ot;,
"", "", "", "69884", "79524", "18106", ""), Code19 = c("73031",
"", "", "", "12840", "93888", "78589", ""), Code20 = c("11326",
&
Hi Arun,
The second method is indeed working much faster. It worked fast for my
600.000 row record.
Still I have 2 bigger files where processing becomes an issue even though I
have lots of memory (32 gig) for the second statement:
res2<-reshape(dat2,idvar="newCol",varying=list(2:26),direction="lon
Hi A.K,
Thanks for your great help.
I'm now running your first suggestion on a 600.000 row sample after
verifying it works on a smaller sample.
It's now been running for 40 minutes.
Which method do you think will be faster?
Regards Derk
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Hi,
My desired output for my sample!! using dput():
structure(list(ID = c("1", "2", "3", "4", "5", "6", "7", "8",
"9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19",
"20", "21", "22", "23", "24", "25", "26", "27", "28", "29", "30",
"31", "32", "33", "34", "35", "36", "37", "38", "3
Hi experts,
I have a dataframe with 100k+ records. it has a key/id column and 25 code
columns. I would like to restructure it having a row for each code column.
I have a structure like this (used dput):
structure(list(DSYSRTKY = structure(c(1L, 2L, 3L, 3L, 4L, 4L), .Names =
c("1",
"2", "3", "4",
Hi all,
I have a dataframe of users which contain US-state codes.
Now I want to add a column named REGION based on the state code. I have
already done a mapping:
NorthEast <- c(07, 20, 22, 30, 31, 33, 39, 41, 47)
MidWest <- c(14, 15, 16, 17, 23, 24, 26, 28, 35, 36, 43, 52)
South <- c(01, 04, 08,
Hi all,
I have two datasets:
Dataset 1 - List of Users, the layout looks like this:
ID Name C1 C2 C3 C23 C24 C25
Dataset 2 - List of Codes, the layout looks like this:
Code Description Category
The code fields in the user-dataset do not have to contain a value and if
they have
Hi all,I have two datasets:*Dataset 1 - List of Users:*ID Name C1 C2 C3
C23 C24 C25*Dataset 2 - List of Codes*Code Description
CategoryThe code fields in the user-dataset do not have to contain a value
and if they have a value they dont have to correspond with the
Codes-dataset.Now I ne
Hi Arun Kirshna,
I have tested your method and it will work for me.
I only run into one problem. Before I want to do this operation I have
sorted my data frame so my rownumbers ar not subsequent.
You can see if you first order your example data frame like:
dat1 <- dat1[order(-dat1$value),]
head(
Works like a charm, thanks a lot!
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Hi all,
I think this should be an easy question for the guru's out here.
I have this large data frame (2.500.000 rows, 15 columns) and I want to add
a column named "SEGMENT" to it.
The first 5% rows (first 125.000 rows) should have the value "Top 5%" in the
SEGMENT column
Then the rows from 5% to
Hi,
Yes maybe I should have been more clear on my problem.
I want to append the different data-frames back into one variable ( rbind )
and save it as one R Data file.
Regards Derk
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Really no one has any suggestions on this issue?
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R-help@r-proj
Hi all,
For a project we have to process some very large CSV files (up to 40 gig)
To reduce them in size and increase operating performance I wanted to store
them as RData files.
Since it was to big I decided to split the csv and saving those parts as
separate .RDA files.
So far so good. Now I wan
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