Function reference • salic

Overview Summary of core functions and sample data
`salic`	salic: Prepare Agency Dashboard Data
`data_salic`	Salic Sample Data Overview
Sample Data Example of state agency data
`cust`	Sample Standardized Data: 30,000 Customers
`lic`	Sample Standardized Data: License Types
`sale`	Sample Standardized Data: Sales 2008 thru 2018
`history`	Sample Data: License History
`metrics`	Sample Data: Dashboard Metrics
`dashboard`	Sample Data: Metrics formatted for Dashboard Input
Data Formattting Functions to check formatting guidelines for standardized data
`data_check()`	Check standardized data (cust, lic, sale) formatting rules
`data_check_table()` `data_check_cust()` `data_check_lic()` `data_check_sale()`	Check formatting rules for standardized data tables
`data_foreign_key()`	Check key coverage between two tables
License History Functions to create a license history from standardized data
`rank_sale()`	Filter sales to 1 row per customer per year.
`make_history()`	Make license history table
`history_check_sample()` `history_check_R3()` `history_check_lapse()`	Checking license history
Dashboard Metrics Functions to summarize dashboard metrics from license history
`est_part()` `est_recruit()`	Estimate participants by year from license history
`scaleup_part()` `scaleup_recruit()`	Scale segmented participation counts to total (if needed)
`est_churn()`	Estimate churn by year from license history
`format_result()`	Format estimated metrics for input to Dashboard
Category Variables Functions for coding and labelling category variables
`recode_agecat()`	Create age category based on year (of sale) and birth year
`label_categories()`	Convert multiple numeric variables to factors
`df_factor_var()` `df_factor_sex()` `df_factor_res()` `df_factor_R3()` `df_factor_age()`	Convert numeric to factor in data frame and check
`factor_var()` `factor_age()` `factor_sex()` `factor_res()` `factor_R3()`	Convert numeric variable to factor
Southwick Processing Functions/Data for Southwick-specific data preparation
`check_dups()`	Check for duplicates in a table
`count_lines_textfile()`	Count rows in a text file
`recode_month()`	Standardize month (for individual state dashboards)
`recode_state()`	Recode state abbreviations
`summary_churn()`	Summarize churn by year
`summary_initial()`	Summarize sales, customers, and churn by year
`summary_sale()`	Summarize sales and customers by year
`state_abbreviations`	Data: State/Province/Territory Abbreviations for US & Canada

Reference

Overview

Sample Data

Data Formattting

License History

Dashboard Metrics

Category Variables

Southwick Processing

Contents