How can subset a dataframe by nrow and groups in r? - r

Question

I have a dataframe that contains 240,000 obs. of 7 variables. In the dataframe there are 100 groups of 2400 records each, by Symbol. Example:
Complete DataFrame
I want to split this dataframe in new dataframe that contains every first observation and each 240 observation. The new dataframe will be 1000 obs of 7 variables:
New DataFrame
I tried df[seq(1, nrow(df), 240), ] but the new dataframe has each 240 observation and not distinguished by group (Symbol). I mean, I want a new dataframe that contains the rows 240, 480, 720, 960, and so on, for each symbol. In the original data frame every symbol has 2400 obs thus the new dataframe will have 10 obs by group.

Answer 1

Since we don't have your data, we can use an R database: iris. In this example we split iris by Species and select first n rows using head, in this example I set n=5 to extract first 5 rows by Species
> split_data <- lapply(split(iris, iris$Species), head, n=5)
> do.call(rbind, split_data)
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
setosa.1 5.1 3.5 1.4 0.2 setosa
setosa.2 4.9 3.0 1.4 0.2 setosa
setosa.3 4.7 3.2 1.3 0.2 setosa
setosa.4 4.6 3.1 1.5 0.2 setosa
setosa.5 5.0 3.6 1.4 0.2 setosa
versicolor.51 7.0 3.2 4.7 1.4 versicolor
versicolor.52 6.4 3.2 4.5 1.5 versicolor
versicolor.53 6.9 3.1 4.9 1.5 versicolor
versicolor.54 5.5 2.3 4.0 1.3 versicolor
versicolor.55 6.5 2.8 4.6 1.5 versicolor
virginica.101 6.3 3.3 6.0 2.5 virginica
virginica.102 5.8 2.7 5.1 1.9 virginica
virginica.103 7.1 3.0 5.9 2.1 virginica
virginica.104 6.3 2.9 5.6 1.8 virginica
virginica.105 6.5 3.0 5.8 2.2 virginica
>
Update
Given your comment, try this using your data.frame:
ind <- seq(from=240, to=240000, by=240) # a row index of length = 1000
split_data <- lapply(split(yourData, yourData$Symbol), function(x) x[ind,] )
do.call(rbind, split_data)

Answer 2

Here is one way using base R.
just like in the answer by user #Jilber Urbina I will give an example use with the built-in dataset iris.
fun <- function(DF, n = 240, start = n){
DF[seq(start, NROW(DF), by = n), ]
}
res <- lapply(split(iris, iris$Species), fun, n = 24)
res <- do.call(rbind, res)
row.names(res) <- NULL
res
# Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#1 5.1 3.3 1.7 0.5 setosa
#2 4.6 3.2 1.4 0.2 setosa
#3 6.1 2.8 4.7 1.2 versicolor
#4 6.2 2.9 4.3 1.3 versicolor
#5 6.3 2.7 4.9 1.8 virginica
#6 6.5 3.0 5.2 2.0 virginica
This can be made into a function, I named selectStepN.
#
# x - dataset to subset
# f - a factor, split criterion
# n - the step
#
selectStepN <- function(x, f, n = 240, start = n){
fun <- function(DF, n){
DF[seq(start, NROW(DF), by = n), ]
}
res <- lapply(split(x, f), fun, n = n)
res <- do.call(rbind, res)
row.names(res) <- NULL
res
}
selectStepN(iris, iris$Species, 24)
# Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#1 5.1 3.3 1.7 0.5 setosa
#2 4.6 3.2 1.4 0.2 setosa
#3 6.1 2.8 4.7 1.2 versicolor
#4 6.2 2.9 4.3 1.3 versicolor
#5 6.3 2.7 4.9 1.8 virginica
#6 6.5 3.0 5.2 2.0 virginica