i have a data.frame consisting of character columns and numeric columns. Now I would like to calculate the mean of the numeric columns and append the results to the end of the dataframe.
class1 1 2 5
class2 2 3 6
class3 2 3 2
to
class1 1 2 1
class2 2 3 6
class3 2 3 2
mean 1.6 2.6 3
I tried so with colMeans, but this conflicts with the character column and I get the following error:
Error in colMeans(data, na.rm = FALSE) : 'x' must be numeric
I also tried to restrict colMeans to parts of the data.frame with data[2:4], but then I struggle to append the string, as it doesn't have the same length as the original data.frame.
Thanks for your help.
I agree with the above comment that sticking them at the end of your data frame doesn't seem like a good idea.
Anyway, you could take this opportunity to expand your R-pertoire with rapply
str(iris)
# 'data.frame': 150 obs. of 5 variables:
# $ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
# $ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
# $ Petal.Length: num 1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
# $ Petal.Width : num 0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
# $ Species : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...
summary(iris)
# Sepal.Length Sepal.Width Petal.Length Petal.Width Species
# Min. :4.300 Min. :2.000 Min. :1.000 Min. :0.100 setosa :50
# 1st Qu.:5.100 1st Qu.:2.800 1st Qu.:1.600 1st Qu.:0.300 versicolor:50
# Median :5.800 Median :3.000 Median :4.350 Median :1.300 virginica :50
# Mean :5.843 Mean :3.057 Mean :3.758 Mean :1.199
# 3rd Qu.:6.400 3rd Qu.:3.300 3rd Qu.:5.100 3rd Qu.:1.800
# Max. :7.900 Max. :4.400 Max. :6.900 Max. :2.500
rapply(iris, mean, classes = c('numeric','integer'))
# Sepal.Length Sepal.Width Petal.Length Petal.Width
# 5.843333 3.057333 3.758000 1.199333
But if you had to join them, you could do
tmp <- rapply(iris, mean, classes = c('numeric','integer'))
rbind(iris, tmp[match(names(iris), names(tmp))])
tail(rbind(iris, tmp[match(names(iris), names(tmp))]), 5)
# Sepal.Length Sepal.Width Petal.Length Petal.Width Species
# 147 6.300000 2.500000 5.000 1.900000 virginica
# 148 6.500000 3.000000 5.200 2.000000 virginica
# 149 6.200000 3.400000 5.400 2.300000 virginica
# 150 5.900000 3.000000 5.100 1.800000 virginica
# 151 5.843333 3.057333 3.758 1.199333 <NA>
I regret coining R-pertoire already