Replacing Values in a Frame¶

> library(h2o)
> h2o.init()

#Upload the iris dataset
> path <- "http://h2o-public-test-data.s3.amazonaws.com/smalldata/iris/iris_wheader.csv""
> df <- h2o.importFile(path)

#Replace a single numerical datum. Note that columns and rows start at 0,
#so in the example below, the value in the 15th row and 3rd column will be set to 2.0.
> df[14,2] <- 2.0

#Replace a whole column. The example below multiplies all values in the second column by 3.
> df[,1] <- 3*df[,1]

#Replace by row mask. The example below searches for value less than 4.4 in the
#sepal_len column and replaces those values with 4.6.
> df[df[,”sepal_len”] < 4.6, “sepal_len”] <- 4.6

#Replace using ifelse. Similar to the previous example,
#this replaces values less than 4.6 with 4.6.
> df[,”sepal_len”] <- h2o.ifelse(df[,”sepal_len”] < 4.4, 4.6, df[,”sepal_len”])

#Replace missing values with 0
> df[is.na(df[,”sepal_len”]), “sepal_len”] <- 0

#Alternative with ifelse
> df[,”sepal_len”] <- h2o.ifelse(is.na(df[,”sepal_len”]), 0, df[,”sepal_len”]