how to sum based on three different condition in R - r

Question

The following is my data.
gcode code year P Q
1 101 2000 1 3
1 101 2001 2 4
1 102 2000 1 1
1 102 2001 4 5
1 102 2002 2 6
1 102 2003 6 5
1 103 1999 6 1
1 103 2000 4 2
1 103 2001 2 1
2 104 2000 1 3
2 104 2001 2 4
2 105 2001 4 5
2 105 2002 2 6
2 105 2003 6 5
2 105 2004 6 1
2 106 2000 4 2
2 106 2001 2 1
gcode 1 has 3 different codes 101, 102 and 103. They all have the same year (2000 and 2001). I want to sum up P and Q for these years. Otherwise, I want to delete the irrelevant data. I want to do the same for gcode 2 as well.
How can I get the result like this?
gcode year P Q
1 2000 1+1+4 3+1+2
1 2001 2+4+2 4+5+1
2 2001 2+4+2 4+5+1

Answer 1

We can split the data based on gcode subset the data based on common year which is present in all the code and aggregate the data by gcode and year.
do.call(rbind, lapply(split(df, df$gcode), function(x) {
aggregate(cbind(P, Q)~gcode+year,
subset(x, year %in% Reduce(intersect, split(x$year, x$code))), sum)
}))
# gcode year P Q
#1.1 1 2000 6 6
#1.2 1 2001 8 10
#2 2 2001 8 10
Using dplyr with similar logic we can do
library(dplyr)
df %>%
group_split(gcode) %>%
purrr::map_df(. %>%
group_by(year) %>%
filter(n_distinct(code) == n_distinct(.$code)) %>%
group_by(gcode, year) %>%
summarise_at(vars(P:Q), sum))
data
df <- structure(list(gcode = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), code = c(101L, 101L, 102L, 102L,
102L, 102L, 103L, 103L, 103L, 104L, 104L, 105L, 105L, 105L, 105L,
106L, 106L), year = c(2000L, 2001L, 2000L, 2001L, 2002L, 2003L,
1999L, 2000L, 2001L, 2000L, 2001L, 2001L, 2002L, 2003L, 2004L,
2000L, 2001L), P = c(1L, 2L, 1L, 4L, 2L, 6L, 6L, 4L, 2L, 1L,
2L, 4L, 2L, 6L, 6L, 4L, 2L), Q = c(3L, 4L, 1L, 5L, 6L, 5L, 1L,
2L, 1L, 3L, 4L, 5L, 6L, 5L, 1L, 2L, 1L)), class = "data.frame",
row.names = c(NA, -17L))

Answer 2

An option using data.table package:
years <- DT[, {
m <- min(year)
ty <- tabulate(year-m)
.(year=which(ty==uniqueN(code)) + m)
}, gcode]
DT[years, on=.(gcode, year),
by=.EACHI, .(P=sum(P), Q=sum(Q))]
output:
gcode year P Q
1: 1 2000 6 6
2: 1 2001 8 10
3: 2 2001 8 10
data:
library(data.table)
DT <- fread("gcode code year P Q
1 101 2000 1 3
1 101 2001 2 4
1 102 2000 1 1
1 102 2001 4 5
1 102 2002 2 6
1 102 2003 6 5
1 103 1999 6 1
1 103 2000 4 2
1 103 2001 2 1
2 104 2000 1 3
2 104 2001 2 4
2 105 2001 4 5
2 105 2002 2 6
2 105 2003 6 5
2 105 2004 6 1
2 106 2000 4 2
2 106 2001 2 1")

Answer 3

I came up with the following solution. First, I counted how many times each year appear for each gcode. I also counted how many unique codes exist for each gcode. Then, join the two results using left_join(). Then, I identified rows that have same values in n_year and n_code. Then, I joined the original data frame, which is called mydf. Then, I defined groups by gcode and year, and summed up P and Q for each group.
library(dplyr)
left_join(count(mydf, gcode, year, name = "n_year"),
group_by(mydf, gcode) %>% summarize(n_code = n_distinct(code))) %>%
filter(n_year == n_code) %>%
left_join(mydf, by = c("gcode", "year")) %>%
group_by(gcode, year) %>%
summarize_at(vars(P:Q),
.funs = list(~sum(.)))
# gcode year P Q
# <int> <int> <int> <int>
#1 1 2000 6 6
#2 1 2001 8 10
#3 2 2001 8 10
Another idea
I was reviewing this question later and came up with the following idea, which is much simpler. First, I defined groups by gcode and year. For each group, I counted how many data points existed using add_count(). Then, I defined groups again with gcode only. For each gcode group, I wanted to get rows that meet n == n_distinct(code). n is a column created by add_count(). If a number in n and a number returned by n_distinct() matches, that means that a year in that row exists among all code. Finally, I defined groups by gcode and year again and summed up values in P and Q.
group_by(mydf, gcode, year) %>%
add_count() %>%
group_by(gcode) %>%
filter(n == n_distinct(code)) %>%
group_by(gcode, year) %>%
summarize_at(vars(P:Q),
.funs = list(~sum(.)))
# This is the same code in data.table.
setDT(mydf)[, check := .N, by = .(gcode, year)][,
.SD[check == uniqueN(code)], by = gcode][,
lapply(.SD, sum), .SDcols = P:Q, by = .(gcode, year)][]