fnobs function

Fast (Grouped) Observation Count for Matrix-Like Objects

fnobs is a generic function that (column-wise) computes the number of non-missing values in x, (optionally) grouped by g. It is much faster than sum(!is.na(x)). The TRA argument can further be used to transform x using its (grouped) observation count.

fnobs(x, ...)

## Default S3 method:
fnobs(x, g = NULL, TRA = NULL, use.g.names = TRUE, ...)

## S3 method for class 'matrix'
fnobs(x, g = NULL, TRA = NULL, use.g.names = TRUE, drop = TRUE, ...)

## S3 method for class 'data.frame'
fnobs(x, g = NULL, TRA = NULL, use.g.names = TRUE, drop = TRUE, ...)

## S3 method for class 'grouped_df'
fnobs(x, TRA = NULL, use.g.names = FALSE, keep.group_vars = TRUE, ...)

Arguments

• x: a vector, matrix, data frame or grouped data frame (class 'grouped_df').
• g: a factor, GRP object, atomic vector (internally converted to factor) or a list of vectors / factors (internally converted to a GRP object) used to group x.
• TRA: an integer or quoted operator indicating the transformation to perform: 0 - "na" | 1 - "fill" | 2 - "replace" | 3 - "-" | 4 - "-+" | 5 - "/" | 6 - "%" | 7 - "+" | 8 - "*" | 9 - "%%" | 10 - "-%%". See TRA.
• use.g.names: logical. Make group-names and add to the result as names (default method) or row-names (matrix and data frame methods). No row-names are generated for data.table's.
• drop: matrix and data.frame method: Logical. TRUE drops dimensions and returns an atomic vector if g = NULL and TRA = NULL.
• keep.group_vars: grouped_df method: Logical. FALSE removes grouping variables after computation.
• ...: arguments to be passed to or from other methods. If TRA is used, passing set = TRUE will transform data by reference and return the result invisibly.

Details

fnobs preserves all attributes of non-classed vectors / columns, and only the 'label' attribute (if available) of classed vectors / columns (i.e. dates or factors). When applied to data frames and matrices, the row-names are adjusted as necessary.

Returns

Integer. The number of non-missing observations in x, grouped by g, or (if TRA is used) x transformed by its number of non-missing observations, grouped by g.

See Also

fndistinct, Fast Statistical Functions , Collapse Overview

Examples

## default vector method
fnobs(airquality$Solar.R)                   # Simple Nobs
fnobs(airquality$Solar.R, airquality$Month) # Grouped Nobs

## data.frame method
fnobs(airquality)
fnobs(airquality, airquality$Month)
fnobs(wlddev)                               # Works with data of all types!
head(fnobs(wlddev, wlddev$iso3c))

## matrix method
aqm <- qM(airquality)
fnobs(aqm)                                  # Also works for character or logical matrices
fnobs(aqm, airquality$Month)

## method for grouped data frames - created with dplyr::group_by or fgroup_by
airquality |> fgroup_by(Month) |> fnobs()
wlddev |> fgroup_by(country) |>
           fselect(PCGDP,LIFEEX,GINI,ODA) |> fnobs()