similar to: Generating variable from 2 others in dataframe

Hi everyone, Please forgive me if my question is simple and my code terrible, I'm new to R. I am not looking for a ready-made answer, but I would really appreciate it if someone could share conceptual hints for programming, or point me toward an R function/package that could speed up my processing time. Thanks a lot for your help! ## My dataframe includes the variables 'year',

Hi, Having a dataframe 'l1' (dput output is below): >dim(l1) 1274 2 >l1[1:12,] Var1 Freq 1 1988-01-13 1 2 1988-01-16 1 3 1988-01-20 3 4 1988-01-25 2 5 1988-01-30 1 6 1988-02-01 5 7 1988-02-08 4 8 1988-02-14 1 9 1988-02-16 1 10 1988-02-18 4 11 1988-02-24 2 12 1988-03-04 1 I want to extract the times

I would lilke to shape upload ftp bandwidth in a dual ISP setup [shorewall show connections] tcp 6 431215 ESTABLISHED src=192.168.2.89 dst=83.xxx.xxx.23 sport=1487 dport=21 src=83.xxx.xxx.23 dst=10.0.11.2 sport=21 dport=1487 [ASSURED] use=2 mark=1 [tcdevices] #INTERFACE IN-BANDWITH OUT-BANDWIDTH $EIF 970kbit 245kbit $LIF 970kbit 245kbit

Has any one used this? U(x[^arg[^...]]): x - Name of the subroutine to execute via Gosub arg - Arguments for the Gosub routine Execute via Gosub the routine <x> for the *called* channel before connecting to the calling channel. Arguments can be specified to the Gosub using '^' as a delimiter. The Gosub routine can set the variable ${GO

Hi, I have the next procedure: t1<-data.frame(table(substr(names(subset(lasker[[1]], lasker[[1]] >= 4)), 1, 7))) t1[1:5,] Var1 Freq 1 1988-02 3 2 1988-03 1 3 1988-04 1 4 1988-05 2 5 1988-06 3 How to make a new list?, dataframe? having 189 elements in the 'lasker' list: > str(lasker[[1]]) 'table' int [, 1:1274] 1 1 3 2 1 5 4 1 1 4 ... -

Hi, I have a list of 20 elements, each of them of variable length and with a structure like this: lasker[[1]][1:10,] Var1 Freq 1 1988-02 3 2 1988-03 1 3 1988-04 1 4 1988-05 2 5 1988-06 3 6 1988-07 1 7 1988-08 1 8 1988-09 1 9 1989-03 1 10 1989-04 1 How do I can insert in this list: 1988-01 0 1988-10 0 1988-11 0 1988-12 0 1989-01 0

Hi, I'm trying to create a function, jim(p) which varies depending on whether the value of p is odd or even. I was trying to use th eIf function, but i cant work out a formula to work out if p is odd or even. Thanks, Dave __________________________________________________ Yahoo! Plus For a better Internet experience http://www.yahoo.co.uk/btoffer

I have the following list of observations of calendar time: [1] 03-Nov-1997 09-Oct-1991 27-Aug-1992 01-Jul-1994 19-Jan-1990 12-Nov-1993 [7] 08-Oct-1993 10-Nov-1982 08-Dec-1986 23-Dec-1987 02-Aug-1995 20-Oct-1998 [13] 29-Apr-1991 16-Mar-1994 20-May-1991 28-Dec-1987 14-Jul-1999 27-Nov-1998 [19] 09-Sep-1999 26-Aug-1999 20-Jun-1997 05-May-1995 26-Mar-1998 15-Aug-1994 [25] 24-Jun-1996 02-Oct-1996

Hello all! I have a problem with ggplot2 library. I want to do an heat map and the y variables are the year months. If I use the following code, he y values are in alphabetical order, but I want it in month order. The code is: library(reshape) library(ggplot2) library(scales) p <- ggplot(data.m, aes(variable, Month)) + geom_tile(aes(fill = value),

Dear list, This is a bit of an off-topic question, but I'm hoping to get some advice from more experienced people. I've used the website "Web of Science" to manually collect publication counts responding to several keywords as a function of date, since the 1960s. http://apps.isiknowledge.com/RAMore.do?product=UA&search_mode=&SID=P1g9lFJp9 at

