R Condition Function/Loop to check value in Data Frame - r

Question

I am trying to write code that checks to see if the 1 value in a df is greater than another value in a different row/column in the same df.
I have the following as a sample:
Date GSPC.Open GSPC.High GSPC.Low GSPC.Close
2014-02-28 2014-02-28 1855.12 1867.92 1847.67 1859.45
2014-02-27 2014-02-27 1844.90 1854.53 1841.13 1854.29
2014-02-26 2014-02-26 1845.79 1852.65 1840.66 1845.16
2014-02-25 2014-02-25 1847.66 1852.91 1840.19 1845.12
I want to create a loop or function that checks to see if GSPC.Open is greater than or equal to the previous day's GSPC.Close. I would imagine the code would look like
if (df$GSPC.Open >= df$GSPC.Close[1]) {
df$GSPC.AboveOpen = 1
}
but I keep an length > 1 error.
I would like the function to create an column df$GSPC.AboveOpen filled w/ discrete values if the current day's open is greater than or equal to the previous day's close.
How do I write this code?
Thanks!

Answer 1

I would not advise to use a loop here. You are using a time series - therefore, use appropriate time series methods (such as lag).
This code compares the current day's open with previous day's close and gives 1 if the open is higher (or equal) and 0 otherwise.
library(quantmod)
getSymbols('^GSPC',src='yahoo',from='1990-01-01')
GSPC$AboveOpen<-(GSPC[,"GSPC.Open"]>=lag(GSPC[,"GSPC.Close"],1))
Just in case you also want to deal with single stock data: Keep in mind that .Close and .Open (at least from Yahoo) are not split and dividend adjusted. .Adjusted is the adjusted close.

Answer 2

Try this:
df$GreaterThanPreviousClose <- NA
for (i in 2:nrow(df)){
df[i,6] <- df[i,2] >= df[i-1,5]
}
Maybe this will speed it up
compare <- function(i){
Larger <- df[i,2] >= df[i-1,5]
return(Larger)
}
df$GreaterThanPreviousClose <- sapply(1:nrow(df),compare)