README.md

In aassumpcao/CJIL: Produces the Analysis For the CJIL's Code Sample

Code Sample for the Criminal Justice Innovation Lab @ UNC Chapel Hill

Author: Andre Assumpcao

Email: [e-mail]

Description

This script executes the functions in R package CJIL, which I have created as a code sample for the Criminal Justice Innovation Lab @ UNC. The package visits and downloads data from the NC Courts and NC demography APIs, processes them and executes a simple analysis of the data. I believe this is a clean and new way of conveying research results to the public.

Instructions

You should just execute the following code snippet on a R Session.

# make sure you have devtools installed.
if (!require(devtools)) {install.packages('devtools')}

# install the CJIL from github
devtools::install_github('aassumpcao/CJIL')

# there you go. you can use all functions in the package.
# download the data
data <- CJIL::data_download()

# process the data
data_cleaned <- CJIL::data_process(data)

# produce the analysis and store table
table <- CJIL::data_analyze(data_cleaned)

# output the table
print(table)

Each function

CJIL::data_download() visits two NC goverment APIs and downloads data (NC Courts and the Office of State Budget and Management). They are returned as a tibble dataset.

CJIL::data_process() cleans up the data. It renames variables, transform scales and returns the new dataset.

CJIL::data_process() produces three simple analyses: a) it saves a graph of the evoluation of the type of criminal cases in North Carolina; b) it oureturns the tputs regression coefficients for a simple correlation between log(population) and number_of_cases; c) it saves the regression line from b).

Others

Please feel free to email me @ [e-mail] for further clarification.

aassumpcao/CJIL documentation built on Feb. 25, 2021, 2:04 p.m.