my data frame had many outliers in each column / variable. I removed them using Boxplot / IQR cut-off for 75% / 25%. I took out each column and removed outliers from them. Therefore, each column has different number of values in it. Now I want to combine those all NEW variables which does not has any outlier in it to single data frame. I am getting this error in Data frame. How do I solve this problem? Because, I have to perform logistic regression on that NEW data frame. I tried cbind.data.frame and then similar with rbind, but that is not solving the issue.
Here is the code:
newdata <- data.frame(finalsbp, mynewT, mynewldl,mynewtypea1, mynewobesity, mynewalcohol, age, famhist)
Error in data.frame(finalsbp, mynewT, mynewldl, mynewtypea1, mynewobesity, :
arguments imply differing number of rows: 447, 443, 448, 458, 454, 429, 462
P.S. Length of age and famhist is same. i.e. 462
Without knowing more about your data, you could try to just make each vector the same length like this as indicated in this post.
a <- seq(from = 1, to = 10)
b <- seq(15, 30)
c <- seq(2, 10)
length(a) <- n
length(b) <- n
length(c) <- n
newdata <- cbind(a, b, c)
This should solve your problem, assuming you want all the blanks to appear as NA at the end of the data frame.