Hello everyone, I have a data generated in a way similar to the following library(chron);library(zoo) date<- seq(as.Date("1990-01-01"),, as.Date("2000-12-31"), by = 1) obs<- zoo(rnorm(length(date), mean = 10, sd = 2.5), order.by = date) monthly<- function(date) as.Date(as.yearmon(Date)) result<- data.frame ( Date = obs = aggregate(obs, monthly, sum)) Now, I want

I have weekly time series data with year, month, day, and price variables. The input data set for the weekly series takes the following form: Year month day price 1990 8 20 119.1 1990 8 27 124.5 1990 9 3 124.2 1990 9 10 125.2 1990 9 17 126.6 1990 9 24 127.2 1990 10 1 132.1 1990 10 8 133.3 1990 10 15 133.9 1990 10 22 134.5 1990 10 29 133.9 .. ... ... ... ... ... .... .... 2008 3 3 313.7 2008

I've a matrix like this: 1985 1.38 1.27 1.84 2.10 0.59 3.47 1986 1.05 1.13 1.21 1.54 0.21 2.14 1987 1.33 1.21 1.77 1.44 0.27 2.85 1988 1.86 1.06 2.33 2.14 0.55 1.40 1989 2.10 0.65 2.74 2.43 1.19 1.45 1990 1.55 0.00 1.59 1.94 0.99 2.14 1991 0.92

R-help, I'm trying to plot the following: year lgd 1 1986 136.97479 2 1987 69.10377 3 1988 67.66744 4 1989 71.60316 5 1990 62.06897 6 1992 6.25000 7 1993 27.72021 8 1995 23.83648 9 1996 10.29412 10 1997 95.67487 11 1998 82.09367 12 1999 56.60401 13 2000 29.80864 14 2001 23.77535 15 2002 48.30378 16 2003 83.47571 17 2004 74.58711 There are 2 missing years

cumsum() seems to be what you need. This can probably be done more elegantly, but ... out <- aggregate(Q ~ wyr, data = Daily, which.max) tbl <- table(Daily$wyr) out$Q <- out$Q + cumsum(c(0,tbl[-length(tbl)])) out ## yields wyr Q 1 1990 4 2 1991 6 3 1992 9 4 1993 15 5 1994 18 I leave the matter of Julian dates to you or others. Cheers, Bert Bert Gunter "The trouble

I require some assistance with JGR, but following the mailing list link from http://jgr.markushelbig.org/FAQ.html leads me to http://mailman.rz.uni-augsburg.de/mailman/listinfo/stats-rosuda-devel which responds with No such list stats-rosuda-devel I was previously subscribed to this mailing list and want to resubscribe, but where has it gone? Many thanks, Oliver Mannion Programmer COMPASS -

Using the dataset below, I got close to what I'm after, but not quite all the way there. Any suggestions appreciated: Daily <- read.table(textConnection(" Date wyr Q 1911-04-01 1990 4.530695 1911-04-02 1990 4.700596 1911-04-03 1990 4.898814 1911-04-04 1990 5.097032 1911-04-05 1991 5.295250 1911-04-06 1991 6.569508 1911-04-07 1991 5.861587 1911-04-08 1991 5.153666

I have a data set with observations on 549 cities spanning an 18 year period. However, some of cities did not report in one or more of the 18 years. I would like to implement the procedure suggested by Wooldridge section 17.1.3 in his "Econometric analysis of cross section and panel data" to correct for attrition. For example the table below indicates that the 3rd and the 7th cities in

Hi everyone I have banking data set in long format with 4 columns.One of these columns is bank name which consist of 49 banks and I want the data for only 40 banks out of these 49 so can anyone help me on how to get this 40 banks data My data looks like Year Name totalliabilties assets 1990 a 90 10 1991 a 89 48 1992 a 87

Hi, I've been using R for a few weeks now, but consider myself still a newbie, especially in what concerns the basics of data handling in R. My situation is this: I read in data from a database using RODBC, and then use "table" to produce a table of "counts per years", table which I give to "plot". All is well, as long as there are no gaps in the years