# ncases: Number of Cases in Data In quest: Prepare Questionnaire Data for Analysis

## Description

`ncases` counts how many cases in a data.frame there are that have a specified frequency of observed values across a set of columns. This function is similar to `nrow` and is essentially `partial.cases` + `sum`. The user can have `ncases` return the number of complete cases by calling `ov.min = 1`, `prop = TRUE`, and `inclusive = TRUE` (the default).

## Usage

 `1` ```ncases(data, vrb.nm = names(data), ov.min = 1, prop = TRUE, inclusive = TRUE) ```

## Arguments

 `data` data.frame or matrix of data. `vrb.nm` a character vector of colnames from `data` specifying the variables. `ov.min` minimum frequency of observed values required per row. If `prop` = TRUE, then this is a decimal between 0 and 1. If `prop` = FALSE, then this is a integer between 0 and `length(vrb.nm)`. `prop` logical vector of length 1 specifying whether `ov.min` should refer to the proportion of observed values (TRUE) or the count of observed values (FALSE). `inclusive` logical vector of length 1 specifying whether the case should be included if the frequency of observed values in a row is exactly equal to `ov.min`.

## Value

integer vector of length 1 providing the nrow in `data` with the given amount of observed values.

`partial.cases` `nrow`
 ```1 2 3 4 5``` ```vrb_nm <- c("Ozone","Solar.R","Wind") nrow(airquality[vrb_nm]) # number of cases regardless of missing data sum(complete.cases(airquality[vrb_nm])) # number of complete cases ncases(data = airquality, vrb.nm = c("Ozone","Solar.R","Wind"), ov.min = 2/3) # number of rows with at least 2 of the 3 variables observed ```