# Usage of R functions "table" & "ifelse" when NA’s exist

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Most of the time I came across now and then in help posts questions regarding the mismatching total count of observations after employing the R functions “table” and “ifelse”. This usually creates frustration among fresh/part-time practitioners which ends up doubting the application and reverting back to their earlier tool.**Econometrics_Help**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

However, this mismatching of total count happens only when you have NA’s in the data.

Thus, to always get the total count figures, we should make practice of use following options with respect to the R functions mentioned above:

table(varname1, varname2, useNA = c(“ifany”)) # in “table” usage of “useNA” option

ifelse(is.na(varname1) == T, ***, ifelse(varname1 > 100 & varname1 <= 110, 1, 0))

# in “ifelse” usage of “is.na” option

***– here you need to provide which value to be taken if variable has values of NA.

To

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