更简单的你可以使用colMeans
函数。这里有一个例子
> set.seed(001) # Generating some random data
> file1 <- data.frame(matrix(rnorm(50, 100, 5), ncol=5))
> file1 # this is how the artificial data.frame should look like
X1 X2 X3 X4 X5
1 96.86773 107.55891 104.59489 106.79340 99.17738
2 100.91822 101.94922 103.91068 99.48606 98.73319
3 95.82186 96.89380 100.37282 101.93836 103.48482
4 107.97640 88.92650 90.05324 99.73097 102.78332
5 101.64754 105.62465 103.09913 93.11470 96.55622
6 95.89766 99.77533 99.71936 97.92503 96.46252
7 102.43715 99.91905 99.22102 98.02855 101.82291
8 103.69162 104.71918 92.64624 99.70343 103.84266
9 102.87891 104.10611 97.60925 105.50013 99.43827
10 98.47306 102.96951 102.08971 103.81588 104.40554
> colMeans(file1) # this part computes the means for each column without a 'for' loop
X1 X2 X3 X4 X5
100.66101 101.24422 99.33163 100.60365 100.67068
看看?colMeans
如果你有非数字列可以autotically跳过它们使用sapply
内colMeans
例如:
set.seed(001) # Generating some random data
file1 <- data.frame(matrix(rnorm(50, 100, 5), ncol=5))
# Creating three columns with non-numeric data
factors <- data.frame(matrix(sample(letters, 30, TRUE), ncol=3))
file1 <- cbind(factors, file1) # this is your data.frame
colnames(file1) <- paste0('Col.', 1:ncol(file1)) # set some colnames
file1 # this is the data.frame to work with
> colMeans(file1[sapply(file1, is.numeric)])# colmeans for only those numeric cols
Col.4 Col.5 Col.6 Col.7 Col.8
100.65027 101.52467 102.04486 99.14944 100.23847
现在这个工作很好,但我在这里仍然有点问题。我的数据的前3列不是数字。 colMeans函数正在考虑所有列为数字,我可以排除前3个colmuns吗?还是我需要创建一个由数字组成的新文件?谢谢 – Error404
你先生,都很亲切:帽子: 非常感谢:) – Error404