#' Makes raw cash flow data usable and readable.
#'
#' Processes raw cash flow data from quantmod to return
#' a tidied data frame. Raw cash flow data must be formatted
#' in a list such that every element is a data frame or
#' matrix containing quantmod data.
#'
#' \code{tidy_cashflows} produces a data frame that is 'tidy'
#' or more readily readable by a user and usable by other
#' functions within this package.
#'
#' @param x A list of raw cash flow data produced from quantmod
#'
#' @return Returns a data set that's been 'tidied' up for use
#' by other functions in this package.
#'
#' @seealso \code{\link{get_info}}
#' @seealso \code{\link{tidyinfo}}
#' @seealso \code{\link{tidy_balancesheets}}
#' @seealso \code{\link{tidy_incomestatements}}
tidy_cashflows <- function(x) {
## Calls tidy_helper to construct a list of data.frames and merges the list elements into one large data.frame
cashflows <- do.call(rbind, lapply(x, tidy_helper))
## Remove all rows that are solely NAs.
cashflows <- cashflows[rowSums(!is.na(cashflows)) >= 1, ]
rownames(cashflows) <- NULL
## These are the categories we expect from the raw data, with abbreviations for each of the variables found in the cash flows
names(cashflows) <- c("ticker", "year", "order", "NI.SL", "DP.DPL", "AM", "DT", "NCI", "CWC", "COA", "CX", "OICF", "CIA", "FCFI", "TCDP", "ISN", "IDN",
"CFA", "FEE", "NCC", "CIP", "CTP")
cashflows
}
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