[R-SIG-Finance] Calculating Proportions & Appending New Column?

[Ilya Kipnis]

Jason,

This isn't a finance problem. This is the wrong list to post on. Does your
class have a discussion forum?

-Ilya

On Mon, Sep 22, 2014 at 8:36 PM, Jason Eyerly <teamtraders3564 at gmail.com>
wrote:

> Hello Folks,
>         I’m doing a study for a coursera Data Science class, and I am
> trying to determine if American’s financial satisfaction has any
> correlation to the percentage return of the S&P500 in the year prior. I
> have to calculate the proportion of "Satisfied" and "More Or Less" compared
> to the total number of observations for year "X", starting at 1989. After
> computing that for each year, I need to place them in a column at the end
> of the dataset similar to what we see with "PercentChange”. However, the
> years only go from 1989 - 2012. Calculating it for each observation seems
> tedious and inefficient. The end result is a chart where the X-Axis is each
> different percent change, and the Y-Axis is the proportion that are
> satisfied. What's the most efficient way to do this? Sorry for posting all
> of my code, but I don’t know what’s important and what isn’t. I realize I
> probably didn’t code everything in the most efficient way possible.
>
> require(Quandl)
> require(lubridate)
> require(zoo)
> require(xts)
>
> myGSS <- load(url("http://bit.ly/dasi_gss_data"))
>
> year <- gss$year
> finSat <- gss$satfin
>
> relativeTable <- data.frame(year, finSat)
> relativeTable <- subset(relativeTable, year > "1988" & !is.na(finSat))
>
>
> spReturns <- Quandl("SANDP/ANNRETS", trim_start="1970-01-11",
>                     trim_end="2012-12-31", authcode="nwy3a_Gmd7TSS9fVirxT",
>                     collapse="annual")
>
> percentChange <- spReturns$"Total Return Change"
>
> spReturns$"Year Ending" <- format((spReturns$"Year Ending"), "%Y")
> spReturns$"Year Ending" <- as.numeric(spReturns$"Year Ending")
> spReturns$"Year Ending" <- spReturns[,1] + 1 #the following year
>
> combined <- merge(relativeTable, spReturns, by.x = "year", by.y = "Year
> Ending")
> names(combined)[6] <- "percentChange"
>
> finalResults <- data.frame(combined$year, combined$finSat,
> combined$percentChange)
> names(finalResults)[1] <- "Year"
> names(finalResults)[2] <- "FinancialSatisfaction"
> names(finalResults)[3] <- "PercentChange"
>
> finalResults$PercentChange <- finalResults$PercentChange * 100
>
> Regards,
>     Jason E.
>         [[alternative HTML version deleted]]
>
>
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