I have data on current and previous location of individuals. I would like
to have a matrix with bilateral movement between locations. I would like
the final output to look like the second table below.
I have tried using crosstab() from the ecodist but I do not have another
variable to measure the flow. Ultimately I would like to compute the
probability of movement between cities (movement to city_i/total movement
from city_j).
Is it possible to aggregate the data in this way? Any guidance would be
highly appreciated. Thank you!
# Original data
structure(list(id = 101:115, current_location = structure(c(2L,
8L, 8L, 3L, 6L, 5L, 1L, 2L, 7L, 4L, 2L, 8L, 8L, 3L, 6L), .Label =
c("Austin",
"Boston", "Cambridge", "Durham", "Houston", "Lynn", "New Orleans",
"New York"), class = "factor"), previous_location = structure(c(6L,
2L, 4L, 6L, 7L, 5L, 1L, 3L, 6L, 2L, 6L, 2L, 4L, 6L, 7L), .Label =
c("Atlanta",
"Austin", "Cleveland", "Houston", "New Orleans", "OKC", "Tulsa"
), class = "factor")), class = "data.frame", row.names = c(NA,
-15L))
# Expected output
structure(list(X = structure(c(3L, 1L, 2L), .Label = c("Austin",
"Houston", "OKC"), class = "factor"), Boston = c(2L, NA, NA),
New.York = c(NA, 2L, 2L), Cambridge = c(2L, NA, NA)), class =
"data.frame", row.names = c(NA,
-3L))
Sincerely,
Milu
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