I created a data frame of the following type
Name Date Value
A 01.01.01 10
B 02.01.01 2
A 04.01.01 4
...
I would like to obtain a list that ranks the elements in the name column by the total sum, provided that the dates are within a certain range.
Welcome to Stack Overflow (SO). It is very important for anybody asking questions to provide reproducible data which you can get using dput(). Please read this link. If you have tried something, you want to leave your code and describe what your challenge is. In this way, you can help SO users save more time and you are likely to receive more support. Here, I did my best to read your question, created a sample data, and did the following using the dplyr package.
# Sample data
foo <- data.frame(id = c("A", "B", "A", "C", "D", "B", "D", "E", "A", "S", "B"),
date = c("01.01.01", "02.01.01", "04.01.01", "05.01.01",
"11.01.01", "09.03.01", "12.15.01", "08.08.01",
"03.27.01", "11.16.01", "04.07.01"),
value = c(-10, -2, -4, 8, 5, 2, 10, 5, 11, 7, 8),
stringsAsFactors = FALSE)
# id date value
#1 A 01.01.01 -10
#2 B 02.01.01 -2
#3 A 04.01.01 -4
#4 C 05.01.01 8
#5 D 11.01.01 5
#6 B 09.03.01 2
#7 D 12.15.01 10
#8 E 08.08.01 5
#9 A 03.27.01 11
#10 S 11.16.01 7
#11 B 04.07.01 8
library(dplyr)
foo %>%
# Create date objects
mutate(date = as.Date(date, format = "%m.%d.%y")) %>%
# Select data points which stay between 2001-01-01 and 2001-08-31
filter(between(date, as.Date("2001-01-01"), as.Date("2001-08-31"))) %>%
# For each id group
group_by(id) %>%
# Get sum of value
summarise(Total = sum(value)) %>%
# Arrange row order by descending order with Total
arrange(desc(Total))
# id Total
#1 C 8
#2 B 6
#3 E 5
#4 A -3
