This question builds from the SO post found here and uses code that was modified from a post on the R-help mailing list which can be seen here
I am trying to extract a random sample of rows in a data frame but with a conditional. Using the R iris
data which looks like:
> head(iris)
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1 5.1 3.5 1.4 0.2 setosa
2 4.9 3.0 1.4 0.2 setosa
3 4.7 3.2 1.3 0.2 setosa
4 4.6 3.1 1.5 0.2 setosa
5 5.0 3.6 1.4 0.2 setosa
6 5.4 3.9 1.7 0.4 setosa
To take a simple random sample, the code below works fine to take a sample of 2 rows.
iris[sample(nrow(iris), 2), ]
However I am unsure how to condition the Species field. For example how to take the random sample as indicated above but only when Species != “setosa”
There are three categories of iris$Species
> summary(iris$Species)
setosa versicolor virginica
50 50 50
I am unsure how to correctly nest conditionals. One of my earlier attempts is below with the obviously incorrect results included….
> iris[sample(nrow(iris)[iris$Species != "setosa"], 2), ]
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
NA NA NA NA NA <NA>
NA.1 NA NA NA NA <NA>
Thanks
sample_n() function in R Language is used to take random sample specimens from a data frame.
Solution. To remove rows at random without shuffling in Pandas DataFrame: Get an array of randomly selected row index labels. Use the drop(~) method to remove the rows.
I'd use which
to get the vector of rows numbers from which you can sample
given your condition....
iris[ sample( which( iris$Species != "setosa" ) , 2 ) , ]
# Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#59 6.6 2.9 4.6 1.3 versicolor
#133 6.4 2.8 5.6 2.2 virginica
With dplyr:
library(dplyr)
set.seed(12)
filter(iris, Species != "setosa") %>% sample_n(., 2)
Output:
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
7 6.3 3.3 4.7 1.6 versicolor
81 7.4 2.8 6.1 1.9 virginica
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