| Type: | Package |
| Title: | IPEA Common Functions |
| Version: | 0.0.6 |
| Maintainer: | Gustavo Coelho <gustavo.coelho@ipea.gov.br> |
| Description: | The most used functions on IPEA (Instituto de Pesquisa Economica Aplicada). Most of functions deal with brazilian names. It can guess the women single's name, extract prepositions or extract the first name. |
| License: | GPL-3 |
| Encoding: | UTF-8 |
| LazyData: | true |
| RoxygenNote: | 6.0.1 |
| URL: | https://github.com/ipea/utilsIPEA |
| BugReports: | http://github.com/ipea/utilsIPEA/issues |
| Depends: | R (≥ 3.0) |
| Imports: | data.table, stringr, utils, stringdist, RCurl, dplyr |
| Suggests: | testthat, covr |
| NeedsCompilation: | no |
| Packaged: | 2018-04-20 19:37:25 UTC; B15599226 |
| Author: | Gustavo Coelho [aut, cre], Lucas Mation [aut], Daniel Lima [ctb], Igor Noberto [ctb], João Victor Machado [ctb] |
| Repository: | CRAN |
| Date/Publication: | 2018-04-20 19:51:54 UTC |
Abrevia o nome do meio.
Description
abrevia_nome_meio return names .
Usage
abrevia_nome_meio(base, ..., suffixo = "_abrev")
Arguments
base |
A data table, data frame or character vector. |
... |
columns for apply the function |
suffixo |
A character indicating the final part of the new columns' names |
Value
the base parameter with a new column.
Examples
base <- data.frame(nome = c("Carlos Pereira Neves", "Pedro Aparecido Anjos"))
base <- remove_preposicao_nomes(base, "nome")
Remove de da e dos of names .
Description
contar_letras return number of any letters on alphabet for each column.
Usage
contar_letras(base, columns, suffix = NULL)
Arguments
base |
A data table, data frame or character vector. |
columns |
for apply the function |
suffix |
Suffix name for the new column. |
Value
a data.table number of any letters on alphabet for each column
Examples
base <- data.frame(nome = c("João das Neves", "Pedro dos Anjos", "Maria das Gracas"))
base <- contar_letras(base, "nome")
Brazilian address
Description
Some addresses from Brazil
Usage
geocod_base
Format
A data frame with 5 rows and 12 variables:
- uf
state of Brazil
- MatchedAddress
Address returned from GALILEO
- cep
Zip code
- enderecofinal
Prompted Address
- Nome_Municipio
City names
ident_erros_munic_galileo Returns a new column called munmatch with true or false. This column identify where GALILEO failed
Description
ident_erros_munic_galileo Returns a new column called munmatch with true or false. This column identify where GALILEO failed
Usage
ident_erros_munic_galileo(base, mun, match, uf)
Arguments
base |
Data frame, data set with return from GALILEO |
mun |
character, the name of the municipio. |
match |
character, the column MatchAdress from GALILEO. |
uf |
character, the name of the state. |
Value
Returns a new column called munmatch with true or false.
Return women single's name
Description
nome_de_solteira Return women single's name using the husband last name.
Usage
nome_de_solteira(nome_casada, nome_conjuge)
Arguments
nome_casada |
Character, married woman's name |
nome_conjuge |
character, husband's name. |
Value
Returns a list of possible names
Examples
nome_de_solteira(nome_casada = "Maria Conceicao da Costa", nome_conjuge = "Mario Silva da Costa")
Remove de da e dos of names .
Description
remove_preposicao_nomes return names without de, da e dos.
Usage
remove_preposicao_nomes(base, ..., suffixo = "_semD")
Arguments
base |
A data table, data frame or character vector. |
... |
columns for apply the function |
suffixo |
Suffix name for the new column. |
Value
the base parameter with a new column.
Examples
base <- data.frame(nome = c("João das Neves", "Pedro dos Anjos", "Maria das Gracas"))
base <- remove_preposicao_nomes(base, "nome")