Metadata-Version: 2.1
Name: deflateBR
Version: 0.2
Summary: Deflate Nominal Brazilian Reais
Home-page: http://github.com/neylsoncrepalde/deflatebr
Author: Neylson Crepalde & Fernando Meireles
Author-email: neylsoncrepalde@gmail.com
License: MIT
Description: deflateBR
        =========
        
        [![PyPi version](https://pypip.in/v/deflateBR/badge.png)](https://crate.io/packages/deflateBR/)
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        [![PyPi downloads](https://pypip.in/d/deflateBR/badge.png)](https://crate.io/packages/deflateBR/)
        
        
        
        `deflateBR` is a `Python` package used to deflate nominal Brazilian Reais
        using several popular price indexes. It is a reimplementation of the great
        [deflateBR R package](https://cran.r-project.org/web/packages/deflateBR/index.html) 
        by [Fernando Meireles](https://twitter.com/meirelesff).
        
        Installation
        ============
        
        ```bash
        pip install deflateBR
        ```
        
        Examples
        ========
        
        The `deflateBR`’s main function, `deflate`, requires three arguments to
        work: an `int` of `float` vector of nominal Reais (`nominal_values`); a `str` or `datetime` vector of corresponding dates (`nominal_dates`); and a reference month in the `YYYY-MM` format (`real_date`), used to deflate the values. An
        example:
        
        To deflate BRL R$100,00 (one hundred brazilian reais) in January 2015,
        simply do
        
        ```python
        import deflatebr as dbr
        
        dbr.deflate(nominal_values=100, nominal_dates='2015-01-01', 
                    real_date='2020-01')
        ```
            array([131.32029183])
        
        To deflate a bigger series, do
        
        ```python
        import pandas as pd
        
        df = pd.DataFrame({'nom_values':[100,200,300,400],
                            'dates':['2015-01-01', '2015-02-01',
                                    '2015-10-01', '2015-12-01']})
        df
        ```
               nom_values       dates
            0         100  2015-01-01
            1         200  2015-02-01
            2         300  2015-10-01
            3         400  2015-12-01
        
        ```python
        dbr.deflate(nominal_values=df.nom_values, nominal_dates=df.dates, 
                    real_date='2020-01')
        ```
            array([131.32029183, 259.42387232, 365.99132289, 479.18030761])
        
        
        Behind the scenes, `deflateBR` requests data from
        [IPEADATA](http://www.ipeadata.gov.br/)’s API on one these five
        Brazilian price indexes:
        [IPCA](https://ww2.ibge.gov.br/english/estatistica/indicadores/precos/inpc_ipca/defaultinpc.shtm)
        and
        [INPC](https://ww2.ibge.gov.br/english/estatistica/indicadores/precos/inpc_ipca/defaultinpc.shtm),
        maintained by [IBGE](https://ww2.ibge.gov.br/home/); and
        [IGP-M](http://portalibre.fgv.br/main.jsp?lumChannelId=402880811D8E34B9011D92B6160B0D7D),
        [IGP-DI](http://portalibre.fgv.br/main.jsp?lumChannelId=402880811D8E34B9011D92B6160B0D7D),
        and
        [IPC](http://portalibre.fgv.br/main.jsp?lumChannelId=402880811D8E34B9011D92B7350710C7)
        maintained by
        [FGV/IBRE](http://portalibre.fgv.br/main.jsp?lumChannelId=402880811D8E2C4C011D8E33F5700158).
        To select one of the available price indexes, just provide one of the
        following options to the `index =` argument: `ipca`, `igpm`, `igpdi`,
        `ipc`, and `inpc`. In the following, the INPC index is used.
        
        ```python
        dbr.deflate(nominal_values=100, nominal_dates='2015-01-01', 
                    real_date='2020-01', index='inpc')
        ```
            array([131.06584509])
        
        
        Methodology
        -----------
        
        Following standard practice, seconded by the [Brazilian Central
        Bank](https://www3.bcb.gov.br/CALCIDADAO/publico/metodologiaCorrigirIndice.do?method=metodologiaCorrigirIndice),
        the `deflateBR` adjusts for inflation by multiplying nominal Reais by
        the ratio between the original and the reference price indexes. For
        example, to adjust 100 reais of January 2018, with IPCA index of
        4916.46, to August 2018, with IPCA of 5056.56 in the previous month, we
        first calculate the ratio between the two indexes (e.g., 5056.56 /
        4916.46 = 1.028496) and then multiply this value by 100 (e.g., 102.84
        adjusted Reais). The `deflate` function gives exactly the same result:
        
        ```python
        dbr.deflate(100,"2018-01-01", "2018-08", "ipca")
        ```
            array([102.84961131])
        
        Authors
        ------
        
        [Neylson Crepalde](https://www.neylsoncrepalde.com) & 
        [Fernando Meireles](http://fmeireles.com)
        
Keywords: deflate deflation economics salary wage finance
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Office/Business :: Financial
Classifier: Topic :: Scientific/Engineering :: Mathematics
Requires-Python: >=3.6
Description-Content-Type: text/markdown
