I would like to order a data frame by a numeric vector and a character vector so that I can remove duplicates in the Code column, retaining the records with the highest value in the Value column. However, if my Category column has a "YS" or "YS1", then I want to retain those records even if the Value isn't the highest number
Here's a sample data set:
Code <- c(2,2,3,5,3,7,8)
Value <- c(17,18,35,25,67,34,2)
Category <- c("YS", "DW", "YS1", "OS", "OS", "OS1", "GD")
Dataset <- data.frame(Code, Value, Category)
Code Value Category
1 2 17 YS
2 2 18 DW
3 3 35 YS1
4 5 25 OS
5 3 67 OS
6 7 34 OS1
7 8 2 GD
When I order the data by Code (ascending) and Value (descending) and remove the duplicate records by Code, my "YS" record for Code = 2 is not retained because it has a lower Value.
order_data <- Dataset[order(Dataset$Code, -Dataset$Value),]
dataset_nodup <- order_data[!duplicated(order_data$Code),]
Code Value Category
2 2 18 DW
5 3 67 OS
4 5 25 OS
6 7 34 OS1
7 8 2 GD
I'd like to first order by my Category column and then my Value column so that my "YS" and "YS1" records are listed first. I have tried the following but it is not working.
order_data <- Dataset[order(Dataset$Code, -Dataset$Category, -Dataset$Value),]
I would like my output to look like:
Code Value Category
1 2 17 YS
2 3 67 YS1
3 5 25 OS
4 7 34 OS1
5 8 2 GD
We can use match
to bring Category
with "YS"
and "YS1"
ahead and then remove duplicates
order_data <- Dataset[with(Dataset, order(match(Category, c("YS", "YS1")),
Code, -Value)),]
dataset_nodup <- order_data[!duplicated(order_data$Code),]
dataset_nodup
# Code Value Category
#1 2 17 YS
#3 3 35 YS1
#4 5 25 OS
#6 7 34 OS1
#7 8 2 GD
Or using dplyr
library(dplyr)
Dataset %>%
arrange(match(Category, c("YS", "YS1")), Code, desc(Value)) %>%
filter(!duplicated(Code))
The technical post webpages of this site follow the CC BY-SA 4.0 protocol. If you need to reprint, please indicate the site URL or the original address.Any question please contact:yoyou2525@163.com.