I have a number of columns that I would like to remove from a data frame. I know that we can delete them individually using something like: df$x <- NULL But I was hoping to do this with fewer commands. Also, I know that I could drop columns using integer indexing like this: df <- … Read more
I’d like to remove the lines in this data frame that: a) contain NAs across all columns. Below is my example data frame. gene hsap mmul mmus rnor cfam 1 ENSG00000208234 0 NA NA NA NA 2 ENSG00000199674 0 2 2 2 2 3 ENSG00000221622 0 NA NA NA NA 4 ENSG00000207604 0 NA NA … Read more
Whenever I want to do something “map”py in R, I usually try to use a function in the apply family. However, I’ve never quite understood the differences between them — how {sapply, lapply, etc.} apply the function to the input/grouped input, what the output will look like, or even what the input can be — … Read more
I want to sort a data frame by multiple columns. For example, with the data frame below I would like to sort by column ‘z’ (descending) then by column ‘b’ (ascending): dd <- data.frame(b = factor(c(“Hi”, “Med”, “Hi”, “Low”), levels = c(“Low”, “Med”, “Hi”), ordered = TRUE), x = c(“A”, “D”, “A”, “C”), y = … Read more
Given two data frames: df1 = data.frame(CustomerId = c(1:6), Product = c(rep(“Toaster”, 3), rep(“Radio”, 3))) df2 = data.frame(CustomerId = c(2, 4, 6), State = c(rep(“Alabama”, 2), rep(“Ohio”, 1))) df1 # CustomerId Product # 1 Toaster # 2 Toaster # 3 Toaster # 4 Radio # 5 Radio # 6 Radio df2 # CustomerId State # … Read more
This question’s answers are a community effort. Edit existing answers to improve this post. It is not currently accepting new answers or interactions. When discussing performance with colleagues, teaching, sending a bug report or searching for guidance on mailing lists and here on Stack Overflow, a reproducible example is often asked and always helpful. What are … Read more
