seriesbr package

Submodules

seriesbr.bcb module

seriesbr.bcb.get_series(code: int, start: str = None, end: str = None, last_n: int = None) → pandas.core.frame.DataFrame[source]

Get multiple BCB time series.

Parameters:
  • code (int) – Series identifier.
  • start (str, optional) – Initial date.
  • end (str, optional) – Final date.
  • last_n (int, optional) – Number of last observations.
Returns:
Return type:

pandas.DataFrame
seriesbr.bcb.get_metadata(code: int) → dict[source]

Get a BCB time series metadata.

Parameters:code (str) – Time series’ code.
Returns:A DataFrame with metadata values.
Return type:pandas.DataFrame

Examples

>>> bcb.get_metadata(20786).head()
                                                                    values
referencias              <P><A href="http://www.bcb.gov.br/estatisticas...
license_title            Licença Aberta para Bases de Dados (ODbL) do O...
maintainer                  Banco Central do Brasil/Departamento Econômico
relationships_as_object                                                 []
vcge                     Política Econômica [http://vocab.e.gov.br/2011...

seriesbr.ibge module

seriesbr.ibge.get_series(table: int, variables: Union[int, str, List[int], List[str]] = None, start: str = None, end: str = None, last_n: int = None, locations: seriesbr.ibge.series.LocationsInput = None, classifications: Union[int, List[int], dict[Classification, Category]] = None) → pandas.core.frame.DataFrame[source]

Get an IBGE table

Parameters:
  • table (int) – Table code.
  • variables (int or list of ints, optional) – Variables codes.
  • start (int or str, optional) – Initial date, month or day first.
  • end (int or str, optional) – Final date, month or day first.
  • last_n (int or str, optional) – Return only last n observations.
  • municipalities (str, int, bool a list, optional) –
  • states (str, int, bool or a list, optional) –
  • macroregions (str, int, bool or a list, optional) –
  • microregions (str, int, bool or a list, optional) –
  • mesoregions (str, int, bool or a list, optional) –
  • classifications (dict, int, str or list, optional) –
Returns:

A DataFrame with series values and metadata.
Return type:

pandas.DataFrame

Examples

>>> ibge.get_series(1419, start="11-2019", end="11-2019")
            Nível Territorial                              Variável   Geral, grupo, subgrupo, item e subitem   Valor
Date
2019-11-01            Brasil                 IPCA - Variação mensal   Índice geral                              0.51
2019-11-01            Brasil       IPCA - Variação acumulada no ano   Índice geral                              3.12
2019-11-01            Brasil  IPCA - Variação acumulada em 12 meses   Índice geral                              3.27
2019-11-01            Brasil                     IPCA - Peso mensal   Índice geral                            100.00
seriesbr.ibge.get_metadata(table: int) → dict[source]

Get an IBGE table metadata.

Examples

>>> ibge.get_metadata(1419)
                                                             values
id                                                             1419
nome              IPCA - Variação mensal, acumulada no ano, acum...
URL                            http://sidra.ibge.gov.br/tabela/1419
pesquisa              Índice Nacional de Preços ao Consumidor Amplo
assunto                                           Índices de preços
periodicidade     {'frequencia': 'mensal', 'inicio': 201201, 'fi...
nivelTerritorial  {'Administrativo': ['N1', 'N6', 'N7'], 'Especi...
variaveis         [{'id': 63, 'nome': 'IPCA - Variação mensal', ...
classificacoes    [{'id': 315, 'nome': 'Geral, grupo, subgrupo, ...

seriesbr.ipea module

seriesbr.ipea.get_series(code: str, start: str = None, end: str = None, last_n: int = None) → pandas.core.frame.DataFrame[source]

Get multiple IPEA time series.

Parameters:
  • code (str) – Series identifier.
  • start (str, optional) – Initial date.
  • end (str, optional) – Final date.
Returns:
Return type:

pandas.DataFrame
seriesbr.ipea.get_metadata(code: str) → seriesbr.ipea.metadata.IpeaMetadata[source]

Get IPEA time series metadata.

Parameters:code (int or str) –
Returns:
Return type:pandas.DataFrame

Examples

>>> ipea.get_metadata("BM12_TJOVER12").head()
                                                           values
SERCODIGO                                           BM12_TJOVER12
SERNOME                              Taxa de juros - Over / Selic
SERCOMENTARIO   Quadro: Taxas de juros efetivas.  Para 1974-19...
SERATUALIZACAO                      2019-12-17T05:06:00.793-02:00
BASNOME                                            Macroeconômico

Module contents