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I have a dataframe as follows: Date time value 20110620 11:18:00 7 20110620 11:39:00 9 20110621 11:41:00 8 20110621 11:40:00 6 20110622 14:05:00 8 20110622 14:06:00 6 For every date, I want to extract the row that has the greatest time. Therefore, ending up like: 20110620 11:39:00 9 20110621 11:41:00 8 20110622 14:07:00 6 I am using for loops (for every date, find largest time value) to do

Suppose I have: Book Value A 10 B 11 C 9 D 8 A 12 C 4 D 5 B 7 I want to summarize above not by Book but by groupings of Books as in (below) I have a list ... basic_map <- list(c("A",B"),c("C,D")) Big_names <- c("A1", "A2") Names(basic_map) <- big_names So I want to get : A1 40 A2 26 How do I use tapply AND the list to get my

Hi all: I have a directory of files as in -------------> bunchafiles <- list.files(path="/data/2.3/2006", pattern="returns", full.names=T,recursive=T) .... Each file is a bunch of returns for a particular date (unique). There are like 252 files or so. With a custom function myread (below), I define a vector ----- res <-

Hi, I am doing the following: 1. I have a list of files.. Files1=list.files("some directory",pattern="some pattern") 2. I define a list as res=vector("list", length(files1)) 3. I read all the files into this list: res=lapply(files1, read.csv) I now want to rowbind all the items in the list into one big mass (all files have same number of columns). I tried

R-experts, I have a bunch of files (by date) that I can read into dataframes as below. df$today: identifier rtgmdy rtgmdy_dt rtgmdy_watch rtgmdy_nowatch rtgmdy_watch_dt rtgsp rtgsp_dt 310000031 Aa3 20050701 Aa3 NA AA- 20050510 310000086 B1 20070920 B1 NA B+ 20070828 310000106 Baa2 20040326 Baa2 NA BBB 20051003 310000170 Baa3 20070601 Baa3 NA BBB+ 20051024 310000225 Ba2 20070601 Ba2 NA