GO:0007444", "GO:0007472", "GO:0007476", "GO:0007552", "GO:0007560", "GO:0008104", "GO:0008213", "GO:0008283", "GO:0008284", "GO:0008315", "GO:0008356", "GO:0009059", "GO:0009611", "GO:0009653", "GO:0009790", "GO:0009791", "GO:0009880", "GO:0009886", "GO:0009887", "GO:0009888", "GO:0009889", "GO:0009890", "GO:0009892", "GO:0009893", "GO:0009896", "GO:0009968", "GO:0009987", "GO:0010032", "GO:0010033", "GO:0010092", "GO:0010389", "GO:0010468", "GO:0010498", "GO:0010556", "GO:0010558", "GO:0010564", "GO:0010604", "GO:0010605", "GO:0010608", "GO:0010629", "GO:0010648", "GO:0010948", "GO:0014016", "GO:0014017", "GO:0014070", "GO:0016043", "GO:0016055", "GO:0016070", "GO:0016310", "GO:0016319", "GO:0016321", "GO:0016441", "GO:0016458", "GO:0016568", "GO:0016569", "GO:0016570", "GO:0016571", "GO:0016572", "GO:0017145", "GO:0018130", "GO:0019219", "GO:0019222", "GO:0019438", "GO:0019827", "GO:0019953", "GO:0022402", "GO:0022403", "GO:0022404", "GO:0022412", "GO:0022414", "GO:0022610", "GO:0023052", "GO:0023057", "GO:0030111", "GO:0030154", "GO:0030178", "GO:0030182", "GO:0030261", "GO:0030422", "GO:0030703", "GO:0030727", "GO:0031023", "GO:0031047", "GO:0031050", "GO:0031056", "GO:0031060", "GO:0031123", "GO:0031145", "GO:0031175", "GO:0031323", "GO:0031324", "GO:0031325", "GO:0031326", "GO:0031327", "GO:0031331", "GO:0031398", "GO:0031399", "GO:0031401", "GO:0031570", "GO:0031572", "GO:0031935", "GO:0032268", "GO:0032270", "GO:0032501", "GO:0032502", "GO:0032504", "GO:0032507", "GO:0032774", "GO:0032776", "GO:0032886", "GO:0033043", "GO:0033044", "GO:0033260", "GO:0033301", "GO:0033554", "GO:0034622", "GO:0034641", "GO:0034645", "GO:0034654", "GO:0034754", "GO:0034968", "GO:0035023", "GO:0035107", "GO:0035114", "GO:0035120", "GO:0035186", "GO:0035194", "GO:0035195", "GO:0035220", "GO:0035282", "GO:0035295", "GO:0035825", "GO:0036211", "GO:0036388", "GO:0040029", "GO:0042060", "GO:0042221", "GO:0042445", "GO:0043009", "GO:0043066", "GO:0043069", "GO:0043161", "GO:0043170", "GO:0043331", "GO:0043412", "GO:0043414", "GO:0043549", "GO:0043631", "GO:0043933", "GO:0044237", "GO:0044249", "GO:0044260", "GO:0044271", "GO:0044419", "GO:0044700", "GO:0044702", "GO:0044703", "GO:0044707", "GO:0044728", "GO:0044763", "GO:0044767", "GO:0044770", "GO:0044771", "GO:0044772", "GO:0044773", "GO:0044774", "GO:0044786", "GO:0044818", "GO:0044839", "GO:0044843", "GO:0044848", "GO:0045132", "GO:0045165", "GO:0045168", "GO:0045185", "GO:0045448", "GO:0045455", "GO:0045787", "GO:0045814", "GO:0045859", "GO:0045892", "GO:0045931", "GO:0045934", "GO:0046331", "GO:0046425", "GO:0046483", "GO:0046580", "GO:0046605", "GO:0046777", "GO:0048070", "GO:0048134", "GO:0048135", "GO:0048285", "GO:0048311", "GO:0048468", "GO:0048477", "GO:0048513", "GO:0048518", "GO:0048519", "GO:0048522", "GO:0048523", "GO:0048563", "GO:0048569", "GO:0048583", "GO:0048585", "GO:0048609", "GO:0048646", "GO:0048666", "GO:0048699", "GO:0048704", "GO:0048705", "GO:0048706", "GO:0048707", "GO:0048731", "GO:0048736", "GO:0048737", "GO:0048754", "GO:0048856", "GO:0048863", "GO:0048865", "GO:0048867", "GO:0048869", "GO:0050789", "GO:0050793", "GO:0050794", "GO:0050896", "GO:0051052", "GO:0051058", "GO:0051128", "GO:0051171", "GO:0051172", "GO:0051225", "GO:0051235", "GO:0051246", "GO:0051247", "GO:0051252", "GO:0051253", "GO:0051276", "GO:0051297", "GO:0051299", "GO:0051301", "GO:0051302", "GO:0051321", "GO:0051325", "GO:0051329", "GO:0051338", "GO:0051351", "GO:0051443", "GO:0051445", "GO:0051641", "GO:0051646", "GO:0051651", "GO:0051704", "GO:0051716", "GO:0051726", "GO:0051783", "GO:0051785", "GO:0060255", "GO:0060429", "GO:0060548", "GO:0060688", "GO:0060966", "GO:0060968", "GO:0060993", "GO:0061138", "GO:0065003", "GO:0065004", "GO:0065007", "GO:0070192", "GO:0070507", "GO:0070887", "GO:0070918", "GO:0071103", "GO:0071359", "GO:0071822", "GO:0071824", "GO:0071840", "GO:0071897", "GO:0071900", "GO:0072028", "GO:0072078", "GO:0072079", "GO:0072088", "GO:0080090", "GO:0090068", "GO:0090304", "GO:0090306", "GO:0098609", "GO:1901071", "GO:1901360", "GO:1901362", "GO:1901576", "GO:1901987", "GO:1901988", "GO:1901990", "GO:1901991", "GO:1902275", "GO:1902299", "GO:1902589", "GO:1902679", "GO:1902749", "GO:1903046", "GO:1903047", "GO:1903308", "GO:1903322", "GO:2000026", "GO:2000112", "GO:2000113", "GO:2001141")

The error message in itself is informative. If one tries to make it reproducible, it's best to work with small subsets. It usually helps to have a dead stare at your data before trying to reproduce the behavior. For example,
OQ = c("GO:0000003", "GO:2001141", )
Notice that there are two elements of this character vector. Or are they?
