rowSumsdflikedf

rowSumsdflikedf is a term used in some programming discussions to denote a hypothetical function that encapsulates the idea of computing rowwise sums for data frame–like objects. The name blends rowSums, a common row-wise summation operation, with df and like, suggesting a function that operates on a data frame and selects columns according to a predicate. There is no universally recognized standard by this exact name, and it is generally treated as a conceptual wrapper rather than a built-in function.

Conceptually, such a function would take a data frame or matrix and return a numeric vector where each element is the sum across the selected numeric columns for that row. By default non-numeric columns would be ignored or coerced as appropriate, and missing values would be handled in a configurable way, such as via an na.rm flag.

Typical arguments might include x, the input data frame or matrix; cols, an optional vector of column indices or names to include; na.rm, a boolean indicating whether to drop missing values; and weights, an optional numeric vector applied to columns before summation.

Implementation notes: in real code, similar behavior can be achieved with rowSums(x[ , numeric_cols], na.rm=TRUE) or with rowwise summarization in packages like dplyr. A hypothetical rowSumsdflikedf would likely be a wrapper that automatically filters to numeric columns when given a data frame and delegates to a standard row-wise summation function.

Example: rowSumsdflikedf(df) would return a vector of row sums for all numeric columns; rowSumsdflikedf(df, cols=c('A','B','C'), na.rm=TRUE) would apply the same operation to the selected columns. See also rowSums, apply, and rowwise.