I have the following 2 data.frames: a1 <- data.frame(a = 1:5, b=letters[1:5]) a2 <- data.frame(a = 1:3, b=letters[1:3])
I\'m getting a strange error when I run the following function: TypeIDs=c(18283,18284,17119,17121,17123,17125,17127,17129,17131,17133,18367,18369,18371,18373,18375,18377,18379)
Say I have a dataframe df with two or more columns, is there an easy way to use unique() or other R function to create a subset of unique combinations of two or more columns?
df <- data.frame(var1 = c(\'a\', \'b\', \'c\'), var2 = c(\'d\', \'e\', \'f\'), freq = 1:3) What is the simplest way to expand each row the first two columns of the data.frame above, so that each
I have a data frame. Let\'s call him bob: > head(bob) phenotypeexclusion GSM399350 3- 4- 8- 25- 44+ 11b- 11c- 19- NK1.1- Gr1- TER119-
I would like to create a new dataset where the foll开发者_StackOverflow中文版owing four conditions are all met.
I have 13 quantitative variables in a data.frame (called \'UNCA\'). The variables are named q01_a, q01_b, ...q01_m.
This question already has answers here: Replacing NAs with latest non-NA value (21 answers) Closed 4 years ago.
I have a big dataframe with columns such as: ID, time, OS, IP Each row of that dataframe corresponds to one entry. Within that dataframe for some IDs several entries (rows) exist. I would like to g
Dear StackOverFlowers (flowers in short), I have a list of data.frames (walk.sample) that I would like to collapse into a single (giant) data.frame. While collapsing, I would like to mark (adding ano
加载中,请稍侯......