Slicing Columns¶
H2O lazily slices out columns of data and will only materialize a shared copy upon some type of triggering IO. This example shows how to slice columns from a frame of data.
- r
- python
> library(h2o)
> h2o.init()
> path <- "http://h2o-public-test-data.s3.amazonaws.com/smalldata/iris/iris_wheader.csv"
> df <- h2o.importFile(path)
> print(df)
sepal_len sepal_wid petal_len petal_wid class
1 5.1 3.5 1.4 0.2 Iris-setosa
2 4.9 3.0 1.4 0.2 Iris-setosa
3 4.7 3.2 1.3 0.2 Iris-setosa
4 4.6 3.1 1.5 0.2 Iris-setosa
5 5.0 3.6 1.4 0.2 Iris-setosa
6 5.4 3.9 1.7 0.4 Iris-setosa
[150 rows x 5 columns]
# slice 1 column by index
> c1 <- df[,1]
> print(c1)
sepal_len
1 5.1
2 4.9
3 4.7
4 4.6
5 5.0
6 5.4
[150 rows x 1 column]
# slice 1 column by name
> c1_1 <- df[, "petal_len"]
> print(c1_1)
petal_len
1 1.4
2 1.4
3 1.3
4 1.5
5 1.4
6 1.7
[150 rows x 1 column]
# slice cols by vector of indexes
> cols <- df[, 1:4]
> print(cols)
sepal_len sepal_wid petal_len petal_wid
1 5.1 3.5 1.4 0.2
2 4.9 3.0 1.4 0.2
3 4.7 3.2 1.3 0.2
4 4.6 3.1 1.5 0.2
5 5.0 3.6 1.4 0.2
6 5.4 3.9 1.7 0.4
[150 rows x 4 columns]
# slice cols by vector of names
> cols_1 <- df[, c("sepal_len", "sepal_wid", "petal_len", "petal_wid")]
> print(cols_1
sepal_len sepal_wid petal_len petal_wid
1 5.1 3.5 1.4 0.2
2 4.9 3.0 1.4 0.2
3 4.7 3.2 1.3 0.2
4 4.6 3.1 1.5 0.2
5 5.0 3.6 1.4 0.2
6 5.4 3.9 1.7 0.4
[150 rows x 4 columns]