| Title: | Databases Used Routinely by the Brazilian Jurimetrics Association | 
| Version: | 1.1.2 | 
| Description: | The Brazilian Jurimetrics Association (ABJ in Portuguese, see https://abj.org.br/ for more information) is a non-profit organization which aims to investigate and promote the use of statistics and probability in the study of Law and its institutions. This package has a set of datasets commonly used in our book. | 
| Depends: | R (≥ 3.3.1) | 
| License: | MIT + file LICENSE | 
| Encoding: | UTF-8 | 
| LazyData: | true | 
| URL: | https://abjur.github.io/abjData/ | 
| RoxygenNote: | 7.2.0 | 
| LazyDataCompression: | xz | 
| NeedsCompilation: | no | 
| Packaged: | 2022-06-14 00:23:12 UTC; julio | 
| Author: | Julio Trecenti | 
| Maintainer: | Julio Trecenti <julio.trecenti@gmail.com> | 
| Repository: | CRAN | 
| Date/Publication: | 2022-06-15 07:20:05 UTC | 
Case types
Description
A dataset contains information about case types in Brazil.
Usage
assuntos
Format
a data frame with 37022 lines and 15 variables.
- tribunal
- indicates which court is concerned 
- ano
- subject year 
- assunto_nome1
- first branch 
- assunto_nome2
- second branch 
- assunto_nome3
- third branch 
- assunto_nome4
- fourth branch 
- assunto_nome5
- fifth branch 
- assunto_nome6
- sixth branch 
- generico
- generic code 
- codigo
- code related to the subject 
- x1_grau
- number of cases in first instance 
- x2_grau
- number of cases in second instance 
- juizado_especial
- number of cases in the special court 
- turma_recursal
- number of cases in the special class 
- total
- total cases 
Source
Examples
summary(assuntos)
Municipality info (legacy)
Description
A dataset containing the municipality codes. The database is outdated, as it does not consider all municipalities.
Usage
cadmun
Format
a data frame with 5657 rows and 35 variables:
- description
- set of codes of the municipalities and their situation, containing information about border, Amazon, capital, longitude, latitude, among others 
Source
IBGE
Examples
summary(cadmun)
Consumer cases
Description
Retrospective basis to use in book examples.
Usage
consumo
Format
a data frame with 1000 rows and 9 columns.
- id_processo
- case identifier number (appeal) 
- assunto
- type of the case 
- comarca
- municipality of the case 
- valor
- value of cause 
- tipo_litigio
- configuration of the parties to the dispute 
- dec_val
- second instance decision 
- dec_unanime
- unanimity 
- dec_date
- decision date 
- tempo
- case time in days 
Source
Examples
summary(consumo)
Auctions
Description
Auctions sample dataset used in our book.
Usage
leiloes
Format
a data frame with 1000 rows and 10 columns.
- id_processo
- case identifier number 
- descricao
- item description 
- id_leiloeiro
- Auctioneer ID 
- tipo_remuneracao
- Auctioneer compensation type 
- modalidade
- auction mode 
- tipo
- auction type 
- data_edital
- auction date 
- vendeu
- was the item sold? 
- valor_avaliacao_inicial
- appraised value 
- valor_total_arrematado
- auctioned value 
Source
Examples
summary(leiloes)
Municipality info
Description
A dataset containing useful data for joining with city datasets, such as city codes, acronyms of the federative units and regions.
Usage
muni
Format
a data frame with 5572 rows and 17 columns:
- muni_id
- IBGE code (7 digits) 
- muni_id_6
- IBGE code (6 digits) 
- muni_nm
- Municipality name (original IBGE) 
- muni_nm_clean
- Clean municipality name (without accents, upper case) 
- uf_nm
- Name of the original federative unit 
- uf_sigla
- Federative unit initials 
- uf_id
- code of IBGE federative unit 
- regiao_nm
- region name 
- tse_id
- municipality TSE code 
- rf_id
- Brazilian Federal Revenue code of the municipality 
- bcb_id
- Central Bank of Brazil code of the municipality 
- existia_1991
- 1 if municipality existed in 1991, 0 otherwise 
- existia_2000
- 1 if municipality existed in 2000, 0 otherwise 
- existia_2010
- 1 if municipality existed in 2010, 0 otherwise 
- lon
- longitude based on shapefile centroid 
- lat
- latitude based on shapefile centroid 
- capital
- TRUE if federative unit is a capital, FALSE otherwise 
Source
Municipalities dataset enriched with external data.
Examples
summary(muni)
UNDP minimal dataset
Description
A dataset that contains UNDP information for municipalities by years.
Usage
pnud_min
Format
a data frame with 16686 rows and 15 columns.
- ano
- for more information, check - pnud_siglas
Source
Examples
summary(pnud_min)
UNDP data by Municipality
Description
A dataset that contains information about UNDP for municipalities and federative units.
Usage
pnud_muni
Format
a data frame with 16695 rows and 124 columns.
Considered the year municipality observational unit.
- id
- for more information, check - pnud_siglas
Source
summary(pnud_muni)
UNDP Acronyms
Description
A dataset that serves as a glossary of available variables.
Usage
pnud_siglas
Format
a data frame with 236 rows e 4 columns:
- sigla
- all acronyms available 
- nome_curto
- short name of the variable 
- nome_longo
- long name of the variable 
- definicao
- definition of acronym 
Source
Examples
summary(pnud_siglas)
UNDP data by Federative Units
Description
A dataset that contains information about UNDP of Federative Units.
Usage
pnud_uf
Format
a data frame with 81 rows e 235 columns.
- ano
- for more information, check - pnud_siglas
Source
https://www.br.undp.org/content/brazil/pt/home/idh0/rankings/idhm-uf-2010.html
Examples
summary(pnud_uf)