extract_salary {priceR}

Extract numeric salary from text data

Description

Extract numeric salary from text data. 'extract_salary' automatically converts weekly and hourly rates to amounts per annum.

Usage

extract_salary(salary_text, exclude_below, exclude_above, salary_range_handling,
include_periodicity, hours_per_workday, days_per_workweek, working_weeks_per_year)

Arguments

salary_text

A character string, or vector of character strings.

exclude_below

A lower bound. Anything lower than this number will be replaced with NA.

exclude_above

An upper bound. Anything above this number will be replaced with NA.

salary_range_handling

A method of handling salary ranges. Defaults to returning an average of the range; can also be set to "max" or "min".

include_periodicity

Set to TRUE to return an additional column stating the detected peridicity in the character string. Periodicity is assumed to be 'Annual' unless evidence is found to the contrary.

hours_per_workday

Set assumed number of hours in the workday. Only affects annualisation of rates indentified as Daily. Default is 8 hours.

days_per_workweek

Set assumed number of days per workweek. Only affects annualisation of rates indentified as Daily. Default is 5 days.

working_weeks_per_year

Set assumed number of working weeks in the year. Only affects annualisation of rates indentified as Daily or Weekly. Default is 50 weeks.

Value

A data.frame of 1 column, or 2 columns if include_periodicity is set to TRUE

Examples

# Provide a salary string and 'extract_salary' and will extract the salary and return it
extract_salary("$160,000 per annum")
# 160000


# If a range is present, the average will be taken by default
extract_salary("$160,000 - $180000.00 per annum")
# 170000


# Take the 'min' or 'max' of a salary range by setting salary_range_handling parameter accordingly
extract_salary("$160,000 - $180000.00 per annum", salary_range_handling = "min")
# 160000


# Extract salaries from character string(s)
annual_salaries <- c("$160,000 - $180000.00 per annum",
                     "$160000.00 - $180000.00 per annum",
                     "$145000 - $155000.00 per annum",
                     "$70000.00 - $90000 per annum",
                     "$70000.00 - $90000.00 per annum plus 15.4% super",
                     "$80000.00 per annum plus 15.4% super",
                     "60,000 - 80,000",
                     "$78,686 to $89,463 pa, plus 15.4% superannuation",
                     "80k - 100k")

extract_salary(annual_salaries)
# 170000 170000 150000  80000  53338  40008  70000  56055  90000
# Note the fifth, sixth, and eighth elements are averages including '15' (undesirable)
# Using exclude_below parameter avoids this (see below)

# Automatically detect, extract, and annualise daily rates
daily_rates <- c("$200 daily", "$400 - $600 per day", "Day rate negotiable dependent on experience")
extract_salary(daily_rates)
# 48000 120000     NA


# Automatically detect, extract, and annualise hourly rates
hourly_rates <- c("$80 - $100+ per hour", "APS6/EL1 hourly rate contract")
extract_salary(hourly_rates)
# 172800   6720
# Note 6720 is undesirable. Setting the exclude_below and exclude_above sensibly avoids this


salaries <- c(annual_salaries, daily_rates, hourly_rates)


# Setting lower and upper bounds provides a catch-all to remove unrealistic results
# Out of bounds values will be converted to NA
extract_salary(salaries, exclude_below = 20000, exclude_above = 600000)
# 170000 170000 150000  80000  80000  80000  70000  84074  90000  48000 120000     NA 172800     NA


# extract_salary automatically annualises hourly and daily rates
# It does so by making assumptions about the number of working weeks in a year,
# days per workweek, and hours per workday
# And the assumed number of hours per workday can be changed from the default (8)
# The assumed number of workdays per workweek can be changed from the default (5)
# The assumed number of working weeks in year can be changed from the default (50)
# E.g.
extract_salary(salaries, hours_per_workday = 7, days_per_workweek = 4,
               working_weeks_per_year = 46, exclude_below = 20000)
# 170000 170000 150000  80000  53338  40008  70000  56055  90000  36800  92000     NA 115920     NA


# To see which salaries were detected as hourly or weekly, set include_periodicity to TRUE
extract_salary(salaries, include_periodicity = TRUE, exclude_below = 20000)

# salary periodicity
# 1  170000      Annual
# 2  170000      Annual
# 3  150000      Annual
# 4   80000      Annual
# 5   80000      Annual
# 6   80000      Annual
# 7   70000      Annual
# 8   84074      Annual
# 9   90000      Annual
# 10  48000       Daily
# 11 120000       Daily
# 12     NA       Daily
# 13 172800      Hourly
# 14     NA      Hourly