Now suppose that we want to filter the data table to only show the entries for which the murder rate is lower than 0.71. To do this we use the filter function, which takes the data table as the first argument and then the conditional statement as the second. Like mutate, we can use the unquoted variable names from murders inside the function and it will know we mean the columns and not objects in the workspace.
filter(murders, rate <= 0.71)
#> state abb region population total rate
#> 1 Hawaii HI West 1360301 7 0.515
#> 2 Iowa IA North Central 3046355 21 0.689
#> 3 New Hampshire NH Northeast 1316470 5 0.380
#> 4 North Dakota ND North Central 672591 4 0.595
#> 5 Vermont VT Northeast 625741 2 0.320Run the sample code to see how filter() function works.
library(dplyr)
library(dslabs)
data("murders")
# Add the rate column
murders <- mutate(murders, rate = total / population * 100000)
# Check murders to find that the new column is added.
head(murders)
# select the data under condition rate <= 0.71
filter(murders, rate <= 0.71)