Use this tag for questions relating to functions from the dplyr package, such as group_by, summarize, filter, and select.
Given data: library(data.table) DT = data.table(category=LETTERS[1:3], b=1:3) DT # category b # 1: A 1 # 2: B 2 # 3: C 3 Using dplyr, how …
r dplyrI have a long form dataframe that have multiple entries for same date and person. jj <- data.frame(…
r dplyr tidyrSuppose I have the following data df = data.frame(name=c("A", "B", "C", "D"), score = c(10, 10, 9, 8)) I want to …
r dplyrQuestion has been edited from the original. After reading this interesting discussion I was wondering how to replace NAs in …
r dplyri have a dataframe that looks like this > data <- data.frame(foo=c(1, 1, 2, 3, 3, 3), bar=c('a', 'b', …
r dplyris there an elegant way to handle NA as 0 (na.rm = TRUE) in dplyr? data <- data.frame(a=…
r sum dplyrdplyr is amazingly fast, but I wonder if I'm missing something: is it possible summarise over several variables. For example: …
r dplyrIn dplyr I can replace NA with 0 using the following code. The issue is this inserts a list into my …
r dplyr na