We can use sub to create a – between the first 4 characters and the next 2. Match the four characters (.{4}), place it in a capture groups ((…)), followed by the next 2 characters in another capture group, replace it with the backreference for those groups (\\1, \\2) and in between we add the … Read more
A matrix with determinant 0 does not have an inverse but one can calculate a generalized inverse (also see Moore Penrose inverse) which is not a true inverse but may be useful depending on what you want to do. See the ginv function in the MASS package (which comes with R). M <- matrix(1:9, 3) … Read more
Assuming you’re just using lm the trick is to change the data argument to subset to something different. speciesList <- unique(df$Species) for(i in 1:length(speciesList){ lmmodel <- lm(x ~ year, data = subset(df, Species == speciesList[i])) #Now do all the stuff you want with lmmodel, e.g. plot, find slope, etc } I’m not going to write … Read more
The question’s use of the xts function is incorrect but it doesn’t really matter since xts cannot represent that sort of data in the first place. xts requires an index class that represents dates or date/times such as Date or POSIXct but here we have plain numbers. Create a zoo series instead. library(zoo) # test … Read more
You should give a reproducible example. Here some data: set.seed(1234) dat <- data.frame(Smoker=sample(c(‘Smoke’,’No_Smoke’),20,rep=TRUE), CANCER=sample(c(‘Cancer’,’NO_Cancer’),20,rep=TRUE)) Then using table you can get your contingency table: table(dat$Smoker,dat$CANCER) Cancer NO_Cancer No_Smoke 7 4 Smoke 5 4 For more information see ?table Description table uses the cross-classifying factors to build a contingency table of the counts at each combination of … Read more
Tried to create your data using the following: df <- data.frame(col1 = c(1,1,2,2,1,1,2,2), col2 = c(34,34,342,23,34,34,342,23), col3 = c(3,4,3,4,3,4,3,4)) And, if you wish to subset based on only one column, you can use @kyle-marsh solution > df[df$col1 == 1, ] col1 col2 col3 1 1 34 3 2 1 34 4 5 1 34 3 … Read more
In Python indentation is very important and so are colons. For this you would also want to use a if statement and not a for loop. This code works, age = int(input(“Enter You Age:”)) if age in range (14,18): print (“This student is in Highschool”) else: print (“This student is not in Highschool”)
When importing a .csv file (I assume it is what you did), you must be careful with some stuff: Columns containing numbers are transformed into characters if there is one or more cells marked as #ERROR or #DIV/0 or any other NA strings that have not been clearly mentioned as such. Sometimes, with analytical data, … Read more
The commenters are right. It doesn’t matter how long the list of numbers is. R can do the operation in one go. x <- c(25.01, 25.8, 25.4) x-15 [1] 10.01 10.80 10.40 If you do run into a situation with many wide-ranging numbers and need to literally keep what comes after the decimal and pick … Read more
You can extract X-square statistic this way: chisq.test(c(89,37,30,28,2), c(40,20,20,15,5)) -> test test$statistic # X-squared # 15 And than just find the maximum value. But it would be easier to help if your example were reproducible.