Counting nodes and computing connectance
In this exercise, you will count the number of each type of node using the customers
dataframe. The churn
column has two different values:
- 0 for non-churners
- 1 for churners
You will also compute the network's connectance using the formula \(p=\frac{2E}{N(N-1)}\) where \(N\) is the number of nodes and \(E\) the number of edges in the network.
This exercise is part of the course
Predictive Analytics using Networked Data in R
Exercise instructions
- Count the number of churn nodes by conditioning on
customers$churn
. - Count the number of non-churn nodes by conditioning on
customers$churn
. - Count the total number of nodes and name the variable
nodes
. - Compute the network's connectance using the formula for \(p\) shown above. You can use
edges
from the previous exercise.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Count the number of churn nodes
ChurnNodes <- sum(customers$___ == ___)
# Count the number of non-churn nodes
NonChurnNodes <- sum(___)
# Count the total number of nodes
___ <- ChurnNodes + NonChurnNodes
# Compute the network connectance
connectance <- 2 * ___ / ___ / (nodes - 1)
# Print the value
connectance