similar to: Plotting quarterly 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

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

Hi Guys, I'm using zoo package now. I found lag is not doing what I assumed. > x <- zoo(11:21) > z <- zoo(1:10, yearqtr(seq(1959.25, 1961.5, by = 0.25)), frequency = 4) > x 1 2 3 4 5 6 7 8 9 10 11 11 12 13 14 15 16 17 18 19 20 21 > lag(x) 1 2 3 4 5 6 7 8 9 10 12 13 14 15 16 17 18 19 20 21 > z 1959 Q2 1959 Q3 1959 Q4 1960 Q1 1960 Q2 1960 Q3 1960 Q4

Hi all, I'm trying to make an integer-backed quarter (as in fraction of year) class, but I can't quite it to work. I want integer-backed so I don't have to worry about floating-point effects when doing math, and so that I can use it as in data.table. First of all, is there a good reference for this anywhere? All of the S4 tutorials that I've found have been too high-level, and

hello, Does anybody know how to aggregate a lag series ? when I try to use aggregate I get the following message > try<-ts(1:100,start=c(1985,1),freq=12) > aggregate(try,4,mean,na.rm=T) Qtr1 Qtr2 Qtr3 Qtr4 1985 2 5 8 11 1986 14 17 20 23 1987 26 29 32 35 1988 38 41 44 47 1989 50 53 56 59 1990 62 65 68 71 1991 74 77 80 83 1992

I have financial data on a a set of firms, with a quarterly period (fundamental data). The data spans 10 years, and four quarters per year. The present file (.csv) reads the Date columns as "200706" for the second quarter of 2007; "199809" for the third quarter of 1997. Is there a way I can convert it to something like "2007 Q2", "1998 Q3"? I am aware of

sample report data that i want to forecast quarter quarter_index Revenue 2007 Q1 1 $3,856,799 2007 Q2 2 $4,243,328 2007 Q3 3 $4,930,369 2007 Q4 4 $5,443,579 2008 Q1 5 $5,164,830 2008 Q2 6 $5,104,413 2008 Q3 7

sample report data that i want to forecast quarter quarter_index Revenue 2007 Q1 1 $3,856,799 2007 Q2 2 $4,243,328 2007 Q3 3 $4,930,369 2007 Q4 4 $5,443,579 2008 Q1 5 $5,164,830 2008 Q2 6 $5,104,413 2008 Q3 7

Example: Will ts objects be obsolete or modified? > a [,1] 1983 Q1 2.747365190 1983 Q2 2.791594762 1983 Q3 -0.009953715 1983 Q4 -0.015059485 1984 Q1 -1.190061246 1984 Q2 -0.553031799 1984 Q3 0.686874720 1984 Q4 0.953911035> lag(a,4) [,1] 1983 Q1 NA 1983 Q2 NA 1983 Q3 NA 1983 Q4 NA 1984 Q1 2.747365190 1984 Q2

I have a data.frame named "df". The dput of df is at the bottom of this e-mail. What I'd like to do is replace the "n/a " values with NA. On Mac OSX, it works to do this: df[df == "n/a"] <- NA However, it does not work on Ubuntu. See below. Thanks in advance, Garrett > x <- df[27, 4] # complete data.frame dput is below > dput(x) "n/a?"

I have the initial matrice: > *data.frame(Subject=rep(100:101, each=4), Quarter=rep(paste("Q",1:4, sep=""),2), Boolean = rep(c("Y","N"),4))* Subject Quarter Boolean 1 100 Q1 Y 2 100 Q2 N 3 100 Q3 Y 4 100 Q4 N 5 101 Q1 Y 6 101 Q2 N 7 101 Q3 Y 8 101

Hello, I have a question on how to tabulate the time series data. I use RStudio, but if can be done in any other R editor, it should work in RStudio as well. > a1<-11:22 > a1ts<-ts(a1, frequency=4, start=c(1978,1)) > a1ts Qtr1 Qtr2 Qtr3 Qtr4 1978 11 12 13 14 1979 15 16 17 18 1980 19 20 21 22 If I click the variable "a1ts" on the

Hi, I have a question about how to obtain the union of several data frame rows. I'm trying to create a common key for several tests composed of different items. Here is a small scale version of the problem. These are keys for 4 different tests, not all mutually exclusive: id q1 q2 q3 q4 q5 q6 1 A C 2 B D 3 A D B 4 C D B D I would like

I have the initial matrice: > *data.frame(Subject=rep(100:101, each=4), Quarter=rep(paste("Q",1:4, sep=""),2), Boolean = rep(c("Y","N"),4))* Subject Quarter Boolean 1 100 Q1 Y 2 100 Q2 N 3 100 Q3 Y 4 100 Q4 N 5 101 Q1 Y 6 101 Q2 N 7 101 Q3 Y 8 101

# Dear List, # I want to characterize a time series according to its Quarter components. # My data ("a.ts": http://docs.google.com/View?id=dfvvwzr2_478cr9k4cdb)? look like: #???????????????? Qtr1????????? Qtr2????????? Qtr3????????? Qtr4 #?? 1948 -0.0714961837? 0.0101747827? 0.0654816569 -0.0227830729 #?? 1949 -0.1175517556? 0.1151378692? 0.1015777858 -0.1971535900 #?? 1950?

Hi R users, I have following data frame df<-data.frame(q1=c(0,0,33.33,"check"),q2=c(0,33.33,"check",9.156), q3=c("check","check",25,100),q4=c(7.123,35,100,"check")) and i would like to replace every element that is less then 10 with . (dot) in order to obtain this: q1 q2 q3 q4 1 . . check . 2 . 33.33 check 35

Dear R-helpers, I know of two ways to reading data within an R program, using textConnection and stdin (demo program below). I've Googled about and looked in several books for comparisons of the two approaches but haven't found anything. Are there any particular advantages or disadvantages to these two approaches? If you were teaching R beginners, which would you present? Thanks, Bob

----- Original Message ----- From: "Silvano" <silvano at uel.br> To: <r-help at r-project.org> Sent: Thursday, June 30, 2011 9:07 AM Subject: Tables and merge > Hi, > > I have 21 files which is common variable CODE. > Each file refers to a question. > > I would like to join the 21 files into one, to construct > tables for each question by CODE. >

Hello, I have a table (1) of the form q1 q3 q4 q8 q9 A 5 2 0 1 3 B 2 0 2 4 4 I have another table (2): q1 q2 q3 q4 q5 q6 q7 q8 q9 C 10 7 4 2 6 9 3 1 2 I would like to divide the numbers in table (1) by the number of the appropriate column in table (2): q1 q3 q4 q8 q9 A 5/10 2/4 0/2 1/1 3/2 B 2/10 0/4 2/2 4/1 4/2

Hi, I have an n x m matrix of numerical observations. ie. stock prices I wish to convert the matrix of observations to a matrix of simple returns (by taking the differences between (column) observations.) Can any good soul suggest a function for this? -- View this message in context: http://r.789695.n4.nabble.com/R-beginner-matrix-algebra-tp4653335.html Sent from the R help mailing list