This is a small example to illustrate my data:
> df <- data.frame(subgroup =rep(paste("s",1:3, sep=""), times=3), feature=c(rep("a",6), rep("b",3)) , var=rep(1:3, each=3), data=c(rnorm(3,1
Tag: aggregate
How to use aggregates with list names
How do I summarize the aggregation in a function by passing a list of conditions and values?
# This works fine:
x <- data.frame(cond1 = sample(letters[1:3], 500, replace=TRUE) ,
cond2 = sam
How to use Pandas aggregate DateTime objects to int
I have this DataFrame structure
id time number
0 1 1970-01-01 00: 00:00 1
1 2 1970-01-02 00:00:00 2
2 1 1970-01-03 00:00:00 2 I want groupby id And aggregate the time of pd.Datetime dtype int
When I don’t want to use aggregate, I should use Pivot to convert SQL Server 2008 row value to column names?
I am trying to master the manipulation of table data into a more visually attractive output format. This may be part of the problem, because what I want may be for a separate reporting software. <
How to use custom column names (using “by”) Data.Table without using “: =”?
I know I can do this
a <- dt[,sum(x), by=y ] I can do this too
dt[,z:=sum(x), by=y] # this would modify dt But I don’t know why I can’t do this:
a <- dt[,z=sum(x), by=y] < p>How t