Dear Rui,
Thnak you very much: this works exactly as I requested, but the merged
vetor (res) order the variables by alphabetical order rather than by the
factors I indicated during the definition of the data frame; thus AVG,
SD and res have different row order.
When I tried to define the factors of AVG, SD and resthe original order
is not kept:
> AVG
stimulation copy
1 Unstimulated 1470.080
2 ESAT6 2043.772
3 CFP10 6107.652
4 Rv3615c 1639.437
5 Rv2654 4025.472
6 Rv3879 2558.704
7 Rv3873 3538.781
8 PHA 213613.795
AVG$stimulation<-factor(AVG$stimulation, levels = c("Unstimulated",
"ESAT6", "CFP10", "Rv3615c",
"Rv2654", "Rv3879", "Rv3873", "PHA"))
SD$stimulation<-factor(SD$stimulation, levels = c("Unstimulated",
"ESAT6", "CFP10", "Rv3615c",
"Rv2654", "Rv3879", "Rv3873", "PHA"))
res$stimulation<-factor(res$stimulation, levels = c("Unstimulated",
"ESAT6", "CFP10", "Rv3615c",
"Rv2654", "Rv3879", "Rv3873", "PHA"))
> res
stimulation AVG SD lower upper
1 CFP10 6107.652 9597.686 -3490.0334 15705.338
2 ESAT6 2043.772 3674.133 -1630.3606 5717.905
3 PHA 213613.795 789614.399 -576000.6044 1003228.194
4 Rv2654 4025.472 5933.346 -1907.8739 9958.818
5 Rv3615c 1639.437 2546.439 -907.0025 4185.876
6 Rv3873 3538.781 6205.863 -2667.0813 9744.644
7 Rv3879 2558.704 5812.945 -3254.2414 8371.649
8 Unstimulated 1470.080 1698.197 -228.1178 3168.277
May I ask whether there is a method to solve this discrepancy?
best regards,
Luigi
On Wed, Mar 19, 2014 at 6:50 PM, Rui Barradas <ruipbarra...@sapo.pt
<mailto:ruipbarra...@sapo.pt>> wrote:
Hello,
Maybe something like the following.
res <- merge(AVG, SD, by = "stimulation")
names(res)[2:3] <- c("AVG", "SD")
res$lower <- res$AVG - res$SD
res$upper <- res$AVG + res$SD
res
Hope this helps,
Rui Barradas
Em 19-03-2014 18:15, Luigi Marongiu escreveu:
Dear all,
I have obtained the averages (means) and standard deviations (SD) of
different variable using the aggregate function, which I have
found very
useful for these kind of computation.
However I would like to calculate the lower and upper ends of the
data (that is mean - SD and mean + SD) varible-wise, but I don't
know how
to cope with this aggregate data. I cannot simply subtract the
aggregated
results (which I have called AVG and SD) and the aggregate
function is a
bit too complicated for me.
Does anybody knows how to add and subtract the means and standard
deviations obtained using the aggregate function?
Best regards,
Luigi
my.data<-structure(list(
column_1 = 1:120,
column_2 = structure(c(
1,2,3,4,5,6,7,8,
1,2,3,4,5,6,7,8,
1,2,3,4,5,6,7,8,
1,2,3,4,5,6,7,8,
1,2,3,4,5,6,7,8,
1,2,3,4,5,6,7,8,
1,2,3,4,5,6,7,8,
1,2,3,4,5,6,7,8,
1,2,3,4,5,6,7,8,
1,2,3,4,5,6,7,8,
1,2,3,4,5,6,7,8,
1,2,3,4,5,6,7,8,
1,2,3,4,5,6,7,8,
1,2,3,4,5,6,7,8,
1,2,3,4,5,6,7,8), .Label = c("Unstimulated", "ESAT6",
"CFP10", "Rv3615c",
"Rv2654", "Rv3879", "Rv3873", "PHA"), class = "factor"),
column_3 = c(
192.0519108,183.6403531,53.46798757
<tel:53.46798757>,83.__60638077,69.60749873,159.__4706861,256.8765622
<tel:256.8765622>,499.__2899303,
2170.799076,1411.349719,2759.__472348,2098.973397
<tel:2098.973397>,2164.739515
<tel:2164.739515>,1288.676574,1611.__486543,6205.229575
<tel:6205.229575>,
870.7424981
<tel:870.7424981>,465.9967135,191.8962375,864.__0937485,2962.693675,1289.__259137,2418.651212,7345.__712517,
0,168.1198893,674.4342961,101.__1575401,47.81596237,0,0,1420.__793922,
142.6871331,5.466468742,291.__9564635,80.73914133
<tel:80.73914133>,73.02239621,64.__47806871,144.3543635,3167.__959757,
3164.748333
<tel:3164.748333>,1092.634557,28733.20269,1207.__87783,729.6090973,151.8706088,__241.2466141,9600.963594,
1411.718287,12569.96285,1143.__254476,6317.378481
<tel:6317.378481>,16542.27718,79.__68025792,1958.495138,7224.__503437,
208.4382941
<tel:208.4382941>,69.48609769,656.691151,0.__499017582,7114.910926,187.__6296174,41.73980805
<tel:41.73980805>,8930.__784541,
4.276752185,0.432300363,60.89228665
<tel:60.89228665>,1.__103924786,0.490686366,1.__812993239,7.264531581,1518.__610307,
2172.051528
<tel:2172.051528>,595.8513744,17141.84336,589.__6565971,1340.287628,117.__350942,593.7034054,24043.__61463,
0,81.83292179
<tel:81.83292179>,1539.864321,36.41722958,8.__385131047,161.7647376,65.__21615696,7265.573875,
97.84753179
<tel:97.84753179>,154.051827,0.613835842,10.__06138851,45.04879285
<tel:45.04879285>,176.8284258,18795.__75462,3067686.769
<tel:3067686.769>,
5780.34957,944.2200834,2398.235596
<tel:2398.235596>,1083.__393165,2541.714557,1251.__670895,1547.178549,1792.__679176,
3067.988416 <tel:3067.988416>,8117.210173,23676.02226
<tel:23676.02226>,8251.937547,__17360.80494,18563.61561,16941.__865,31453.96708
<tel:31453.96708>,
2767.493803 <tel:2767.493803>,4796.33016,12292.93705,3864.657567
<tel:3864.657567>,9380.__673835,14886.44683,8457.88646,__26050.47191
<tel:26050.47191>)),
.Names = c("row", "stimulation", "copy"), row.names = c(NA, -120L),
class = "data.frame")
attach(my.data)
AVG<-aggregate(copy ~ stimulation , my.data, mean, na.rm = T)
SD<-aggregate(copy ~ stimulation , my.data, sd, na.rm = T)
# ??? question: AVG-SD and AVG + SD ???
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