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Mean and standard deviation by groups

I have a data frame something like this:

obs1 obs2 obs3 obs4 obs5
4     6    7     3    0
7     2    4     5    0
2     5    7     8    1
5     8    6     9    1
6     0    3     6    1
7     1    2     4    1

I want to compute the mean and standard deviation for obs 1 to 4 conditioned on obs5 and put it in a table format. The columns headings should be means and standard deviation for each of whether the obs5 is "0" or "1". Thus in this case the table will be of 4 by 4 type.

I tried

table <- aggregate( .~ obs5, DF, function(x) c(mean = mean(x), sd = sd(x)))

and am not sure what to do further to get proper format.

We could use data.table . We convert the 'data.frame' to 'data.table' ( setDT(df1) ), reshape it from 'wide' to 'long' format and then reshape it back to 'wide' format with dcast . The dcast from data.table can take multiple fun.aggregate .

library(data.table)#v1.9.6+
DT <- melt(setDT(df1), id.var='obs5', variable.name='Obs')
dcast(DT, Obs~obs5, value.var='value', fun.aggregate=c(mean, sd))

#    Obs value_mean_0 value_mean_1 value_sd_0 value_sd_1
#1: obs1          5.5         5.00   2.121320   2.160247
#2: obs2          4.0         3.50   2.828427   3.696846
#3: obs3          5.5         4.50   2.121320   2.380476
#4: obs4          4.0         6.75   1.414214   2.217356

You can calculate the means and standard deviations separately then combine the results together:

means <- aggregate( .~ obs5, DF, mean)
rownames(means) <- paste("mean", means$obs5)
sds <- aggregate( .~ obs5, DF, sd)
rownames(sds) <- paste("sd", means$obs5)

tab <- rbind(means, sds)
tab <- tab[, -1]
tab <- t(tab)

Result:

     mean 0 mean 1     sd 0     sd 1
obs1    5.5   5.00 2.121320 2.160247
obs2    4.0   3.50 2.828427 3.696846
obs3    5.5   4.50 2.121320 2.380476
obs4    4.0   6.75 1.414214 2.217356

a bit long-winded but produces output in correct format:

DF <- data.frame(obs1 = c(4, 7, 2, 5, 6, 7), obs2 = c(6, 2, 5, 8, 0, 1), obs3 = c(7, 4, 7, 6, 3, 2), obs4 = c(3, 5, 8, 9, 6, 4), obs5 = c(0, 0, 1, 1, 1, 1))

res <- by(DF[, -5], DF$obs5, FUN = function(x) rbind(colMeans(x), sqrt(diag(var(x)))))
res <- do.call(rbind, res)
rownames(res) <- paste(rep(c('mean', 'sd'), 2), rep(c(0, 1), c(2, 2)), sep = ".")
t(res)

#     mean.0     sd.0 mean.1     sd.1
#obs1    5.5 2.121320   5.00 2.160247
#obs2    4.0 2.828427   3.50 3.696846
#obs3    5.5 2.121320   4.50 2.380476
#obs4    4.0 1.414214   6.75 2.217356

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