Replace missing values
In the last exercise, you noticed that for six observations, the value of RelationalNeighborSecond
was missing.
In this exercise, you will replace those missing values with 0.
This exercise is part of the course
Predictive Analytics using Networked Data in R
Exercise instructions
- Use
summary()
to inspect theRelationalNeighborSecond
feature. - Find the indices of the observations that are missing using
which()
and assign to the variabletoReplace
. - Use the
toReplace
vector to replace the missing values instudentnetworkdata$RelationalNeighborSecond
with a zero. - Inspect
RelationalNeighborSecond
again to make sure there are no longer any missing value.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Inspect the feature
___(studentnetworkdata$RelationalNeighborSecond)
# Find the indices of the missing values
toReplace <- ___(is.na(studentnetworkdata$___))
# Replace the missing values with 0
studentnetworkdata$RelationalNeighborSecond[___] <- ___
# Inspect the feature again
___(___$___)