This library provides a pure Python interface for the Brazilian Central Bank's Time Series Management System (SGS) api. It works with Python 3.5 and above.
SGS is a service with more than 18,000 time series with economical and financial information. This library is intended to make it easier for Python programmers to use this data in projects of any kind, providing mechanisms to search for, extract and join series.
Access time series data with sgs is very simple
Begin by importing the sgs module:
import sgsNow, let's try to get a time serie. For this example, let's get the "Interest rate - CDI" time serie in 2018, wich has the code 12.
CDI_CODE = 12
ts = sgs.time_serie(CDI_CODE, start='02/01/2018', end='31/12/2018')Now, we have a Pandas Series object called ts, with all the data and
the index representing the dates.
ts.head()| 2018-01-02 | 0.026444 |
| 2018-01-03 | 0.026444 |
| 2018-01-04 | 0.026444 |
| 2018-01-05 | 0.026444 |
| 2018-01-08 | 0.026444 |
- Get time serie data with an one-liner using
sgs.time_serie - Create a dataframe from a list of time series codes with
sgs.dataframe - Search time series by text or code with
sgs.search_ts - Get metadata from all the series in a dataframe using
sgs.metadata - Support to search and metadata in English and Portuguese
- Automatic retry
- Automatic cached requests
To install, simply use pip:
$ pip install sgsComplete documentation is available at https://pysgs.readthedocs.io/en/stable/.