On 9/9/2008 2:12 PM, Adam D. I. Kramer wrote:
Maybe something like this:
by(df[,c(77,81,86,90,94,98,101,106)],df$category,apply,2,mean)
...which would then need to be reformatted into a data frame (there is
probably an easy way to do this which I don't know).
sparseby() in the reshape package is more flexible than by(). If the
function returns a vector with a consistent length, you'll get a
dataframe with columns corresponding to its entries.
Duncan Murdoch
aggregate seems like a more reasonable choice, but the function for
aggregate must return scalars, not rows...tapply doesn't take data.frame
inputs. Maybe someone else has a suggestion?
--Adam
On Tue, 9 Sep 2008, Lawrence Hanser wrote:
Dear Colleagues,
I have a dataframe with variables:
[1] "ID" "category" "a11" "a12"
"a13" "a21"
[7] "a22" "a23" "a31" "a32"
"b11" "b12"
[13] "b13" "b21" "b31" "b32"
"b33" "b41"
[19] "b42" "c11" "c12" "c21"
"c22" "c23"
[25] "c31" "c32" "c33" "d11"
"d12" "d13"
[31] "d14" "d21" "d22" "d23"
"d24" "d25"
[37] "d31" "d32" "d33" "e11"
"e12" "e13"
[43] "e21" "e22" "e23" "e31"
"e32" "e33"
[49] "f11" "f12" "f13" "f14"
"f21" "f22"
[55] "f23" "f24" "g11" "g12"
"g13" "g14"
[61] "g21" "g22" "g23" "g24"
"g31" "g32"
[67] "g33" "g41" "g42" "g43"
"h11" "h12"
[73] "h13" "h21" "h22" "h23"
"C1.Employ" "SC11.Ops"
[79] "SC12.Unit" "SC13.Nonadvers" "C2.Enterprise" "SC21.Structure"
"SC22.Gov" "SC23.Culture"
[85] "SC24.Stratcomm" "C3.Manage" "SC31.Resource" "SC32.Change"
"SC33.Continue" "C4.Stratthink"
[91] "SC41.Vision" "SC42.Decision" "SC43.Adapt" "C5.Lead"
"SC51.Develop" "SC52.Care"
[97] "SC53.Diversity" "C6.Foster" "SC61.Teams" "SC62.Negotiate"
"C7.Embody" "SC71.Ethical"
[103] "SC72.Follower" "SC73.Warrior" "SC74.Develop" "C8.Comm"
"C81.Speak" "C82.Listen"
[109] "OverallImp"
The variable "category" has four values: Regular, CCM, CFM, and Other
I'd like to create a table like this to feed into barplot2:
row.name C1.Employ C2.Enterprise C3.Manage C4.Stratthink C5.Lead
C6.Foster C7.Embody C8.Comm
Regular 3.68 4.27 3.22
etc......
CCM 4.32 4.56 etc.....
CFM etc.........
Other etc.........
So far, I have been able to get this far:
>
mean(subset(impchiefs08,category=="Regular",select=c(C1.Employ,C2.Enterprise,C3.Manage,C4.Stratthink,C5.Lead,C6.Foster,C7.Embody,C8.Comm
)))
C1.Employ C2.Enterprise C3.Manage C4.Stratthink C5.Lead
C6.Foster C7.Embody C8.Comm
3.600000 3.851111 4.482222 4.346667 4.608889
4.444444 4.602222 4.493333
But I am stumped as to how to get what I want.
Thanks in advance.
Larry
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and provide commented, minimal, self-contained, reproducible code.
