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#' Makes raw incomestatement data usable and readable.
#'
#' Tidies raw income statement data produced from quantmod and returns
#' the tidied data frame. Raw income statement data must be formatted
#' in a list such that every element is a data frame or matrix containing
#' quantmod data.
#'
#' \code{tidy_incomestatements} 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 incomestatement file 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_cashflows}}
#' @seealso \code{\link{tidy_balancesheets}}
tidy_incomestatements <- function(x) {
## Calls tidy_helper to construct a list of data.frames and merges the list elements into one large data.frame
# incomestatements <- do.call(rbind, lapply(x, tidy_helper))
incomestatements <- dplyr::bind_rows(lapply(x, tidy_helper))
## Remove all rows that are solely NAs.
incomestatements <- incomestatements[rowSums(!is.na(incomestatements)) >= 1, ]
rownames(incomestatements) <- NULL
## These are the categories we expect from the raw data, with abbreviations for each of the variables found in the income statements
## The wanted categories were based on previous outputs from Google Finance API which is discontinued now
## So we have to map the current output (from Yahoo Finance) to previous categories
incomestatements <- incomestatements[, c('ticker', 'year', 'order', 'Net.Income.From.Continuing.And.Discontinued.Operation', 'Gross.Profit', 'Net.Income.Continuous.Operations', 'Pretax.Income', 'Net.Income', 'Net.Non.Operating.Interest.Income.Expense', 'Total.Revenue')]
names(incomestatements) <- c("ticker", "year", "order", "DO", "GPROF", "IAT", "IBT", "NI", "NINT", "TREV")
incomestatements
}
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