Error in c("GO:0000003", "GO:2001141", ) : argument 3 is empty
Number 3 is the key. R is expecting three elements. Notice the comma after the second element. Once you remove it, you'll be able to create the QQ variable. Scan your real example. I'm sure there's a , , somewhere.
EDIT
I tried copy/pasting your code into a script in Rstudio and it produced the error you describe. If you scroll right, you'll notice that syntax coloring is not working at around position 5000. I have folded the code so that it fits on screen and it runs fine.
This is how I folded the vector and it worked.
OQ = c("GO:0000003", "GO:0000070", "GO:0000077", "GO:0000079", "GO:0000082", "GO:0000086", "GO:0000122",
"GO:0000212", "GO:0000226", "GO:0000278", "GO:0000279", "GO:0000280", "GO:0000724", "GO:0000725",
"GO:0000819", "GO:0000910", "GO:0001932", "GO:0002118", "GO:0002121", "GO:0002165", "GO:0003002",
"GO:0003006", "GO:0006022", "GO:0006030", "GO:0006040", "GO:0006139", "GO:0006259", "GO:0006260",
"GO:0006261", "GO:0006267", "GO:0006270", "GO:0006275", "GO:0006277", "GO:0006281", "GO:0006302",
"GO:0006304", "GO:0006305", "GO:0006306", "GO:0006310", "GO:0006323", "GO:0006325", "GO:0006342",
"GO:0006351", "GO:0006355", "GO:0006357", "GO:0006366", "GO:0006464", "GO:0006468", "GO:0006479",
"GO:0006725", "GO:0006807", "GO:0006928", "GO:0006950", "GO:0006974", "GO:0006996", "GO:0007010",
"GO:0007017", "GO:0007018", "GO:0007049", "GO:0007051", "GO:0007059", "GO:0007062", "GO:0007067",
"GO:0007076", "GO:0007088", "GO:0007093", "GO:0007095", "GO:0007098", "GO:0007126", "GO:0007127",
"GO:0007131", "GO:0007140", "GO:0007141", "GO:0007143", "GO:0007154", "GO:0007155", "GO:0007156",
"GO:0007259", "GO:0007266", "GO:0007275", "GO:0007276", "GO:0007281", "GO:0007282", "GO:0007292",
"GO:0007304", "GO:0007307", "GO:0007346", "GO:0007350", "GO:0007365", "GO:0007367", "GO:0007379",
"GO:0007389", "GO:0007399", "GO:0007400", "GO:0007417", "GO:0007420", "GO:0007423", "GO:0007444",
"GO:0007472", "GO:0007476", "GO:0007552", "GO:0007560", "GO:0008104", "GO:0008213", "GO:0008283",
"GO:0008284", "GO:0008315", "GO:0008356", "GO:0009059", "GO:0009611", "GO:0009653", "GO:0009790",
"GO:0009791", "GO:0009880", "GO:0009886", "GO:0009887", "GO:0009888", "GO:0009889", "GO:0009890",
"GO:0009892", "GO:0009893", "GO:0009896", "GO:0009968", "GO:0009987", "GO:0010032", "GO:0010033",
"GO:0010092", "GO:0010389", "GO:0010468", "GO:0010498", "GO:0010556", "GO:0010558", "GO:0010564",
"GO:0010604", "GO:0010605", "GO:0010608", "GO:0010629", "GO:0010648", "GO:0010948", "GO:0014016",
"GO:0014017", "GO:0014070", "GO:0016043", "GO:0016055", "GO:0016070", "GO:0016310", "GO:0016319",
"GO:0016321", "GO:0016441", "GO:0016458", "GO:0016568", "GO:0016569", "GO:0016570", "GO:0016571",
"GO:0016572", "GO:0017145", "GO:0018130", "GO:0019219", "GO:0019222", "GO:0019438", "GO:0019827",
"GO:0019953", "GO:0022402", "GO:0022403", "GO:0022404", "GO:0022412", "GO:0022414", "GO:0022610",
"GO:0023052", "GO:0023057", "GO:0030111", "GO:0030154", "GO:0030178", "GO:0030182", "GO:0030261",
"GO:0030422", "GO:0030703", "GO:0030727", "GO:0031023", "GO:0031047", "GO:0031050", "GO:0031056",
