Displaying 5 results from an estimated 5 matches for "svdatstr".
2016 Apr 20
0
Data reshaping with conditions
...lly B
18 340 susan A
56 340 susan A
22 340 susan B
53 340 susan B
135 351 lee A
114 351 lee A
84 351 lee A
80 351 lee A
19 351 lee A
8 351 lee A
21 351 lee A
88 351 lee B
111 351 lee B
46 351 lee B
108 351 lee B",header=TRUE)
# you can also do this with other reshape functions
library(prettyR)
svdatstr<-stretch_df(svdat,"id",c("Count","type"))
count_ind<-grep("Count",names(svdatstr))
type_ind<-grep("type",names(svdatstr))
svdatstr$maxA<-NA
svdatstr$maxB<-NA
svdatstr$x<-NA
svdatstr$y<-NA
for(row in 1:nrow(svdatstr)) {
svdatstr...
2016 Apr 21
2
Data reshaping with conditions
...135 351 lee A
> 114 351 lee A
> 84 351 lee A
> 80 351 lee A
> 19 351 lee A
> 8 351 lee A
> 21 351 lee A
> 88 351 lee B
> 111 351 lee B
> 46 351 lee B
> 108 351 lee B",header=TRUE)
> # you can also do this with other reshape functions
> library(prettyR)
> svdatstr<-stretch_df(svdat,"id",c("Count","type"))
> count_ind<-grep("Count",names(svdatstr))
> type_ind<-grep("type",names(svdatstr))
> svdatstr$maxA<-NA
> svdatstr$maxB<-NA
> svdatstr$x<-NA
> svdatstr$y<-NA
> for(r...
2016 Apr 21
0
Data reshaping with conditions
...lly B
18 340 susan A
56 340 susan A
22 340 susan B
53 340 susan B
135 351 lee A
114 351 lee A
84 351 lee A
80 351 lee A
19 351 lee A
8 351 lee A
21 351 lee A
88 351 lee B
111 351 lee B
46 351 lee B
108 351 lee B",header=TRUE)
# you can also do this with other reshape functions
library(prettyR)
svdatstr<-stretch_df(svdat,"id",c("Count","type"))
count_ind<-grep("Count",names(svdatstr))
type_ind<-grep("type",names(svdatstr))
svdatstr$maxA<-NA
svdatstr$maxB<-NA
svdatstr$x<-NA
svdatstr$y<-NA
for(row in 1:nrow(svdatstr)) {
indicesA...
2016 Apr 20
2
Data reshaping with conditions
Dear All,
I am trying to reshape the data with some conditions. A small part of the
data looks like below. Like this there will be more data with repeating ID.
Count id name type
117 335 sally A
19 335 sally A
167 335 sally B
18 340 susan A
56 340 susan A
22 340 susan B
53 340 susan B
135 351 lee A
114 351 lee A
84 351 lee A
80 351 lee A
19 351 lee A
8 351 lee A
21 351 lee A
88 351 lee B
111 351
2016 Apr 21
0
Data reshaping with conditions
In R, square brackets [] are called "extraction operators" as they are
interpreted so as to "extract" the parts of an object specified by the
information within them. Your message contained only part of the line
below:
AltB<-svdatstr[row,indicesA][svdatstr[row,indicesA]<svdatstr[row,"maxB"]]
Extraction operators may be specified sequentially or nested. Both are
used in this line. However, to understand how it works, first look at
the line that defines the value of "indicesA":
indicesA<-count_ind[as....