Reputation: 5425
I have a prepared a dataset with about 20k rows of unique identifiers and ~60 columns containing boolean info if a tag is connected to that identifier:
ID Gender Tag1 Tag2 Tag3 Tag4 Tag5 Tag6 Tag 7 ...
A m 0 1 1 0 0 0 0 ...
B m 1 0 1 0 0 1 0 ...
C f 1 1 0 0 0 1 1 ...
I would like to explore the data in Gephi, but don't know what export structure/format to use. How should the data look like in order to be able to explore the relation between tags? What do I need to do to get to this structure? Do I need to further summarize it, and can I keep the gender data in there as an attribute to analyze?
Upvotes: 0
Views: 153
Reputation: 54237
Assuming your data represents a network, here is a way to export it as an edge list csv:
df <- read.table(header =T, sep =";", text = "ID;Gender;Tag1;Tag2;Tag3;Tag4;Tag5;Tag6;Tag7
A;m;0;1;1;0;0;0;0
B;m;1;0;1;0;0;1;0
C;f;1;1;0;0;0;1;1")
library(dplyr)
library(tidyr)
library(magrittr)
df %>%
gather(Target, isTrue, -ID, -Gender) %>%
filter(isTrue == 1) %>%
select(-isTrue) %>%
set_names(c("Source", "Gender", "Target")) %>%
write.csv(file = file.path(tempdir(), "my.csv"), row.names = FALSE)
You can import it in Gephi as an edge list and let gephi automatically create the node list:
Upvotes: 1