英文:
Randomly selecting 50 columns in R data table results in table with only 50 rows. How can I fix this?
问题
我正在尝试在R中随机选择数据表中的50列（原始表格有110列和1000+行）。但是当我运行代码时，生成的表格只有50行（我不是试图筛选行，只是列）。
randomTable = sample_n(ogTable, 50, axis = 'columns')
我查找了这个问题，似乎这个函数如果超过了结果列的数量，就不会显示所有行，但我找不到解决方法。
英文:
I'm trying to randomly select 50 columns in a data table in R (the original table has 110 columns and 1000+ rows). But when I run the code, the resulting table only has 50 rows (I am not trying to filter out the rows, only the columns).
randomTable = sample_n(ogTable, 50, axis = 'columns')
I looked up this issue and it seems like this function doesn't display all rows if it exceeds the number of resulting columns, but I could not find a way to get around this.
答案1
得分: 0
更新后的解释：
library(dplyr)set.seed(42)# 从mtcars中随机选择3列，保持前两列不变selected_columns <- sample(colnames(mtcars)[-c(1, 2)], 3)# 使用`all_of()`函数将常数列与随机选择的列组合在一起mtcars %>%select(mpg, cyl, all_of(selected_columns))
第一个回答：
使用dplyr中的sample_n来随机抽取行（例如，观测值）。请参考?sample_n：sample_n() 和 sample_frac() 已被slice_sample()取代。
要随机选择50列，我们可以这样做：
randomTable <- ogTable[, sample(ncol(ogTable), 50)]
英文:
Update after clarification:
library(dplyr)set.seed(42)# Select 3 columns from mtcars randomly keeping the first two constantselected_columns <- sample(colnames(mtcars)[-c(1, 2)], 3)# Now combine the constant columns with the randomly select using `all_of()` functionmtcars %>%select(mpg, cyl, all_of(selected_columns))
first answer:
sample_n from dplyr is used for sampling rows (e.g. observations). See ?sample_n: sample_n() and sample_frac() have been superseded in favour of slice_sample().
We could do it this way to randomly select 50 columns:
randomTable <- ogTable[, sample(ncol(ogTable), 50)]
答案2
得分: 0
这个一行代码有效：
randomTable <- ogTable[, c(1:2, sample(3:ncol(ogTable), 50)), with = FALSE]
一个 reprex：
library(data.table)set.seed(1)test <- data.table(iris)randomTable <- test[, c(1:2, sample(3:ncol(test), 2)), with = FALSE]head(randomTable)Sepal.Length Sepal.Width Petal.Length Petal.Width1 5.1 3.5 1.4 0.22 4.9 3.0 1.4 0.23 4.7 3.2 1.3 0.24 4.6 3.1 1.5 0.25 5.0 3.6 1.4 0.26 5.4 3.9 1.7 0.4
英文:
This one-liner works:
randomTable <- ogTable[, c(1:2, sample(3:ncol(ogTable), 50)), with = FALSE]
A reprex:
library(data.table)set.seed(1)test <- data.table(iris)randomTable <- test[, c(1:2, sample(3:ncol(test), 2)), with = FALSE]head(randomTable)Sepal.Length Sepal.Width Petal.Length Petal.Width1 5.1 3.5 1.4 0.22 4.9 3.0 1.4 0.23 4.7 3.2 1.3 0.24 4.6 3.1 1.5 0.25 5.0 3.6 1.4 0.26 5.4 3.9 1.7 0.4
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