nodes

问题 I wrote some R code that simulates some graph network based data, creates a graph, removes nodes if there are less than 2 connections and makes it an interactive graph. However, when I plot the graph, I can clearly see that nodes with 0 connections are still there (if nodes with less 2 connections are deleted, this means nodes with 1 connection and 0 connections should also be deleted). Here is a picture that shows nodes with 0 connections have not been deleted: Can someone please tell me

问题 I wrote some R code that simulates some graph network based data, creates a graph, removes nodes if there are less than 2 connections and makes it an interactive graph. However, when I plot the graph, I can clearly see that nodes with 0 connections are still there (if nodes with less 2 connections are deleted, this means nodes with 1 connection and 0 connections should also be deleted). Here is a picture that shows nodes with 0 connections have not been deleted: Can someone please tell me

问题 I wrote some R code that simulates some graph network based data, creates a graph, removes nodes if there are less than 2 connections and makes it an interactive graph. However, when I plot the graph, I can clearly see that nodes with 0 connections are still there (if nodes with less 2 connections are deleted, this means nodes with 1 connection and 0 connections should also be deleted). Here is a picture that shows nodes with 0 connections have not been deleted: Can someone please tell me

问题 I wrote some R code that simulates some graph network based data, creates a graph, removes nodes if there are less than 2 connections and makes it an interactive graph. However, when I plot the graph, I can clearly see that nodes with 0 connections are still there (if nodes with less 2 connections are deleted, this means nodes with 1 connection and 0 connections should also be deleted). Here is a picture that shows nodes with 0 connections have not been deleted: Can someone please tell me

问题 My heroku app cannot be accessed after a build. The logs show that the web server node and worker node both are listening. It's a flask app run by gunicorn and it has 2 addons - newrelic and redistogo. Error: This site can’t be reached. appname.herokuapp.com’s server IP address could not be found. DNS_PROBE_FINISHED_NXDOMAIN Logs: ```2020-02-05T16:24:31.556201+00:00 heroku[worker.1]: Starting process with command `python worker.py` 2020-02-05T16:24:32.278863+00:00 heroku[worker.1]: State

问题 My heroku app cannot be accessed after a build. The logs show that the web server node and worker node both are listening. It's a flask app run by gunicorn and it has 2 addons - newrelic and redistogo. Error: This site can’t be reached. appname.herokuapp.com’s server IP address could not be found. DNS_PROBE_FINISHED_NXDOMAIN Logs: ```2020-02-05T16:24:31.556201+00:00 heroku[worker.1]: Starting process with command `python worker.py` 2020-02-05T16:24:32.278863+00:00 heroku[worker.1]: State

问题 Using R, I create some fake data about a group of people and their relationships to each other: #relationship data Data_I_Have <- data.frame( "Node_A" = c("John", "John", "John", "Peter", "Peter", "Peter", "Tim", "Kevin", "Adam", "Adam", "Xavier"), "Node_B" = c("Claude", "Peter", "Tim", "Tim", "Claude", "Henry", "Kevin", "Claude", "Tim", "Henry", "Claude"), " Place_Where_They_Met" = c("Chicago", "Boston", "Seattle", "Boston", "Paris", "Paris", "Chicago", "London", "Chicago", "London", "Paris"

问题 Using R, I create some fake data about a group of people and their relationships to each other: #relationship data Data_I_Have <- data.frame( "Node_A" = c("John", "John", "John", "Peter", "Peter", "Peter", "Tim", "Kevin", "Adam", "Adam", "Xavier"), "Node_B" = c("Claude", "Peter", "Tim", "Tim", "Claude", "Henry", "Kevin", "Claude", "Tim", "Henry", "Claude"), " Place_Where_They_Met" = c("Chicago", "Boston", "Seattle", "Boston", "Paris", "Paris", "Chicago", "London", "Chicago", "London", "Paris"

问题 I am trying to find out if node attributes and edge attributes are used during graph network clustering (i.e. community detection algorithms) in R. I could not find an answer, so I decided to write some code for this problem and compare the differences. I first created a file of node attributes and edge attributes - then I created a graph network. On this graph network, I performed the clustering/community detection algorithm. In Method 1, I use the full information from the edges and nodes

问题 I posted a comment/reply to another stackoverflow post over here : R: Understanding Graph relating to graphs in R. If you create some data corresponding to movies and actors (in which movies can not be connected to other movies directly, and actors can not be connected to other actors directly), you write some R code to check if your graph is bipartite: library(igraph) film_data <- data.frame( "movie" = c("movie_1", "movie_1", "movie_1", "movie_2", "movie_2", "movie_2", "movie_3", "movie_3",