"GO:0031060", "GO:0031123", "GO:0031145", "GO:0031175", "GO:0031323", "GO:0031324", "GO:0031325",
"GO:0031326", "GO:0031327", "GO:0031331", "GO:0031398", "GO:0031399", "GO:0031401", "GO:0031570",
"GO:0031572", "GO:0031935", "GO:0032268", "GO:0032270", "GO:0032501", "GO:0032502", "GO:0032504",
"GO:0032507", "GO:0032774", "GO:0032776", "GO:0032886", "GO:0033043", "GO:0033044", "GO:0033260",
"GO:0033301", "GO:0033554", "GO:0034622", "GO:0034641", "GO:0034645", "GO:0034654", "GO:0034754",
"GO:0034968", "GO:0035023", "GO:0035107", "GO:0035114", "GO:0035120", "GO:0035186", "GO:0035194",
"GO:0035195", "GO:0035220", "GO:0035282", "GO:0035295", "GO:0035825", "GO:0036211", "GO:0036388",
"GO:0040029", "GO:0042060", "GO:0042221", "GO:0042445", "GO:0043009", "GO:0043066", "GO:0043069",
"GO:0043161", "GO:0043170", "GO:0043331", "GO:0043412", "GO:0043414", "GO:0043549", "GO:0043631",
"GO:0043933", "GO:0044237", "GO:0044249", "GO:0044260", "GO:0044271", "GO:0044419", "GO:0044700",
"GO:0044702", "GO:0044703", "GO:0044707", "GO:0044728", "GO:0044763", "GO:0044767", "GO:0044770",
"GO:0044771", "GO:0044772", "GO:0044773", "GO:0044774", "GO:0044786", "GO:0044818", "GO:0044839",
"GO:0044843", "GO:0044848", "GO:0045132", "GO:0045165", "GO:0045168", "GO:0045185", "GO:0045448",
"GO:0045455", "GO:0045787", "GO:0045814", "GO:0045859", "GO:0045892", "GO:0045931", "GO:0045934",
"GO:0046331", "GO:0046425", "GO:0046483", "GO:0046580", "GO:0046605", "GO:0046777", "GO:0048070",
"GO:0048134", "GO:0048135", "GO:0048285", "GO:0048311", "GO:0048468", "GO:0048477", "GO:0048513",
"GO:0048518", "GO:0048519", "GO:0048522", "GO:0048523", "GO:0048563", "GO:0048569", "GO:0048583",
"GO:0048585", "GO:0048609", "GO:0048646", "GO:0048666", "GO:0048699", "GO:0048704", "GO:0048705",
"GO:0048706", "GO:0048707", "GO:0048731", "GO:0048736", "GO:0048737", "GO:0048754", "GO:0048856",
"GO:0048863", "GO:0048865", "GO:0048867", "GO:0048869", "GO:0050789", "GO:0050793", "GO:0050794",
"GO:0050896", "GO:0051052", "GO:0051058", "GO:0051128", "GO:0051171", "GO:0051172", "GO:0051225",
"GO:0051235", "GO:0051246", "GO:0051247", "GO:0051252", "GO:0051253", "GO:0051276", "GO:0051297",
"GO:0051299", "GO:0051301", "GO:0051302", "GO:0051321", "GO:0051325", "GO:0051329", "GO:0051338",
"GO:0051351", "GO:0051443", "GO:0051445", "GO:0051641", "GO:0051646", "GO:0051651", "GO:0051704",
"GO:0051716", "GO:0051726", "GO:0051783", "GO:0051785", "GO:0060255", "GO:0060429", "GO:0060548",
"GO:0060688", "GO:0060966", "GO:0060968", "GO:0060993", "GO:0061138", "GO:0065003", "GO:0065004",
"GO:0065007", "GO:0070192", "GO:0070507", "GO:0070887", "GO:0070918", "GO:0071103", "GO:0071359",
"GO:0071822", "GO:0071824", "GO:0071840", "GO:0071897", "GO:0071900", "GO:0072028", "GO:0072078",
"GO:0072079", "GO:0072088", "GO:0080090", "GO:0090068", "GO:0090304", "GO:0090306", "GO:0098609",
"GO:1901071", "GO:1901360", "GO:1901362", "GO:1901576", "GO:1901987", "GO:1901988", "GO:1901990",
"GO:1901991", "GO:1902275", "GO:1902299", "GO:1902589", "GO:1902679", "GO:1902749", "GO:1903046",
"GO:1903047", "GO:1903308", "GO:1903322", "GO:2000026", "GO:2000112", "GO:2000113", "GO:2001141")

Resources