Practical Predictive Analytics

Recombining the churner and non-churners

Now that we have simulated the variables separately for the two groups, we will recombine them and then remove some of the NAs:

#bind them back together====d1 <- data.frame(xchurn.list)d2 <- data.frame(xnochurn.list)ChurnStudy <- rbind(d1,d2)ChurnStudy <- na.omit(ChurnStudy)summary(ChurnStudy)nrow(ChurnStudy)savehistory (file="ch5 generate churn data")

The str, summary, and nrow functions will output to the console, and the savehistory() function will save all of the commands that were run to an external file:

Notice that the summary output shows satisfaction as a factor and satisfaction2 as a character ...