First, I have a shortest path matrix generated with igraph (shortest path)
When I want to retreive the node names with "get.shortest.path" it just brings me the number of each column and not its name:
[,a] [,b] [,c] [,d] [,e] [,f] [,g] [,h] [,i] [,j]
[a,] 0 1 2 3 4 5 4 3 2 1
[b,] 1 0 1 2 3 4 5 4 3 2
[c,] 2 1 0 1 2 3 4 5 4 3
[d,] 3 2 1 0 1 2 3 4 5 4
[e,] 4 3 2 1 0 1 2 3 4 5
[f,] 5 4 3 2 1 0 1 2 3 4
[g,] 4 5 4 3 2 1 0 1 2 3
[h,] 3 4 5 4 3 2 1 0 1 2
[i,] 2 3 4 5 4 3 2 1 0 1
[j,] 1 2 3 4 5 4 3 2 1 0
then:
get.shortest.paths(g, 5, 1)
the answer is:
[[1]]
[1] 5 4 3 2
I want the node names not their numbers. Is there any solution? I checked vpath, too.
This does the trick for me:
paths <- get.shortest.paths(g, 5, 1)$vpath
names <- V(g)$name
lapply(paths, function(x) { names[x] })
There is a slightly simpler solution that does not use lapply:
paths <- get.shortest.paths(g, 5, 1)
V(g)$name[paths$vpath[[1]]]
Related
I have a target where I have this DUPLICATE checker with COUNT for multiple arrays. As we can see. Any suggestions on how I make this work? Thank you and have a nice day.
DATA:
id
value
1
[5,6,8,4,2]
2
[2,3,4,1,8]
3
[9,3,2,1,10]
Normal result:
number
count
1
2
2
3
3
2
4
2
5
1
6
1
7
0
8
2
9
1
10
1
This is my target result with sorting (Highest count):
number
count
2
3
1
2
3
2
4
2
8
2
5
1
6
1
10
1
9
1
Fiddle: http://sqlfiddle.com/#!9/c1495/1
I have a table named "locations":
id name parent
1 Sweden 0
2 England 0
3 Stockholm 1
4 Vasteras 1
5 Town 3
6 Town 4
7 London 2
8 Town 7
And table named "closure":
parent child depth
1 1 0
1 3 1
1 4 1
1 5 2
1 6 2
2 2 0
2 7 1
2 8 2
3 3 0
3 5 1
4 4 0
4 6 1
5 5 0
6 6 0
7 7 0
7 8 1
8 8 0
Now I'd like to convert a hierarchy of names I have on hand into location IDs.
Example: Sweden => Stockholm => Town would yield:
id name parent
1 Sweden 0
3 Stockholm 1
5 Town 3
How could I do this without also returning any of the places named "town", but where the parents aren't exactly the same?
I'm using the clustercommand and am having difficulties due to insufficient memory. To get around this problem I would like to delete all duplicate observations.
I would like to cluster via the variables A, B and C and I identify duplicate values as so:
/* Create dummy data */
input id A B C
1 1 1 1
2 1 1 1
3 1 1 1
4 2 2 2
5 2 2 2
6 2 2 2
7 2 2 2
8 3 3 3
9 3 3 3
10 4 4 4
end
sort A B C id
duplicates tag A B C, gen(dup_tag)
I would like to add a variable dup_ID which tells me that ids 2 and 3 are duplicates of id 1, ids 5 and 6 of id 4, and so on. How could I do this?
/* Desired result */
id A B C dup_id
1 1 1 1 1
2 1 1 1 1
3 1 1 1 1
4 2 2 2 4
5 2 2 2 4
6 2 2 2 4
7 2 2 2 4
8 3 3 3 8
9 3 3 3 8
10 4 4 4 10
duplicates is a wonderful command (see its manual entry for why I say that), but you can do this directly:
bysort A B C : gen tag = _n == 1
tags the first occurrence of duplicates of A B C as 1 and all others as 0. For the other way round use _n > 1, _n != 1, or whatever.
