If a series contains missing or NaN values, R will ignore the missing observations in its
lm command. This is convenient when one runs different models, which have different observations due to variations in whether the series with missing is included or not. (R is somewhat inconsistent, in that other functions (than lm), like mean, seem never to have heard about missing variables.)
How should end users deal with missing values in series? This is especially pertinent when they want to use formulas on data frames. Is the expectation that they create a new DataFrame for each lm?