Displaying 20 results from an estimated 1000 matches similar to: "Dividing rows when time is overlapping"
2009 Feb 19
3
Multiple merge, better solution?
Hello,
My problem is that I would like to merge multiple files with a common
column but merge accepts only two
data.frames to merge. In the real situation, I have 26 different
data.frames with a common column. I can of course use merge many times
(see below) but what would be more sophisticated solution? For loop?
Any ideas?
DF1 <- data.frame(var1 = letters[1:5], a = rnorm(5))
DF2 <-
2004 Mar 15
1
gzfile & read.table on Win32
Hello ...
Are there any known problems or even gotchas to look out for when using a
gzfile connection in read.csv/read.table in Windows?
In the package PROcess, available at
www.bioconductor.org/repository/devel/package/html/PROcess.html
there are two files in the PROcess/inst/Test directory which are of the
extension *.csv.gz.
With both files, if I open up a gzfile connection, say:
vv <-
2010 Nov 11
4
How to get a specific named element in a nested list
Hello,
I have a nested named list structure, like the following:
x <- list(
list(
list(df1,df2)
list(df3,
list(df4,df5))
list(df6,df7)))
with df1...d7 as data frames. Every data frame is named.
Is there a way to get a specific named element in x?
so, for example,
x[[c("df5")]] gives me the data frame 5?
Thank you in advance!
Best,
Friedericksen
2012 Jan 26
1
How to remove rows representing concurrent sessions from data.frame?
I have a dataset like this (dput for this below) which represents user
computer sessions:
username machine start end
1 user1 D5599.domain.com 2011-01-03 09:44:18 2011-01-03 09:47:27
2 user1 D5599.domain.com 2011-01-03 09:46:29 2011-01-03 10:09:16
3 user1 D5599.domain.com 2011-01-03 14:07:36 2011-01-03 14:56:17
4 user1 D5599.domain.com
2011 Aug 29
2
splitting into multiple dataframes and then create a loop to work
Dear All
Sorry for this simple question, I could not solve it by spending days.
My data looks like this:
# data
set.seed(1234)
clvar <- c( rep(1, 10), rep(2, 10), rep(3, 10), rep(4, 10)) # I have 100
level for this factor var;
yvar <- rnorm(40, 10,6);
var1 <- rnorm(40, 10,4); var2 <- rnorm(40, 10,4); var3 <- rnorm(40, 5, 2);
var4 <- rnorm(40, 10, 3); var5 <- rnorm(40, 15,
2009 Oct 07
1
merging dataframes with an unequal number of variables
Hallo Everyone
I have the kind of problem that one should never have because one must
always plan well and communicate with your team. But now I haven't so here
is my problem.
I have data coming in on a daily basis from surveys in 10 towns. The
questionnaire has 62 variables but some of the regions have used older
versions of the questionnaire that have a few variables less. I want to
combine
2007 Sep 27
2
create data frame(s) from a list with different numbers of rows
# Hello,
# I have a list with 6 categories and with different numbers of rows.
# I would like to change each of them into a unique data frame in order to
match
# values with other data frames and perform some calculations.
# Or I could make each category or list element have the same number of rows
and create one large data.frame.
# below is a creation of a sample list
# I apologize for the
2010 Dec 16
2
Compare two dataframes
Hello,
I have two dataframes DF1 and DF2 that should be identical but are not
(DF1 has some rows that aren't in DF2, and vice versa). I would like
to produce a new dataframe DF3 containing rows in DF1 that aren't in
DF2 (and similarly DF4 would contain rows in DF2 that aren't in DF1).
I have a solution for this problem (see self contained example below)
but it's awkward and
2007 Oct 22
3
median value dataframe coming from multiple dataframes
Hi all,
I am not a skillful R programmer and has I am handling with large dataframes (about 30000 x 300) I am in need of an efficient function.
I have 4 dataframes with the same dimension. I need to generate other dataframe with the some dimension than the others where in each position it has the median value of the 4 values in the same position coming from the 4 dataframes.
Grateful by your
2012 Jun 03
2
merging single column from different dataframe
Hi all,
probably really simple to solve, but having no background in programming I
haven't been able to figure this out: I have two dataframes like
df1 <- data.frame(names1=c('aa','ab', 'ac', 'ad'), var1=c(1,5,7,12))
df2 <- data.frame(names2=c('aa', 'ab', 'ac', 'ad', 'ae'),
var2=c(3,6,9,12,15))
Now I want merge
2012 Jun 12
4
replacing NA for zero
Dear R users,
I have a very basic query, but was unable to find a proper anwser.
