[R] Bilateral matrix

[Miluji Sb]

Dear William and Ben,

Thank you for your replies and elegant solutions. I am having trouble with
the fact that two of the previous locations do not appear in current
locations (that is no one moved to OKC and Dallas from other cities), so
these two cities are not being included in the output.

I have provided a better sample of the data and the ideal output (wide form
- a 10x10 bilateral matrix) but haven't been able to do this. Would it be
easier if I create variable for each ID - it would be equal to 1 if the
person moved? I am a bit lost - thank you again!

### data
structure(list(ID = 1:12, previous_location. = structure(c(3L,
9L, 8L, 10L, 2L, 5L, 1L, 7L, 4L, 6L, 10L, 5L), .Label = c("Atlanta",
"Austin", "Boston", "Cambridge", "Dallas", "Durham", "Lynn",
"New Orleans", "New York", "OKC"), class = "factor"), current_location. =
structure(c(8L,
3L, 3L, 8L, 4L, 1L, 4L, 5L, 6L, 4L, 7L, 2L), .Label = c("Atlanta",
"Austin", "Boston", "Cambridge", "Durham", "Lynn", "New Orleans",
"New York"), class = "factor")), class = "data.frame", row.names = c(NA,
-12L))

### ideal output
structure(list(previous_location. = structure(c(3L, 9L, 8L, 10L,
2L, 5L, 1L, 7L, 4L, 6L), .Label = c("Atlanta", "Austin", "Boston",
"Cambridge", "Dallas", "Durham", "Lynn", "New Orleans", "New York",
"OKC"), class = "factor"), Boston = c(0L, 1L, 1L, 0L, 0L, 0L,
0L, 0L, 0L, 0L), New.York = c(1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L,
0L, 0L), New.Orleans = c(0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L,
0L), OKC = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), Austin = c(0L,
0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L), Dallas = c(0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L), Atlanta = c(0L, 0L, 0L, 0L, 0L, 1L,
0L, 0L, 0L, 0L), Lynn = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L,
0L), Cambridge = c(0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L), Durham = c(0L,
0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L)), class = "data.frame", row.names =
c(NA,
-10L))

Sincerely,

Milu

On Wed, May 16, 2018 at 5:12 PM, Bert Gunter <bgunter.4567 using gmail.com> wrote:

> xtabs does this automatically if your cross classifying variables are
> factors with levels all the cities (sorted, if you like):
>
>  > x <- sample(letters[1:5],8, rep=TRUE)
> > y <- sample(letters[1:5],8,rep=TRUE)
>
> > xtabs(~ x + y)
>    y
> x   c d e
>   a 1 0 0
>   b 0 0 1
>   c 1 0 0
>   d 1 1 1
>   e 1 1 0
>
> > lvls <- sort(union(x,y))
> > x <- factor(x, levels = lvls)
> > y <- factor(y, levels = lvls)
>
> > xtabs( ~ x + y)
>    y
> x   a b c d e
>   a 0 0 1 0 0
>   b 0 0 0 0 1
>   c 0 0 1 0 0
>   d 0 0 1 1 1
>   e 0 0 1 1 0
>
> Cheers,
> Bert
>
>
>
> Bert Gunter
>
> "The trouble with having an open mind is that people keep coming along and
> sticking things into it."
> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
>
> On Wed, May 16, 2018 at 7:49 AM, Miluji Sb <milujisb using gmail.com> wrote:
>
>> Dear Bert and Huzefa,
>>
>> Apologies for the late reply, my account got hacked and I have just
>> managed to recover it.
>>
>> Thank you very much for your replies and the solutions. Both work well.
>>
>> I was wondering if there was any way to ensure (force) that all possible
>> combinations show up in the output. The full dataset has 25 cities but of
>> course people have not moved from Boston to all the other 24 cities. I
>> would like all the combinations if possible.
>>
>> Thank you again!
>>
>> Sincerely,
>>
>> Milu
>>
>> On Tue, May 8, 2018 at 6:28 PM, Bert Gunter <bgunter.4567 using gmail.com>
>> wrote:
>>
>>> or in base R : ?xtabs    ??
>>>
>>> as in:
>>> xtabs(~previous_location + current_location,data=x)
>>>
>>> (You can convert the 0s to NA's if you like)
>>>
>>>
>>> Cheers,
>>> Bert
>>>
>>>
>>>
>>> Bert Gunter
>>>
>>> "The trouble with having an open mind is that people keep coming along
>>> and sticking things into it."
>>> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
>>>
>>> On Tue, May 8, 2018 at 9:21 AM, Huzefa Khalil <huzefa.khalil using umich.edu>
>>> wrote:
>>>
>>>> Dear Miluji,
>>>>
>>>> If I understand correctly, this should get you what you need.
>>>>
>>>> temp1 <-
>>>> 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))
>>>>
>>>> dcast(temp1, previous_location ~ current_location)
>>>>
>>>> On Tue, May 8, 2018 at 12:10 PM, Miluji Sb <milujisb using gmail.com> wrote:
>>>> > 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
>>>> >
>>>> >         [[alternative HTML version deleted]]
>>>> >
>>>> > ______________________________________________
>>>> > R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
>>>> > https://stat.ethz.ch/mailman/listinfo/r-help
>>>> > PLEASE do read the posting guide http://www.R-project.org/posti
>>>> ng-guide.html
>>>> > and provide commented, minimal, self-contained, reproducible code.
>>>>
>>>> ______________________________________________
>>>> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
>>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>>> PLEASE do read the posting guide http://www.R-project.org/posti
>>>> ng-guide.html
>>>> and provide commented, minimal, self-contained, reproducible code.
>>>>
>>>
>>>
>>
>

	[[alternative HTML version deleted]]