get_jobsector_rac: get_jobsector_rac

In patrickballantyne/tidylodes: tidylodes: A package for extracting, processing and 'spatialising' data from the US Census Bureau's LODES database

Description

This function allows users to subset the output dataframe of get_wac_data to focus on one specific job sector. This will be useful for those using RAC data to perform analysis on the geography of specific job types.

Usage

get_jobsector_rac(df, job_code, job_proportion = T)

Arguments

df	The input for this function is the output dataframe from get_rac_data.
job_code	Here the user can select a specific job code from the output dataframe of get_rac_data, which enables the function to drop all other job sectors, but keep total jobs and the chosen job sector. Users should use colnames(df) to obtain a list of all available job codes.
job_proportion	This argument enables users to calculate the proportion of the chosen job sector in relation to the total number of jobs in each census block. By default the argument is 'T', so will calculate a job_proportion column unless set to 'F'.

Value

A dataframe of cleaned RAC data, focusing on a specific job sector. If job_proportion = T then the dataframe will also contain an additional column where the proportion of total jobs that the chosen job sector occupies is calculated.

Author(s)

Ballantyne, Patrick

References

LODES data available to download manually from: https://lehd.ces.census.gov/data/lodes/LODES7/

Examples

## Users need to use the get_rac_data function first:
df <- get_rac_data("nj", "2008")
## Get a list of all available job sectors
colnames(df)

## Use the get_jobsector_rac function to extract retail trade jobs, and calculate the proportion of retail trade jobs
df2 <- get_jobsector_rac(df, job_code = "Retail_Trade", job_proportion = T)

patrickballantyne/tidylodes documentation built on June 1, 2020, 1:12 p.m.