I am trying to build a sankey network.
This is my data and code:
library(networkD3)
nodes <- data.frame(c("A", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "D", "E", "N", "O", "P", "Q", "R"))
names(nodes) <- "name"
nodes$name = as.character(nodes$name)
links <- data.frame(matrix(
c(0, 2, 318.167,
0, 3, 73.85,
0, 4, 51.1262,
0, 5, 6.83333,
0, 6, 5.68571,
0, 7, 27.4167,
0, 8, 4.16667,
0, 9, 27.7381,
1, 10, 627.015,
1, 3, 884.428,
1, 4, 364.211,
1, 13, 12.33333,
1, 14, 9,
1, 15, 37.2833,
1, 16, 9.6,
1, 17, 30.5485), nrow=16, ncol=3, byrow = TRUE))
colnames(links) <- c("source", "target", "value")
links$source = as.integer(links$source)
links$target = as.integer(links$target)
links$value = as.numeric(links$value)
sankeyNetwork(Links = links, Nodes = nodes, Source = "source",
Target = "target", Value = "value", NodeID = "name",
fontSize = 12, fontFamily = 'Arial', nodeWidth = 20)
The problem is that A and B only have common links to D and E.
Although the links are correctly displayed, D and E are also shown at the right-bottom.
How can I avoid this ?
Note: If I specify
nodes <- data.frame(c("A", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "N", "O", "P", "Q", "R"))
no network at all is created.
Nodes must be unique, see below example. I removed repeated nodes: "D" and "E", then in links, I removed links that reference to nodes that do not exist. We have only 16 nodes, zero based 0:15. And in your links dataframe, you have last 2 rows referencing to 16 and 17.
Or as #CJYetman (networkD3 author) comments:
Another way to say it... every node that is in the nodes data frame will be plotted, even if it has the same name as another node, because the index is technically the unique id.
library(networkD3)
nodes <- data.frame(name = c("A", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "N", "O", "P", "Q", "R"),
ix = 0:15)
links <- data.frame(matrix(
c(0, 2, 318.167,
0, 3, 73.85,
0, 4, 51.1262,
0, 5, 6.83333,
0, 6, 5.68571,
0, 7, 27.4167,
0, 8, 4.16667,
0, 9, 27.7381,
1, 10, 627.015,
1, 3, 884.428,
1, 4, 364.211,
1, 13, 12.33333,
1, 14, 9,
1, 15, 37.2833), nrow=14, ncol=3, byrow = TRUE))
colnames(links) <- c("source", "target", "value")
sankeyNetwork(Links = links, Nodes = nodes, Source = "source",
Target = "target", Value = "value", NodeID = "name",
fontSize = 12, fontFamily = 'Arial', nodeWidth = 20)
Related
This question already has answers here:
Split comma-separated strings in a column into separate rows
(6 answers)
Closed 28 days ago.
I have data.frame df below.
df <- data.frame(id = c(1:12),
A = c("alpha", "alpha", "beta", "beta", "gamma", "gamma", "gamma", "delta",
"epsilon", "epsilon", "zeta", "eta"),
B = c("a", "a; b", "a", "c; d; e", "e", "e", "c; f", "g", "a", "g; h", "f", "d"),
C = c(NA, 4, 2, 7, 4, NA, 9, 1, 1, NA, 3, NA),
D = c("ii", "ii", "i", "iii", "iv", "v", "viii", "v", "viii", "i", "iii", "i"))
Column 'B' contains four entries with semicolons. How can I copy each of these rows and enter in column 'B' each of the separate values?
The expected result df2 is:
df2 <- data.frame(id = c(1, 2, 2, 3, 4, 4, 4, 5, 6, 7, 7, 8, 9, 10, 10, 11, 12),
A = c(rep("alpha", 3), rep("beta", 4), rep("gamma", 4), "delta", rep("epsilon", 3),
"zeta", "eta"),
B = c("a", "a", "b", "a", "c", "d", "e", "e", "e", "c", "f", "g", "a", "g", "h", "f", "d"),
C = c(NA, 4, 4, 2, 7, 7, 7, 4, NA, 9, 9, 1, 1, NA, NA, 3, NA),
D = c("ii", "ii", "ii", "i", "iii", "iii", "iii", "iv", "v", "viii", "viii", "v", "viii", "i", "i", "iii", "i"))
I tried this, but no luck:
df2 <- df
# split the values in column B
df2$B <- unlist(strsplit(as.character(df2$B), "; "))
# repeat the rows for each value in column B
df2 <- df2[rep(seq_len(nrow(df2)), sapply(strsplit(as.character(df1$B), "; "), length)),]
# match the number of rows in column B with the number of rows in df2
df2$id <- rep(df2$id, sapply(strsplit(as.character(df1$B), "; "), length))
# sort the dataframe by id
df2 <- df2[order(df2$id),]
We may use separate_rows here - specify the sep as ; followed by zero or more spaces (\\s*) to expand the rows
library(tidyr)
df_new <- separate_rows(df, B, sep = ";\\s*")
-checking with OP's expected
> all.equal(df_new, df2, check.attributes = FALSE)
[1] TRUE
In the base R, we may replicate the sequence of rows by the lengths of the list output
lst1 <- strsplit(df$B, ";\\s+")
df_new2 <- transform(df[rep(seq_len(nrow(df)), lengths(lst1)),], B = unlist(lst1))
row.names(df_new2) <- NULL
I'm trying to recreate this figure below, where the "to" variable (i.e. target genes) is further grouped into outer (labelled) categories (i.e. receptors).
