similar to: Need help ploting time series

hi: Yesterday I post a message about hoy to plot a time series, but someone told me to post more information about the file so here it is: the file was read using read.table and the name is list. When I use str(list) it tells the following variables: YEAR int: 2003,2003,2003....2004 MONTH int:1,1,1,1,.... DAY:int 1,1,1,... STATE: factor with 51 levels. SALES: int (sales per day) The reason why

Hi Users, I have daily series of data from 1962 - 2000, with the data for February 29th in leap years excluded, leaving 365 daily values for each year. I wish to convert the daily series to monthly series. How can I do this using the zoo package or any other package? Thanks ZABLONE OWITI GRADUATE STUDENT Nanjing University of Information, Science and Technology College of International

I have time series observation on daily frequencies : library(zoo) SD=1 date1 = seq(as.Date("01/01/01", format = "%m/%d/%y"), as.Date("12/31/02", format = "%m/%d/%y"), by = 1) len1 = length(date1); data1 = zoo(matrix(rnorm(len1, mean=0, sd=SD*0.5), nrow = len1),  date1) plot(data1) Now I want to calculate 1. Quarterly statistics like mean, variance etc

Hi all: Im kind of new on R and I need help changing a table. The thing is, i read a file on R using the read.table command and the table looks like this: Item 3d Plot XY plot 001 1 0 001 0 1 001 0 1 002 1 0 002 1 0 002 0 1 ...

Hi all, Thanks a lot for anyone's help in advance. I am trying to find a way to compute the day-to-day return (log return) from a n x r matrix containing, n different stocks and price quotes over r days. The time series of prices are already split by using unstack function. For the result, I would like to see a n x (r-1) matrix, where by each entry is the day-over-day return of

Hello, I have a series of intraday (high-frequency) price data in the form of POSIX timestamp followed by the value. I sucesfuly loaded that into "its" package object. I would like to create from it a regularly spaced time series of prices (for example 1min, 5min, etc apart) so i could calcualte returns. There is an interpolation function locf() that for timestamp with value NA uses last

I built some reasonably successful tools in a graphical database for reconstructing the developmental turning points for feedback loop driven natural processes. I'm trying to move it to R and am having difficulty with the very basics, i.e. a) defining time series using time as a natural number rather than a place in a table. I was also hoping b) someone might have built some of the

Dear R-Users, Have a question about reading in some data and manipulating dates. I have a data set in excel which looks like this: Date PEG ETN HSP PTC 13/10/2004 41.92 64.75 29.86 9.27 14/10/2004 41.93 61.79 29.98 9.14 15/10/2004 41.69 62.7 30.09 9.04 18/10/2004

Hello, I have this kind of dataframe and have to plot it. data <- data.frame(sw= c(1,2,3,4,5,6,7,8,9,10,11,12,15), zehn = c(33.44,20.67,18.20,18.19,17.89,19.65,20.05,19.87,20.55,22.53,NA,NA,NA), zwanzig = c(61.42,NA,26.60,23.28,NA,24.90,24.47,24.53,26.41,28.26,NA,29.80,35.49), fuenfzig =

I have a vector that contains month and year in the format YYYYMM (e.g.“200701”, “200702”) I wish to do to things: 1. I need to convert to a date that is the last calendar day of each month. 2. I need to convert this to a date that is the last U.S. stock-exchange trading day of each month. Any advice is appreciated, mymonths <- c(200701, 200702)

Dear list members I have a rather large vector (part of a data frame) giving the time (date + time, POSIXct) of observations. The times are irregular (with both small and large jumps) but increasing, and there are several millions of them. I now wish to reduce my data set, so that I only have observations which are at least (for example) 60 seconds apart. Basically, I need (all) the indices

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

Hi, R experts. I am a new user of R and trying to learn this program. I have a problem. Here is the code. d<-as.Date(c("2000/01/03","2000/01/05","2000/01/19","2000/01/28")) r<-rnorm(4) da<-data.frame(d,r) a<-as.Date("01/01/2000","%d/%m/%Y") b<-as.Date("30/01/2000","%d/%m/%Y") ab<-seq(a,b,by=1)

Hi R users, I have a time series variable that is only available at a monthly level for 1 years that I need to decompose to a weekly time series level - can anyone recommend a R function that I can use to decompose this series? eg. if month1 = 1200 I would to decompose so that the sum of the weeks for month1 equals 1200, etc.. Many thanks in advance for any help. -- View this message in

Hello, I'm very new to R, and so my question is simple. I have data record with 80 years of daily temperatures in one long string. The dates are also recorded, in YYMMDD format. I'd like to learn an elegant simple way to pull out the annual averages. (Obviously, every 4th year has 366 days.) I know I can set up a formal loop to create annual records and then average. But R

dear r-helpers i've got a table that in extracts looks like this: V1 V2 V3 V4 V5 1 01/01/1975 00:00:00 125.837 3.691 296.618 2 01/01/1975 01:00:00 124.799 3.679 281.307 3 01/01/1975 02:00:00 111.607 3.536 281.307 4 02/24/1976 11:00:00 21.602 2.555 93.893 5 02/24/1976 12:00:00 27.804 2.623 93.893 6 02/24/1976 13:00:00 26.105 2.604 114.716 7 10/18/1977

All, I have been just recently working with zoo objects for trading systems. Can someone please help with these basic questions? Given a daily time series downloaded using get.hist.quote() from the tseries package, ie...... startDate= as.Date("2000-01-01") endDate= as.Date("2011-01-29") frequency= 'd' s= get.hist.quote('IWF', start= startDate, end=

Hello all, I'm using R to visualize and explore the data produced by a software system. The software generates logs for many types of events. The software runs for days on end, and can possibly generate multiple events per second. What is the appropriate time format for year, month, day, hour, minute, second, millisecond? that R can properly interpret (using zoo? or ITS?) I'll have

Hi, I'm trying to draw a 2D plot using multiple tints of red. The (simplified) setup is the following: || year | x | y || My idea is that each year is plotted with a different tint of red. Older year (lightest) -> Later year (darkest). I've managed to plot this with different scales of grays simply by doing: palette(gray(length(years):0/length(years))) before the plot and for each

Thanks in advance for all help , I just started using R and have already done the following. 1. Read through multiple files to get input data 2. plot a vector (X say) 3. end Now i want to plot the vector X for different files on the same plot, and I don't know how to do that. One option I considered was to have a global data frame that holds X for each file. and then plot after iterating