NetKnitr: an R Package to Generate Network for Your Data"

In netknitr: Knit Network Map for any Dataset

knitr::opts_chunk$set(echo = TRUE)

Are you looking to explore the complex relationships within your CSV data? The netknitr open-source framework, developed using R, RShiny, and visNetwork, makes this task simple. All you need to do is install netknitr on your computer, and you can easily generate network maps to visualize the connections within your data.

# install.packages('netknitr')
# netknitr::knitNet()

Curious about how it works? Check out the step-by-step guide provided by the netknitr framework to see how it generates network maps.

Load

# install.packages('netknitr')
library(netknitr)
library(dplyr)
library(visNetwork)

Data : It works for any data

set.seed(0009)

mtcars$name <- row.names(mtcars)
cols <- c('gear', 'name', "cyl")
my_data <- mtcars[,cols]
my_data

res <- lapply(names(my_data), FUN = function(i) {
  paste0(i, " : ", my_data[[i]])
}) %>% do.call('cbind', .) %>% as.data.frame()
names(res) <- names(my_data)
res %>% head()
my_data <- res
head(my_data)

Determine Nodes

nodes <- getNodes(my_data, columns_for_nodes = cols, group = TRUE)
nodes

Can include shapes and Colors

nodes$shape <- getShapes(nodes)
nodes$colors <- sample(c("darkred", "grey", "orange", "darkblue", "purple", 'green'), nrow(nodes), replace = T)
head(nodes)

Determine Edges

associations <- getAssociation(my_data[,cols])
edges <- getEdges(associations, nodes)
head(edges)

Network

createVisNetwork(nodes, edges)

netknitr documentation built on April 3, 2025, 5:47 p.m.