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Good job! There is also another way to do this. The first method showed how to do it manually; now we'll see how to make R do all the work for us. We can get the same result by using the function na.omit(), which looks like this:

census2017_clean <- na.omit(census2017)

As you see, we only need to enter the data frame name. The na.omit() function returns a new data frame with all rows with missing values filtered out.


Use na.omit() on the census2018 data frame and again assign it to the census2018_clean variable.