filter_num: Filter data by levels of numeric variables

In iNZightTools: Tools for 'iNZight'

Filter data by levels of numeric variables

Description

This function filters a dataframe or survey design object by applying a specified boolean condition to one of its numeric variables. The resulting filtered dataframe is returned, along with the tidyverse code used to generate it.

Usage

filter_num(data, var, op = c("<=", "<", ">=", ">", "==", "!="), num)

Arguments

data	A dataframe or survey design object to be filtered.
var	The name of the column in data to be filtered by.
op	A logical operator to apply for the filtering condition. Valid options are: "<=", "<", ">=", ">", "==", or "!=".
num	The numeric value for which the specified op is applied.

Value

A filtered dataframe with the tidyverse code attached.

Author(s)

Owen Jin, Tom Elliott, Zhaoming Su

See Also

code

Examples

filtered <- filter_num(iris, var = "Sepal.Length", op = "<=", num = 5)
cat(code(filtered))
head(filtered)

library(survey)
data(api)
svy <- svydesign(~ dnum + snum,
    weights = ~pw, fpc = ~ fpc1 + fpc2,
    data = apiclus2
)
svy_filtered <- filter_num(svy, var = "api00", op = "<", num = 700)
cat(code(svy_filtered))

iNZightTools documentation built on Oct. 12, 2023, 5:06 p.m.