I have generated some example data, unfortunately I'm not sure what format is needed for the additional outer categories, but it's possibly not far off the link format.
library(circlize)
links <- data.frame(from = c("A", "B", "C", "B", "C"),
to = c("D", "E", "F", "D", "E"),
value = c(1, 1, 1, 1, 1))
categories <- data.frame(from = c("D", "E", "F", "D", "E"),
to = c("X", "X", "Y", "Y", "Y"),
value = c(1, 1, 1, 1, 1))
chordDiagram(links)
Any assistance greatly appreciated!
Most times I try plot a Sankey diagram in R my CPU is maximised and the diagram does not show. Does anyone know what could be causing this? My computer is decent with i7-7600U CPU # 2.80GHz 2.90GHZ. To get the CPU back down again I have been having to restart R.
For example I was using this example code
library("networkD3")
myDf <- list(
nodes=data.frame(name=c( "A", "B", "C", "D", "E",
"V", "W", "X", "Y", "Z")),
links=data.frame(source=as.integer(c(0, 1, 2, 3, 3, 4, 4)),
target=as.integer(c(7, 6, 7, 8, 7, 5, 9)),
value = c(1, 4, 1, 5, 1, 5, 3)
)
)
sankeyNetwork(Links = myDf$links, Nodes = myDf$nodes, Source = "source",
Target = "target", Value = "value", NodeID = "name",
units = "TWh", fontSize = 25, nodeWidth = 30,
fontFamily = "sans-serif", iterations = 0)
This could be an issue with your package or R Studio configuration.
Try saving the sankeyNetwork as an HTML file using the saveNetwork() command from the same package (networkD3) and opening that.
e.g.
library("networkD3")
myDf <- list(
nodes=data.frame(name=c( "A", "B", "C", "D", "E",
"V", "W", "X", "Y", "Z")),
links=data.frame(source=as.integer(c(0, 1, 2, 3, 3, 4, 4)),
target=as.integer(c(7, 6, 7, 8, 7, 5, 9)),
value = c(1, 4, 1, 5, 1, 5, 3)
)
)
sk <- sankeyNetwork(Links = myDf$links, Nodes = myDf$nodes, Source = "source",
Target = "target", Value = "value", NodeID = "name",
units = "TWh", fontSize = 25, nodeWidth = 30,
fontFamily = "sans-serif", iterations = 0)
saveNetwork(sk,file = "sk.html")
I have two different datasets as I've shown below: df_A and df_B.
df_A <- tribble(
~book_name, ~sales_id,
"A", 1,
"B", 2,
"C", 3,
"D", 4,
"E", 5,
"F", 3,
"G", 8,
"H", 6,
"I", 7,
"J", 7,
)
df_B <- tribble(
~book_name, ~sales_id,
"A", 1,
"N", 2,
"C", 3,
"E", 4,
"K", 5,
"R", 3,
"S", 8,
"U", 6,
"Z", 7,
"Y", 7,
)
Now, I want to see the overlap of these two datasets on book_name. Namely, I want to make a list that shows us the book_name that are both in the datasets and also how similar these two datasets according to the book_name column.
Is there any idea to do this in an accurate way?
You can do an inner join between the two dataframes which automatically gives you the intersection between the two dataframes.
This should do the trick,
library(dplyr)
# Creating first data frame
df_A <- tribble(
~book_name, ~sales_id,
"A", 1,
"B", 2,
"C", 3,
"D", 4,
"E", 5,
"F", 3,
"G", 8,
"H", 6,
"I", 7,
"J", 7,
)
# Creating second data frame
df_B <- tribble(
~book_name, ~sales_id,
"A", 1,
"N", 2,
"C", 3,
"E", 4,
"K", 5,
"R", 3,
"S", 8,
"U", 6,
"Z", 7,
"Y", 7,
)
# Joining between the two dataframes to get the common values between the two
result <-
df_A %>%
inner_join(df_B, by = "book_name")
Here is a base R solution, where maybe you can use intersect(), i.e.,
overlap <- subset(df_A,book_name %in% intersect(book_name,df_B$book_name))
such that
> overlap
# A tibble: 3 x 2
book_name sales_id
<chr> <dbl>
1 A 1
2 C 3
3 E 5
I am new to igraph and it seems to be a very powerful (and therefore also complex) package.
I tried to convert the following lists into an igraph object.
graph <- list(s = c("a", "b"),
a = c("s", "b", "c", "d"),
b = c("s", "a", "c", "d"),
c = c("a", "b", "d", "e", "f"),
d = c("a", "b", "c", "e", "f"),
e = c("c", "d", "f", "z"),
f = c("c", "d", "e", "z"),
z = c("e", "f"))
weights <- list(s = c(3, 5),
a = c(3, 1, 10, 11),
b = c(5, 3, 2, 3),
c = c(10, 2, 3, 7, 12),
d = c(15, 7, 2, 11, 2),
e = c(7, 11, 3, 2),
f = c(12, 2, 3, 2),
z = c(2, 2))
Interpretation is as follows: s is the starting node, it links to nodes a and b. The edges are weighted 3 for s to a and 5 for s to b and so on.
I tried all kinds of functions from igraph but only got all kinds of errors. What is the most elegant and easy way to convert the above into an igraph object for plotting the graph?
Create an edgelist and then a graph from that. Assign the weights and plot it.
set.seed(123)
e <- as.matrix(stack(graph))
g <- graph_from_edgelist(e)
E(g)$weight <- stack(weights)[[1]]
plot(g, edge.label = E(g)$weight)