File:FinancePctOfUSprofits.png

Summary[edit]

How to create this image using R[edit]

• NOTE: Wikimedia formatting conflicts with R script
• in that the R "#" comment character is ignored in the display
• USE 'EDIT' to get the R script with comment characters

1. (not visible in standard display)
   1. 3. Table 6.16 of the National Income and Product Accounts,
      4. US Bureau of Economic Analysis.
      6. How to download the US Bureau of Economic Analysis
      7. Table 6.16 and create a plot of finance industry
      8. profits as a percent of US domestic corporate profits
      9. using R (www.r-project.org)
      11. Procedure tested 2012.01.30

1. 2. 1. Go to the web interface for the
   3. National Income and Product Accounts (NIPA)
   4. of the US Bureau of Economic Analysis
   5. (http://bea.gov/national/nipaweb).
   6. Select "List of All NIPA tables".
   7. From there, select 6.16A, 6.16B, 6.16C, and 6.16D
   8. in turn. With each one, select "Annual series",
   9. "Get All Years", and Update.
   10. Then at the bottom, click "Download All Years (CSV)".
   11. This should produce local copies of files with names like
   12. "NIPA Table (1).csv", ..., "NIPA Table (4).csv"
   14. NOTE: Check to make sure you get annual data,
   15. because a slight error in following the above process
   16. can produce quarterly numbers.
   18. Move or copy these files into a working directory
   19. for your R session and rename them to the following:

(table6.16.csv <- paste('NIPA6.16', LETTERS[1:4], '.csv', sep=))

1. 2. 2. Read the contents of the table

table6.16lines <- lapply(table6.16.csv, readLines)

1. Confirm that the first line gives the table numbers:
2. 6.16 A, B, C, D

sapply(table6.16lines, '[', 1)

1. 2. 3. Get years, Domestic Industries, and Financial:
   3. rows 5, 7 and 8 in each table.
2. Confirm that line 5 starts "Line"

(table6.16data <- lapply(table6.16lines, '[', c(5, 7, 8)))

1. NOTE: If line 5 does NOT start "Line", you have the wrong table(s).

get6.16data <- function(x){

   x. <- gsub('\"', , x)
   ys <- strsplit(x., split=',')
   Names <- sapply(ys[-1], '[', 2)
   Names[2] <- gsub(' ', , Names[2])
   yrs <- lapply(ys, '[', -(1:2))
   dat <- lapply(yrs, as.numeric)
   X <- do.call(rbind, dat)
   dimnames(X) <- list(c('year', Names), NULL)
   X

}

1. confirm that it works with the first one

get6.16data(table6.16data1)

1. Now try all 4

(table6.16Data <- lapply(table6.16data, get6.16data))

1. 2. 4. Put them together

str(table6.16AB <- do.call(cbind, table6.16Data[1:2]))

1. Identify duplicate years, keep the last

keepAB <- (table6.16AB[1,]<table6.16Data3[1,1])

str(table6.16ABC <- cbind(table6.16AB[, keepAB], table6.16Data3))

keepABC <- (table6.16ABC[1,]<table6.16Data4[1,1]) str(table6.16ABCD <- cbind(table6.16ABC[, keepABC], table6.16Data4))

1. 2. 5. transpose, convert to data.frame

str(table6.16 <- as.data.frame(t(table6.16ABCD))) names(table6.16)[2] <- 'DomesticIndustries'

1. check years increment one at a time

table(diff(table6.16[,1]))

1. 2. 6. Add percent
2. table6.16$financePct <- with(table6.16, Financial/DomesticIndustries)

png('finance.png', width=480, height=320, bg="transparent") plot(100*Financial/DomesticIndustries ~ year, table6.16, type='l',

    ylim=c(0, 40), xlab=, ylab=,
    frame.plot=FALSE, col='blue', lwd=3, axes=FALSE)

axis(1, seq(1930, 2010, 20), c(1930, NA, 1970, NA, 2010), cex.axis=1.5) axis(2, seq(0, 40, 10), c(0, NA, 20, NA, 40), las=1, cex.axis=1.5)

1. title('Finance as a percent of US Domestic Corporate Profits')

dev.off()

svg('finance.svg', width=4, height=8/3, bg="transparent") plot(100*Financial/DomesticIndustries ~ year, table6.16, type='l',

    ylim=c(0, 40), xlab=, ylab=,
    frame.plot=FALSE, col='blue', lwd=3, axes=FALSE)

axis(1, seq(1930, 2010, 20), c(1930, NA, 1970, NA, 2010), cex.axis=2) axis(2, seq(0, 40, 10), c(0, NA, 20, NA, 40), las=1, cex.axis=2)

1. title('Finance as a percent of US Domestic Corporate Profits')

dev.off()

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