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Data Manipulation in R

Errors
Summary

Instruction

When we start working with new data, we should always check that everything inside is okay. Sometimes there are random errors, missing information, or values that are coded differently than how we need them. To check if we have any missing values we use the is.na() function, which looks like this:

is.na(object_name)

We can use this function to determine if there are any missing values in the census2017 data frame:

any(is.na(census2017))

Exercise

Check if we have any missing values in the census2018 data frame. Use the any() and is.na() functions. What will we get as a result?