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Asked: 2026-05-23T13:27:43+00:00

I have two data.frame s in R , each indexed by date. One is

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I have two data.frames in R, each indexed by date. One is coarser than the other and I would like to compare the data only along the coarser timescale.

To be more concrete let’s say one data.frame has time points DF1[a,b,c,...,x,y,z] and the other only has DF2[f,p,t], where p=="July 19, 1917". I wish to compare DF1[f,p,t] to DF2[f,p,t].

This isn’t syntactic but I want to do for each $i { DF_combined <- df1[$i] . df2[$i] if exists(df1[$i]); }. In other words, make a new data.frame that only contains every shared observation day.

I hope the question is clear. I’ve been looking at other SO answers for a couple of hours and haven’t found one that covers what I’m trying to do yet. Thanks in advance.

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1 Answer

  1. Editorial Team

    Here’s the solution to my problem, from start to finish.

    Problem: Given records from my broker (not evenly spaced in time), put the time series of my net worth next to a time series of the S&P, for comparison in R.

    Answer:

    #get S&P data
require(quantmod)
getSymbols("^GSPC", from="2004-01-01", src="yahoo")
head(GSPC)

              GSPC.Open GSPC.High GSPC.Low GSPC.Close GSPC.Volume GSPC.Adjusted
2004-01-02   1111.92   1118.85  1105.08    1108.48  1153200000       1108.48
2004-01-05   1108.48   1122.22  1108.48    1122.22  1578200000       1122.22
2004-01-06   1122.22   1124.46  1118.44    1123.67  1494500000       1123.67

    Notice that there is no header over the dates. That’s because time-series data types embed the time-value as an ordering index. (class(GSPC) = [1] "xts" "zoo" where zoo is a data type totally ordered by an index, and xts is a time series data-type that tolerates more than the restrictive native ts data type tolerates.)

    #coerce the .csv from my broker into a time-series data type as well
MyNetWorth <- read.csv("/home/joey/Desktop/Historical_NAV.csv")
require(xts)
MyNetWorth <- as.xts( MyNetWorth,
                                   order.by= as.Date(MyNetWorth$TradeDate, format="%m/%d/%Y") )

    In the date format there is a big difference between %Y (’87) and %y (1987), as well as between %m – months and %M – minutes. My broker wrote 10/23/2009.

    So did I do it right?

    > class(MyNetWorth)
[1] "xts" "zoo"

    Yessss.

    Finally, @Joshua Ulrich’s advice does the kind of merge I want:

    comparison <- merge(GSPC$GSPC.Adjusted, MyNetWorth$NetAssets, join="right")

    The right join compares the dates only at the coarser scale (my data is always coarser than Yahoo’s).

    Last of all, to plot the results:

    plot( as.zoo(comparison) , screens=c(1,1), col=c("red", "#333333")  )

    Many thanks to all the people who wrote all this open source software — and especially to those who wrote vignettes!

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