df_factor_var: Convert numeric to factor in data frame and check

In southwick-associates/salic: Prepare Agency Dashboard Data

Description

These are convenience functions for license data, similar to factor_var but operate on data frames (useful for piping) and produce a check summary.

Usage

df_factor_var(df, var, levels, labels, suppress_check = TRUE, ...)

df_factor_sex(df, var = "sex", levels = 1:2, labels = c("Male",
  "Female"), ...)

df_factor_res(df, var = "res", levels = c(1, 0),
  labels = c("Resident", "Nonresident"), ...)

df_factor_R3(df, var = "R3", levels = 1:4, labels = c("Carry",
  "Renew", "Reactivate", "Recruit"), ...)

df_factor_age(df, var = "age", levels = 1:7, labels = c("0-17",
  "18-24", "25-34", "35-44", "45-54", "55-64", "65+"), ...)

Arguments

df	data frame: Input data frame
var	character: Name of numeric variable to convert
levels	numeric: Levels for input numeric vector
labels	labels: Labels to use for output factor vector
suppress_check	logical: If TRUE, does not print a coding summary
...	Other arguments passed to factor

See Also

Other functions for working with category variables: factor_var, label_categories, recode_agecat

Examples

library(dplyr)
data(history)
x <- history %>%
    df_factor_R3(suppress_check = FALSE) %>%
    df_factor_res(suppress_check = FALSE) %>%
    df_factor_sex(suppress_check = FALSE)

southwick-associates/salic documentation built on Nov. 5, 2019, 9:13 a.m.