I have the following data.frame
x y
2 0.12
3 0.25
4 0.11
6 0.16
7 0.20
and, due to further calculations, I need the data to be stored as
x y
1 0
2 0.12
3 0.25
4 0.11
5 0
6 0.16
7 0.20
8 0
How do
2004 Mar 09
5
Adding data.frames together
I have a series of data frames that are identical structurally, i.e. -
made with the same code, but I need to add them together so that they
become one, longer, data frame, i.e. - each of the slot vectors are
increased in length by the length of the added data frame vectors.
So if I have df1 with a slot A so that length(df1$A) = 100 and I have
df2 with a slot A so that length(df2$A)=200 then I
2010 Jan 20
1
Reshaping data with xtabs giving me 'extra' data
Dear all,
Lets say I have several data frames as follows:
> set.seed(42)
> dates <- as.Date(c("2010-01-19", "2010-01-20"))
> times <- c("09:30:00", "11:30:00", "13:30:00", "15:30:00")
> shows <- c("Red Dwarf", "Being Human", "Doctor Who")
>
> df1 <- data.frame(Date = dates[1],
2013 Jun 11
1
mapply on multiple data frames
Hi all-
I am wondering about using the mapply function to multiple data frames. Specifically, I would like to do a t-test on a subset of multiple data frames. All data frames have the same structure.
Here is my code so far:
f<-function(x,y) {
test<-t.test(x$col1[x$col3=="num",],v$col2[x$col3=="num",],paired=T,alternative="greater")
out<-test$p.value
2010 Sep 04
4
Please explain "do.call" in this context, or critique to "stack this list faster"
I've been doing some consulting with students who seem to come to R
from SAS. They are usually pre-occupied with do loops and it is tough
to persuade them to trust R lists rather than keeping 100s of named
matrices floating around.
Often it happens that there is a list with lots of matrices or data
frames in it and we need to "stack those together". I thought it
would be a simple
2010 Jun 08
3
more dates and data frames
Dear R People:
So thanks to your help, I have the following:
> dog3.df <- read.delim("c:/Users/erin/Documents/dog1.txt",header=FALSE,sep="\t")
> dog3.df
V1 V2
1 1/1/2000 dog
2 1/1/2000 cat
3 1/1/2000 tree
4 1/1/2000 dog
5 1/2/2000 cat
6 1/2/2000 cat
7 1/2/2000 cat
8 1/2/2000 tree
9 1/3/2000 dog
10 1/3/2000 tree
11 1/6/2000 dog
12 1/6/2000
2005 Oct 20
1
Windows 2000 crash while using rbind (PR#8225)
Windows 2000 reports that "Rgui.exe has generated errors and will be =
closed by Windows. You will need to restart the program." when using =
rbind.=20
df1 <- data.frame(cbind(x=3D1, y=3D1:1000), fac=3Dsample(LETTERS[1:3], =
1000, repl=3DTRUE))
df2 <- data.frame(cbind(x=3D1, y=3D1:10), fac=3Dsample(LETTERS[4:6], =
10, repl=3DTRUE))
df3 <- data.frame(cbind(x=3D1,
2009 Dec 09
2
Problem with if statement
I am trying to use the value of an ID variable in an if statement and
not getting the results I expected.
# ID values for two school districts
> with(rf, tapply(DistrictID, DistrictName, min) )
Aberdeen School Dist. # 58 Buhl Joint School District
59340 53409
This creates DNAME as I expected ...
2012 Aug 27
2
simplest way (set of functions) to parse a file
Hello,
What would be the best set of R functions to parse and transform a file?
My file looks as shown below. I would like to plot this data and I need to parse it into a single data frame that sorts of "transposes the data" with the following structure:
> df <- data.frame(n=c(1,1,2,2),iter=c(1,2,1,2),step=as.factor(c('Step 1', 'Step2', 'Step 1',
2011 Feb 10
2
for loop to merge .csvs
So I needed to merge 17 .csv files, and did so by brute force, but I might
need to do so again. Anyone have suggestions for a for loop that might do
the below for me (where a:r are separate .csv files)
ab<-merge(a,b,all=TRUE)
cd<-merge(c,d,all=TRUE)
ef<-merge(e,f,all=TRUE)
gh<-merge(g,h,all=TRUE)
ij<-merge(i,j,all=TRUE)
kl<-merge(k,l,all=TRUE)
no<-merge(m,n,all=TRUE)