similar to: Does a data frame have indexes for columns?

Hi, all, Does R have a "const object" concept like which is in C++ language? I want to set some data frames as constant to avoid being modified unintentionally. Thanks! xiagao1982 2011-03-15 [[alternative HTML version deleted]]

Consider the data.frame: df <- data.frame(A = c(1,4,2,6,7,3,6), B= c(3,7,2,7,3,5,4), C = c(2,7,5,2,7,4,5), index = c("A","B","A","C","B","B","C")) I want to select the column specified in 'index' for every row of 'df', to get goal <- c(1, 7, 2, 2, 3, 5, 5) This sounds a lot like the indexing-by-a-matrix

Hi all, I create some objects in local(), and want to pass them to GlobalEnv. How can I do this? Thanks! xiagao1982 2011-05-02 [[alternative HTML version deleted]]

Hi all, I am a C++/C# programmer who is new to R. I would like to use something like "namespace" to organize my functions without creating a package. How can I do this? Thanks! xiagao1982 2011-04-30 [[alternative HTML version deleted]]

Hi -- I'm working with some data frames with fairly high nrows (call it 8 columns, by 20,000 rows). Are there any indexes on these columns? When I do a df[df$foo == 42,] [which I think is idiomatic], am I doing a linear search or something better? If the column contents is ordered, I'd like to at least be doing a naive binary search. Thanks! Ranjan

I am in a holding pattern while client decides upon changes and so I am working some things out internally so it seems to me that indexing frequently searched table fields might be useful. I am using postgres and via postgres, I have added an index to one of my tables whose index is the same name as the column name. The ''find'' screen I am using this to judge populates a number

Dear baseRs, I recently made a mistake when renaming data frame columns, accidentally creating an NA column. I found the following strange behavior when negative indexes are used. Can anyone explain what happens here. No "workarounds" required, just curious. Dieter Version: Windows, R version 2.6.1 (2007-11-26) #----------------------------- df = data.frame(a=0:10,b=10:20) df[,-2]

Dear all, Sometimes I have the situation where a function takes a data.frame and an additional argument describing come columns. For greater flexibility I want to allow for either column names or column indices. What I usually do then is something like the following: -------------8<------------- f <- function(datf, cols) { nc <- seq_along(datf) cn <- colnames(datf) colOK <-

Dear Ivan, thanks a lot, that is helpful. Still, I feel that default partial matching cripples the functionality of data.frame for larger tables. Thanks again and best regards Hilmar On 12.12.23 13:55, Ivan Krylov wrote: > ? Mon, 11 Dec 2023 21:11:48 +0100 > Hilmar Berger via R-devel <r-devel at r-project.org> ?????: > >> What was unexpected is that in this case was that

Hi Hilmar and Ivan, I have used your code examples to write a blog post about this topic, which has figures that show the asymptotic time complexity of the various approaches, https://tdhock.github.io/blog/2023/df-partial-match/ The asymptotic complexity of partial matching appears to be quadratic O(N^2) whereas the other approaches are asymptotically faster: linear O(N) or log-linear O(N log N).

On Wed, 13 Dec 2023 09:04:18 +0100 Hilmar Berger via R-devel <r-devel at r-project.org> wrote: > Still, I feel that default partial matching cripples the functionality > of data.frame for larger tables. Changing the default now would require a long deprecation cycle to give everyone who uses `[.data.frame` and relies on partial matching (whether they know it or not) enough time to

This is what to start with: Data Frame A B C D c1 4 y 5 c3 6 d 7 c1 5 t 6 Now sort on A then C This is what to end with: Data Frame A B C D c1 5 t 6 c1 4 y 5 c3 6 d 7 I assume it is something like this: attach(DF) sort(DF,partial=c(A,C)) Thanks in advance. Meredith [[alternative HTML version deleted]]

Hi, data.frame(x1=1:11,x2=2:12,x3=3:13,y=4:14) I want to extract all the columns that with the name 'x?'. Is there a general way to do this in R? Regards, Peng

Greetings, Is it possible to match several columns in a merge statement? Here is my problem: data1 looks like this... SUBID TARGID ITEM RATING 1 1 1 4 1 1 2 5 1 1 3 3 1 1 4 2 1 1 5 5 ...... SUBID is the ID for the raters, TARGID is the ID for the targets being rated, ITEM ranges from 1 to 64 crossed

#Hello, # I have a question about the addition of values in specific columns and rows of a Data frame. # Below I have created two data frames, X.df and "Y.df". ## creation of X.df data frame X<- matrix(0,16,3) X.df<-data.frame(X) X.df[,1] <- c(1,1,1,1,2,2,2,2,3,3,3,3,4,4,4,4) X.df[,2] <- c(1,2,3,4,1,2,3,4,1,2,3,4,1,2,3,4) names(X.df)[1]<-"L(A)a(i)"

Hello, I am trying to extract a subset of a dataframe A (2 columns) by extracting all entries in A (several repeated entries) that match dataframe B in both columns. For example, part of A and B are shown below. The following does not seem to work correctly. This only seems to select on the first component and all instances of the second. ind <- A$C1 %in% B[,1] & A$C2 %in% B[,2]

Dear R-Users, I have a problem with an algorithm that iteratively goes over a data.frame and exclude n-columns each step based on a statistical criterion. So that the 'column-space' gets smaller and smaller with each iteration (like when you do stepwise regression). The problem is that in every round I use a new subset of my data.frame. However, as soon as I "generate" this

Can you suggest me any way to remove a column of a data frame by the column number,not by the column name. Thanks, Suman Dhara [[alternative HTML version deleted]]

(Re-)read the discussion of indexing (both `[` and `[[`) and be sure to get clear on the difference between matrices and data frames in the Introduction to R document that comes with R. There are many ways to create numeric vectors, character vectors, and logical vectors that can then be used as indexes, including the straightforward way: df[ c( "Unique to strat ", "Unique

Dear all, I have seen that others have discussed the partial matching behaviour of data.frame[idx,] in the past, in particular with respect to unexpected results sets. I am aware of the fact that one can work around this using either match() or switching to tibble/data.table or similar altogether. I have a different issue with the partial matching, in particular its performance when used on