November 2017
Beginner
286 pages
8h 13m
English
book
Statistics for Data Science
by James C. Mott, Rajprasath Subramanian, Shaikh Salamatullah, James D. Miller, Vijayakumar Ramdoss
Content preview from Statistics for Data Science
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Missing values
Critical to the outcome of any analysis is the availability of data.
Suppose there are cases within our population that have values that are missing. You may want to ignore (or omit) those cases in your analysis. Rather than spending time writing code to deal with these cases, you can use the handy R generic function na. The na.omit function evaluates each case in your file and if it is missing any values for any of the variables, it drops that case automatically.
The following example shows the use of the R functions na.omit and nrow on a file with missing values:
Note the row (case) count before and after the use of na.omit ...
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