Using lm() in R in data with many zeroes gives error - r

Question

I'm new to data analysis, and I have a couple questions about using lm() in R to create a linear regression model of my data.
My data looks like this:
testID userID timeSpentStudying testGrade
12345 007 10 90
09876 008 0 75
And my model:
model <- lm(formula = data$testGrade ~ timeSpentStudying, data = data)
I'm getting the following error (twice), across just under 60 rows of data from RStudio:
Warning messages:
1: In sqrt(crit * p * (1 - hh)/hh) : NaNs produced
2: In sqrt(crit * p * (1 - hh)/hh) : NaNs produced
My question is, does the problem have to do with the data containing many instances of zero being the value, such as above under the 'timeSpentStudying' column? If so, how do I handle that? Shouldn't lm() be able to handle values of zero, especially if that would give significance to the data itself?
Thanks!

Answer 1

So far I have been unable to replicate this, e.g.:
dd <- data.frame(y=rnorm(1000),x=c(rep(0,990),1:10))
model <- lm(y~x, data = dd)
summary(model)
Searching the R code base for the code listed in your error and tracing back indicates that the relevant lines are in plot.lm, the function that plots diagnostics, and that the problem is that you are somehow getting a value >1 for the leverage or "hat values" of one of your data points. However, I can't see how you could be achieving that. Data would make this much clearer!