EDIT:
So then the id of tagged observations is just
by A B C: gen dup_id = id[1]
For basic technique with by: see (e.g.) this discussion
You can refer to the first observation in each group of A B C using the subscript [1] on ID. Note the (id) argument in bysort, which sorts by id, but identifies the groups by A, B, and C only.
clear
input id A B C
1 1 1 1
2 1 1 1
3 1 1 1
4 2 2 2
5 2 2 2
6 2 2 2
7 2 2 2
8 3 3 3
9 3 3 3
10 4 4 4
end
bysort A B C (id): gen dup_id = id[1]
li, noobs sepby(dup_id)
yielding
+-------------------------+
| id A B C dup_id |
|-------------------------|
| 1 1 1 1 1 |
| 2 1 1 1 1 |
| 3 1 1 1 1 |
|-------------------------|
| 4 2 2 2 4 |
| 5 2 2 2 4 |
| 6 2 2 2 4 |
| 7 2 2 2 4 |
|-------------------------|
| 8 3 3 3 8 |
| 9 3 3 3 8 |
|-------------------------|
| 10 4 4 4 10 |
+-------------------------+
item qty
1201-10-005-A 1
1110-01-006-A 1
1112-01-006-A 1
1202-01-008-A 1
1202-01-023-A 1
G-1000-00-003-A 1
Q-2252-00-004-D 1
1150-01-002-A 1
1201-01-009-A 1
1201-01-010-A 1
1201-01-012-A 1
1201-01-013-A 1
1201-02-005-A 1
1201-02-006-A 1
1201-04-001-A 1
1201-05-001-A 1
1201-06-002-A 1
1201-06-003-A 1
1201-06-004-A 1
1201-07-001-A 1
1201-07-002-A 1
1201-07-005-A 1
1201-07-006-A 1
1201-07-009-A 1
1201-07-007-A 1
1201-06-004-A 2
1201-07-001-A 2
1201-07-002-A 2
1201-07-005-A 2
1201-07-006-A 2
1201-07-007-A 2
1201-07-009-A 2
1201-10-005-A 2
1202-01-008-A 2
1202-01-023-A 2
1110-01-006-A 2
1201-06-004-A 3
1201-07-001-a 3
1201-07-002-A 3
1201-07-005-A 3
1201-07-006-a 3
1201-07-007-A 3
1201-07-009-A 3
1201-10-005-A 3
1202-01-008-A 3
1202-01-023-A 3
1110-01-006-A 3
1130-03-009-A 3
1201-06-004-A 4
1201-07-001-A 4
1201-07-002-A 4
1201-07-005-A 4
1201-07-006-A 4
1201-07-007-A 4
1201-07-009-A 4
1201-10-005-A 4
1202-01-008-A 4
1202-01-023-A 4
1110-01-006-A 4
1130-03-009-A 4
1110-01-006-A 5
1130-03-009-A 5
1201-01-009-A 1
0004-08-107-A 1
0010-08-012-A 1
1000-00-003-B 1
Same item repeat show max quantuty value ony
You need to use Group By:
select item,max(quantity)
from table
group by item
Hello i would like to know how can i merge 2 data frames in R,there is a merge function ,but i would like to do this :
data frame1
X Y Z
1 1 1 1
2 1 1 1
3 1 1 1
4 1 1 1
5 1 1 1
data frame 2
A B C
1 2 2 2
2 2 2 2
3 2 2 2
mergedataframe
X Y Z A B C
1 1 1 1
2 1 1 1
3 1 1 1 2 2 2
4 1 1 1 2 2 2
5 1 1 1 2 2 2
the think is i must synchronize 3 csv files (dataframe) and i have no idea how to it with R.
if somebody have any idea about it ,thank u
i redit my post i would like my merged data frame like that :
data frame1
X Y Z
1 1 1 1
2 1 1 1
3 1 1 1
4 1 1 1
5 1 1 1
6 1 1 1
data frame 2
A B C
1 2 2 2
2 2 2 2
mergedataframe
X Y Z A B C
1 1 1 1
2 1 1 1
3 1 1 1 2 2 2
4 1 1 1 2 2 2
5 1 1 1
6 1 1 1
df1 <- data.frame(X=rep(1,5),Y=1, Z=1)
df2 <- data.frame(A=rep(2,3),B=2, C=2)
#rownames(df2) <- 3:5
rownames(df2) <- tail(rownames(df1), nrow(df2))
mergedataframe <- merge(df1,df2, by=0, all=TRUE)
mergedataframe <- mergedataframe[,-1]
mergedataframe
X Y Z A B C
1 1 1 1 NA NA NA
2 1 1 1 NA NA NA
3 1 1 1 2 2 2
4 1 1 1 2 2 2
5 1 1 1 2 2 2