r - Summarizing multiple columns with dplyr? - Stack Overflow I'm struggling a bit with the dplyr-syntax I have a data frame with different variables and one grouping variable Now I want to calculate the mean for each column within each group, using dplyr i
r - Applying group_by and summarise on data while keeping all the . . . Applying group by and summarise data while extracting specific column values Hot Network Questions If modern keyboards use 8-bit microcontrollers (due to low cost), what microcontrollers did keyboards for 8-bit 16-bit era of computers use?
dplyr summarise_each standard error function - Stack Overflow I can summarise my data and calculate mean and sd values using: summary <- aspen %>% group_by(year,Spp,CO2) % gt;% summarise_each(funs(mean,sd)) However, I cannot manage to calculate standard
Using R dplyr to summarize - group_by, count, mean, sd I am fairly new to R and even newer to dplyr I have a small data set comprised of 2 columns - var1 and var2 The var1 column is comprised of num values The var2 column is comprised of factors wit
Summarize in dplyr and insert 0 for categories with no values Instead of group_by and summarise, you can use count with drop = FALSE as an argument You will need to make the education column factors first, so you can try adding at the last: count(age, as factor(education), drop = FALSE) EDIT: Put factors in order for a cleaner result
r - Using dplyr::summarise with dplyr::across and purrr::map to sum . . . For this and similar problems I made the 'dplyover' package (it is not on CRAN) Here we can use dplyover::across2() to loop over two series of columns, first, all columns ending with "pre" and second all columns ending with "post"