similar to: How to import time-series data

Dear all, I have a time serie dataset such as the following with data acquired every 15 minutes: Date Heure Profondeur Temp?rature Salinit? Turbidit? Chloration 1 2012-07-06 08:47:22 -0.144 22.469 0.011 0.000 0 2 2012-07-06 09:02:21 -0.147 22.476 0.011 0.000 0 3 2012-07-06 09:17:21 -0.139 22.498 0.011 19.323 0 4 2012-07-06

Is there a easy way to create the time index for a zoo/xts object for every 100 milliseconds. eg. time Index would be: 10:00:00:100 10:00:00:200 10:00:00:300 10:00:00:400 I am looking to build an empty zoo/xts object with time index from 10am to 3pm, index jumps by 100ms each row. Thanks, Chris -- View this message in context:

Hello, I have a population of 2000+ zoo time series (but my environment also contains objects that are not zoo time series). I'm trying to calculate the latest 90 days Z-Score of all zoo time series, using the following code: LZS<-function(ser) { temp<-window(ser,start=Sys.Date()-90) last((temp-mean(temp))/sd(temp)) } sapply(ls(), LZS ) The LZS function works on individual zoo time

Using Achim's d this also works to generate z where FUN is a function used to transform the index column and format is also passed to FUN. z <- read.zoo(d, index = "time", FUN = as.yearqtr, format = "Q%q %Y") On Sun, Jan 28, 2018 at 4:53 PM, Achim Zeileis <Achim.Zeileis at uibk.ac.at> wrote: > On Sun, 28 Jan 2018, phil at philipsmith.ca wrote: > >> I

I have a data set with quarterly time series for several variables. The time index is recorded in column 1 of the dataframe as a character vector "Q1 1961", "Q2 1961","Q3 1961", "Q4 1961", "Q1 1962", etc. I want to produce line plots with ggplot2, but it seems I need to convert the time index from character to date class. Is that right? If so, how

Hi all, Issue: I merged two zoo objects (a regular and an irregular). After the merge I used the function 'na.approx' to have also values in the resolution of the regular time series. Problem: After approximation some rows at the beginning or at the end of the zoo objects disappear due to the 'na.approx' algorithm. Now I just want to have all the rows of the regular time series

On Sun, 28 Jan 2018, phil at philipsmith.ca wrote: > I have a data set with quarterly time series for several variables. The > time index is recorded in column 1 of the dataframe as a character > vector "Q1 1961", "Q2 1961","Q3 1961", "Q4 1961", "Q1 1962", etc. I want > to produce line plots with ggplot2, but it seems I need to

#Is there a way to break the below zoo object into non-NA data frames algorithmically #this is a small example of a much larger problem. #It is really no even necessary to have the continuous chunks #end up as zoo objects but it is important to have them end #up with the index column. #thanks for all of your help in advance, and #if you need anything else please let me know library(zoo) ind.

I have a matrix of zoo series. each series is in a column. x <- as.yearmon(2000 + seq(0, 23)/12) # 24 months of data, lets make 20 sets of random data testData <- matrix(rnorm(480),ncol=20) # make a zoo object and columns will hold the 20 series TestZoo <- zoo(testData,order.by=x) # now run lm for just one series. m <- lm(TestZoo[,1]~time(TestZoo))$coeff[2] m time(TestZoo)

Hi Using the ggplot2 package, I would like to obtain a plot that contains two time series that have data points on different dates. For instance, one data frame looks like: date1, value1 2010-01-05, 2921.74 2010-01-08, 2703.89 2010-01-14, 3594.21 2010-01-20, 3659.22 The other data frame looks like date2, value2 2010-01-01, 285.85 2010-01-02, 229.20 2010-01-05, 333.91 2010-01-06, 338.27

Hi, I'm trying to make a ts object that has both NA values and a frequency other than 1 (so I can use stl). I've tried all permutations I can think of, but cannot get the desired (expected?) results. The values live in x and the corresponding semi-regular time stamps are in t: > library('zoo') > z = zoo(x, order.by=t, frequency=24) > zzr = as.zooreg(z, start=0) > zr

Hi, I am trying to get the following two timeseries (these are small subsets of the whole thing) into R so I can merge them using zoo. Timeseries 1=[ Date Count 9/28/2003 1505 10/5/2003 1535

I have 2 zoo objects - 1) Interest rate spread between 10-YR-US-Treasury and 2-YR-US-Treasury (object name = sprd) 2) S&P 500 index (object name = spy) > str(spy) ?zoo? series from 1976-06-01 to 2011-03-31 Data: num [1:8791] 99.8 100.2 100.1 99.2 98.6 ... Index: Class 'Date' num [1:8791] 2343 2344 2345 2346 2349 ... > str(sprd) ?zoo? series from 1976-06-01 to 2011-03-31

Hi R community! I'd like to create a temporal series with ts command for the interval 1st January 2002 - 31 December 2008. I have daily values, so this is a 2557 days temporal series. I'm using this command : ts(observations, start=2002, end=2009, freq=365) However, I don't get the correct temporal series since both frequency (365 OR 366 for leap years) and deltat (1/365 OR

Hi there, I have a spreadsheet in excel which consists of first column of dates and then subsequent columns that refer to prices of different securities on those dates. (the first row contains each series name) I saved the excel file as type csv and then imported to excel using prices=read.csv(file="C:/Documents and Settings/Hugh/My Documents/PhD/Option prices.csv",header = TRUE, sep

Hello, This is a standard example in which I read the time series data from a csv file and create a zoo object: x0 <- read.csv(file="CPI.csv", header=TRUE) time_0<-as.yearmon("1981-01")+(0:371)/12 x0zoo<-zoo(x0, time_0) The data look like this: TIME CPI CPI_food CPI_Clothes CPI_House CPI_Rent 198101 62.1 55.34 103.45 65.24 61.43 198102 63.16 56.95

Hi, I have data with multiple sub-second entries: 2011/03/15 09:32:15.035619,-0.403103,1.09664,48.6,126.92,117.32 2011/03/15 09:32:15.069331,-0.39851,1.09874,48.6,126.92,117.32 2011/03/15 09:32:15.289135,-0.402463,1.10084,48.59,126.92,117.32 2011/03/15 09:32:15.296110,-0.450244,1.10063,48.59,126.92,117.32 2011/03/15 09:32:15.451358,-0.438813,1.10273,48.59,126.93,117.32 2011/03/15

Hi, I'd like to make a time series at an annual frequency. > a<-xts(x=c(2,4,5), order.by=c("1991","1992","1993")) Error in xts(x = c(2, 4, 5), order.by = c("1991", "1992", "1993")) : order.by requires an appropriate time-based object > a<-xts(x=c(2,4,5), order.by=1991:1993) Error in xts(x = c(2, 4, 5), order.by =

Newbie question - mechanical engineer trying to learn R I've had success with plotting time series data and even made a heat map using R Graphs Cookbook by Mittal. I have a new problem - I need to align a number of time series data "columns" to the desired regular exact time stamp vector. The target time vector could be finer or more course than the typical time stamp spacing found.

Not sure if the question is appropos, but I have multiple csv's which are read into an xts object, corresponding to telemetry data (accelerometer, magnetometer/compass, and gyroscope). For examination, it would be ?ber useful if plot.zoo (or something similar) allowed me to zoom in and out of a subset of the time axes. -- Sent from my mobile device Envoyait de mon portable