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Handling Missing Values in R Programming

As the name indicates, Missing values are those elements that are not known. NA or NaN are reserved words that indicate a missing value in R Programming language for q arithmetical operations that are undefined.

R – Handling Missing Values

Missing values are practical in life.

For example, some cells in spreadsheets are empty.

Check for na in r data frame

If an insensible or impossible arithmetic operation is tried then NAs occur.

Dealing Missing Values in R

Missing Values in R, are handled with the use of some pre-defined functions:

is.na() Function for Finding Missing values:

A logical vector is returned by this function that indicates all the NA values present.

It returns a Boolean value. If NA is present in a vector it returns TRUE else FALSE.

R

Output:

[1] TRUE FALSE FALSE TRUE TRUE TRUE

Properties of Missing Values:

For testing objects that are NA use is.na()
For testing objects that are NaN use is.nan()
There are classes under which NA comes.

Hence integer class has integer type NA, the