I have this data frame df:
df <- structure(list(App = structure(c(4L, 4L, 3L, 3L, 2L, 2L, 1L), .Label = c("DB",
"End", "Mid", "Web"), class = "factor"), Server = structure(c(5L,
6L, 1L, 2L, 3L, 4L, 7L), .Label = c("GServer101", "Hserver103",
"JServer100", "Kserver200", "Server101", "Server102", "Xdb101"
), class = "factor"), Process1 = c(1L, 5L, 1L, 1L, 1L, 1L, 1L
), Process2 = c(1L, 1L, 1L, 4L, 1L, 1L, 1L), Process3 = c(NA,
NA, NA, NA, NA, NA, NA), Process4 = c(NA, NA, NA, NA, NA, NA,
NA), Process5 = c(NA, NA, NA, 1L, 1L, 1L, 1L)), .Names = c("App",
"Server", "Process1", "Process2", "Process3", "Process4", "Process5"
), class = "data.frame", row.names = c(NA, -7L))
I would like to be able to summarize df data frame and count and place process by columns as below. I need to know how many process each app has group by column name. How would I do this in R?
end <- structure(list(App = structure(c(4L, 3L, 2L, 1L), .Label = c("DB",
"End", "Mid", "Web"), class = "factor"), Process1 = c(6L, 2L,
2L, 1L), Process2 = c(2L, 5L, 2L, 1L), Process3 = c(0L, 0L, 0L,
0L), Process4 = c(0L, 0L, 0L, 0L), Process5 = c(0L, 1L, 2L, 1L
)), .Names = c("App", "Process1", "Process2", "Process3", "Process4",
"Process5"), class = "data.frame", row.names = c(NA, -4L))
You can use dplyr:
library(dplyr)
df %>%
group_by(App) %>%
summarize_at(vars(starts_with("Process")), funs(sum(., na.rm=TRUE)))
# A tibble: 4 × 6
# App Process1 Process2 Process3 Process4 Process5
# <fctr> <int> <int> <int> <int> <int>
#1 DB 1 1 0 0 1
#2 End 2 2 0 0 2
#3 Mid 2 5 0 0 1
#4 Web 6 2 0 0 0
Or if column positions are preferred, the positions can be passed to .cols parameter:
df %>%
group_by(App) %>%
summarize_at(.cols=3:7, funs(sum(., na.rm=TRUE)))
# A tibble: 4 × 6
# App Process1 Process2 Process3 Process4 Process5
# <fctr> <int> <int> <int> <int> <int>
#1 DB 1 1 0 0 1
#2 End 2 2 0 0 2
#3 Mid 2 5 0 0 1
#4 Web 6 2 0 0 0