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I tried a date by date forecast of a time series and it seems to be too wild. How can I aggregate the date into weeks or months as required? Thanks. The input looks like ID datadate("YYYY-MM-DD") value_for_day -- ----- ------- -- ------ -------- and I want to be able to change it to ID dataweek value_for_week or

(1) > a = c("a","b") > mode(a) [1] "character" > b = c(1,2) > mode(b) [1] "numeric" > c = data.frame(a,b) > mode(c$a) [1] "numeric" (2) > a = c("a","a","b","b","c") > levels(as.factor(a)) [1] "a" "b" "c" > levels(as.factor(a[1:3])) [1]

(1) I have a master data frame that reads ClientID |date |value (2) I also have a control data frame that reads Client ID| Min date| Max date| control parameters The control data set may not have all client IDs . I want to use the control data frame on the master data frame to remove client IDS that don't exist in the control data set and for those that do, remove dates outside the

I have > df quantity branch client date name 1 10 1 1 2010-01-01 one 2 20 2 1 2010-01-01 one 3 30 3 2 2010-01-01 two 4 15 4 1 2010-01-01 one 5 10 5 2 2010-01-01 two 6 20 6 3 2010-01-01 three 7 1000 1 1 2011-01-01 one 8 2000 2 1 2011-01-01

I have a data frame that reads client ID date transcations 323232 11/1/2010 22 323232 11/2/2010 0 323232 11/3/2010 missing 121212 11/10/2010 32 121212 11/11/2010 15 ................................. I want to order the rows by client ID and date and using a black-box forecasting method create the data fcst(client,date of forecast, date for which forecast applies). Assume that I

Is there a way to use read.csv() on such a file without deleting one of the header rows? Thanks.

the csv files are downloaded from a database and it looks like some character fields contain the CR-LF sequence within them. This causes R to see a new record/row and the number of rows it sees is different (usually higher) from the number of rows actually extracted. Any suggestions? Thanks.

an example available on the net goes like > df identifier quantity 1 1 10 2 1 20 3 2 30 4 1 15 5 2 10 6 3 20 > aggregate(df$quantity, by=list(df$identifier), sum) Group.1 x 1 1 45 2 2 40 3 3 20 I'd like Group.1 to retain the name "identifier" and would like to

I have a data frame with three columns client ID | date | value For each cilent ID I want to determine Min date and Max date and for any dates in between that are missing I want to insert a row Client ID | date| NA Any help would be appreciated.

I have a dataframe with columns "ID",'date","estimate","actual" (but not necessarily in that order - I do a merge somewhere and that somehow messes up the order of the columns). How can I output it to a csv file with the columns in the order that I want? Thanks.

I download a csv extract from a database and use read.csv to read it from R and when there are large character fields with embedded blanks, slashes etc. - R often sees one line as two lines (or more). I verfied with readLines that an embedded blank in a character field causes a spurious new line to be seen. I am sure this problem has beem seen before - and would appreciate any help in reading

...; and provide commented, minimal, self-contained, reproducible code. > -- Jim Holtman Data Munger Guru What is the problem that you are trying to solve? ------------------------------ Message: 14 Date: Fri, 21 Jan 2011 07:58:04 -0500 From: jim holtman <jholtman@gmail.com> To: "analyst41@hotmail.com" <analyst41@hotmail.com> Cc: r-help@r-project.org Subject: Re: [R] data and parameters Message-ID: <AANLkTimn=o7kcuD3jZyVyjH=kMK=-5Yb+rNJW2eO-sod@mail.gmail.com<5Yb%2BrNJW2eO-sod@mail.gmail.com> > Content-Type: text/plain; charset=ISO-8859-1 try 'sqldf...

Have > actualsdf ID Name datadate val 1 23 Acme Corp 1 23 2 23 Acme Corp 2 43 3 23 Acme Corp 3 54 4 23 Acme Corp 4 65 5 23 Acme Corp 5 23 6 23 Acme Corp 6 43 7 23 Acme Corp 7 NA 8 23 Acme Corp 8 43 9 23 Acme Corp 9 54 10 23 Acme Corp 10 32 > fcstdf fcstrundate fcstdate fcst ID Name 1