Count origin-destination relationships (without direct) with R - r

Question

I have a origin-destination table like this.
library(dplyr)
set.seed(1983)
namevec <- c('Portugal', 'Romania', 'Nigeria', 'Peru', 'Texas', 'New Jersey', 'Colorado', 'Minnesota')
## Create OD pairs
df <- data_frame(origins = sample(namevec, size = 100, replace = TRUE),
destinations = sample(namevec, size = 100, replace = TRUE))
Question
I got stucked in counting the relationships for each origin-destination (with no directionality).
How can I get output that Colorado-Minnesota and Minnesota-Colorado are seen as one group?
What I have tried so far:
## Counts for each OD-pairs
df %>%
group_by(origins, destinations) %>%
summarize(counts = n()) %>%
ungroup() %>%
arrange(desc(counts))
Source: local data frame [48 x 3]
origins destinations counts
(chr) (chr) (int)
1 Nigeria Colorado 5
2 Colorado Portugal 4
3 New Jersey Minnesota 4
4 New Jersey New Jersey 4
5 Peru Nigeria 4
6 Peru Peru 4
7 Romania Texas 4
8 Texas Nigeria 4
9 Minnesota Minnesota 3
10 Nigeria Portugal 3
.. ... ... ...

Answer 1

One way is to combine the sorted combination of the two locations into a single field. Summarizing on that will remove your two original columns, so you'll need to join them back in.
paired <- df %>%
mutate(
orderedpair = paste(pmin(origins, destinations), pmax(origins, destinations), sep = "::")
)
paired
# # A tibble: 100 × 3
# origins destinations orderedpair
# <chr> <chr> <chr>
# 1 Peru Colorado Colorado::Peru
# 2 Romania Portugal Portugal::Romania
# 3 Romania Colorado Colorado::Romania
# 4 New Jersey Minnesota Minnesota::New Jersey
# 5 Minnesota Texas Minnesota::Texas
# 6 Romania Texas Romania::Texas
# 7 Peru Peru Peru::Peru
# 8 Romania Nigeria Nigeria::Romania
# 9 Portugal Minnesota Minnesota::Portugal
# 10 Nigeria Colorado Colorado::Nigeria
# # ... with 90 more rows
left_join(
paired,
group_by(paired, orderedpair) %>% count(),
by = "orderedpair"
) %>%
select(-orderedpair) %>%
distinct() %>%
arrange(desc(n))
# # A tibble: 48 × 3
# origins destinations n
# <chr> <chr> <int>
# 1 Romania Portugal 6
# 2 New Jersey Minnesota 6
# 3 Portugal Romania 6
# 4 Minnesota New Jersey 6
# 5 Romania Texas 5
# 6 Nigeria Colorado 5
# 7 Texas Nigeria 5
# 8 Texas Romania 5
# 9 Nigeria Texas 5
# 10 Peru Peru 4
# # ... with 38 more rows
(The only reason I used "::" as the separator is in the unlikely event you need to parse orderedpair; using the default " " (space) won't work with (e.g.) "New Jersey" in the mix.)