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...t;environment: namespace:base> Stefano >-----Messaggio originale----- >Da: r-help-bounces at stat.math.ethz.ch >[mailto:r-help-bounces at stat.math.ethz.ch]Per conto di >Guazzetti Stefano >Inviato: Thursday, May 04, 2006 07:55 AM >A: isaia at econ.unito.it; ruser2006 at yahoo.com >Cc: r-help at stat.math.ethz.ch >Oggetto: [R] R: [Re:] function to replace missing values with median >value?]] > > >there is also a replace function > > > >-----Messaggio originale----- > >Da: r-help-bounces at sta...

I have a dataset of 3 ?columns? and 5 ?rows?. temp<-data.frame(col1=c(5,10,14,56,7),col2=c(4,2,8,3,34),col3=c(28,4,52,34,67)) I wish to convert this to a single ?column?, with column 1 on ?top? and column 3 on ?bottom?. i.e. 5 10 14 56 7 4 2 8 3 34 28 4 52 34 67 Are there any functions that do this, and that will work well on much larger datasets (e.g. 1000 rows, 6000 columns)?

I am using R 2.1.1 in a Windows Xp environment. I need to import a large database from Microsoft SQL into R. I am currently using the ?sqlQuery? function/command. This works, but I sometimes run out of memory if my database is too big, or it take quite a long time for the data to import into R. Is there a better way to bring a large SQL database into R? IS there an efficient way to convert

Is there a way to get the following code to include NA values where the coefficients are ?NA?? ((summary(reg))$coefficients) explanation: Using a loop, I am running regressions on several ?subsets? of ?data1?. ?reg <- ( lm(lm(data1[,1] ~., data1[,2:l])) )? My regression has 10 independent variables, and I therefore expect 11 coefficients. After each regression, I wish to save the

I have many very large dataframes with 20 columns each. In order to conserve memory, I wish to separate the data frame into 20 vectors, each named the name of the dataframe followed by .1,.2,.3 .20. (For example purposes, one data frame is named ?testa?.) e.g. testa.1, testa.2, testa.3 I have written the code to do this (see below). I am trying to convert this into a function that I can reuse.

I am using R in a Windows environment. I have a basic question regarding lm(). I have a dataframe ?data1? with ncol=w. I know that my dependent variable is in column1. Is there a way to write the regression formula so that I can use columns 2 thru w as my independent variables? e.g. something like: ? lm(data1[,1] ~ data1[,2:w] ) ? Thanks

I am running R 2.1.1 in a Windows XP environment. I wish to use the sqlSave command to export a dataframe into Microsoft SQL. My dataframe is called temp and has 2 ?columns?, ?monthenddate? and ?value?. Monthenddate is in 'POSIXct', format. (i.e. 'POSIXct', format: chr "1984-01-31" "1984-01-31" "1984-01-31" "1984-01-31" ...). How can I

I have a dataset with 20 columns and ~600,000 rows. Column 1 has a number from 2-19. This number tells me, for each row, which column has the ?applicable? data. (i.e. the data that I wish to use for each individual row) I want to create a vector that contains the data from the value in column 1. e.g. If column 1, row 1, has a value of ?6?, I want to obtain the value in column 6, row1. If

I have two datasets, big and small. s_date<-c(?2005-12-02?, ?2005-12-01?, ?2004-11-02?,?2002-10-05?,?2000-12-15?) s_id<-c(?a?,?a?,?b?,?c?,?d?) b_date<- c(?2005-12-31?, ?2005-12-31?, ?2004-12-31?,?2002-10-05?,?2001-10-31?,?1999-12-31?) b_id<-c(?a?,?b?,?c?,?d?,?e?,?c?) small<-data.frame(date_=as.Date(s_date),id=s_id) big<-data.frame(date_=as.Date(b_date),id=b_id) For each row

I am trying to combine the value of a variable and text. e.g. I want ?test1?, with no spaces. I try: h=1 paste(?test?,1) But get: [1] "test 1" (i.e. there is a space between ?test?? and ?1?) Is there a way to eliminate the space?

I am using R 2.1.1 in an windows XP environment. I have 2 dataframes, temp1 and temp2. Each dataframe has 20 variables (“cocolumns") and 525 observations (“rows”). All variables are numeric. I want to create a new dataframe that also has 20 columns and 525 rows. The values in this dataframe should be the sum of the 2 other dataframe. (i.e. temp1$column

I have a dataframe of numeric values with 30 ?rows? and 7 ?columns?. For each column, beginning at ?row? 12 and down to ?row? 30, I wish to calculate the ?rolling 12 row product?. I.e., within each column, I wish to multiply all the values in row 1:12, 2:13, 19:30. I wish to save the results as a new dataframe, which will have 19 rows and 7 columns.

getting s-apply to skip columns with non-numeric data? I have a dataframe ?x? of w columns. Some columns are numeric, some are not. I wish to create a function to calculate the mean and standard deviation of each numeric column, and then ?bind? the column mean and standard deviation to the bottom of the dataframe. e.g. tempmean <- apply(data.frame(x), 2, mean, na.rm = T) xnew <-

I am running R 2.1.1 in a Microsoft Windows XP environment. I have a matrix with three vectors (“columns”) and ~2 million “rows”. The three vectors are date_, id, and price. The data is ordered (sorted) by code and date_. (The matrix contains daily prices for several thousand stocks, and has ~2 million “rows”. If a stock did not trade on a particular date, its price is set to “NA”)

I am using R 2.2.1 in a Windowes XP environment. I work with very large datasets, and occassionally run out of memory. I have modified my boot.ini file to use the "/3gb switch". I also run the following line after I launch R ( I am unsure if it is helpful). "memory.limit(size = 4095)" Please point me to useful references on how to better manage memory, or suggestother

I am using the R 2.2.1 in a Windows XP environment. I have a dataframe with 12 columns and 1,000 rows. (Some of the rows have 1 or fewer values.) I am trying to use rowVars to calculate the variance of each row. I am getting the following message: ?Error in na.remove.default(x) : length of 'dimnames' [1] not equal to array extent? Is there a good work-around?

What is the difference among an array, a dataframe and a matrix? Why is the size of a dataframe so much larger? (see example below) a<-c(rep(1:1000000,1)) b<-c(rep(1:1000000,1)) c1<-cbind(a,b) cdf<-as.data.frame(cbind(a,b)) cm<-as.matrix(cbind(a,b)) object.size(a)/1000000 object.size(b)/1000000 object.size(c1)/1000000 object.size(cdf)/1000000 object.size(cm)/1000000

I have a dataframe named ?temp?, and another dataframe named ?descriptions?. I wish to ?rename? temp, and to ?call? it the names of a certain column in the dataframe ?descriptions?. Is there a good way to do this? A similar question: I am using a ?for loop? to create several new dataframes. e.g. for(j in 1:9){ .. I?d like each dataframe to be named d1, d2, d3, with the number being tied to

I have a dataframe of 25 columns and 100,000 rows called ?testdf?. I wish to build a new dataframe, with 14 columns and 100,000 rows. I wish the new dataframe to have the ?trailing 12 column? mean. That is, I want column 1 of the new dataframe to have soemthing like: ?( mean(testdf[,1:12],na.rm=T)? What is the best way to accomplish this?

I have a dataframe with 700,000 rows and 2 vectors (columns): ?group? and ?score?. I wish to calculate a third vector of length 700000: the average score by group. Even though the avarge value will repeat, I wish to return the average for that particular group for each row. (I know I can do this by calculating each group?s average and then using the merge command, but as my calculations get