---
title: "Getting Started"
author: "Marcelo Perlin"
date: "`r Sys.Date()`"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Getting Started}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

## Motivation

The Central Bank of Brazil (BCB) offers access to its SGS system (sistema gerenciador de series temporais) with a official API available [here](http://www.bcb.gov.br/?sgs).

Package GetBCBData offers a R interface to the API and many other advantages:

- A caching system with package `memoise` to speed up repeated requests of data;
- User can utilize all cores of the machine (parallel computing) when fetching a large batch of time series;
- Error handling internally. Even if requested series does not exist, the function will still return all results.

## A simple example

Let's have a look at unemployment rates around the world. After searching for the ids in the [SGS system](http://www.bcb.gov.br/?sgs), we find the ids for 6 countries and set it as input `id`. 

Now, lets download the data with `GetBCBData`:

```{r, message=FALSE, eval=FALSE}
library(GetBCBData)
library(dplyr)
library(ggplot2)

my.countries <- c('Germany', 'Canada', 'USA', 
                  'France', 'Italy', 'Japan')

my.ids <- c(3785:3790)

names(my.ids) <- paste0('Unemp. rate - ', my.countries)

df.bcb <- gbcbd_get_series(id = my.ids ,
                       first.date = '2000-01-01',
                       last.date = Sys.Date(),
                       format.data = 'long',
                       use.memoise = TRUE, 
                       cache.path = tempdir(), # use tempdir for cache folder
                       do.parallel = FALSE)

glimpse(df.bcb)

p <- ggplot(df.bcb, aes(x = ref.date, y = value) ) +
  geom_line() + 
  labs(title = 'Unemploymnent Rates Around the World', 
       subtitle = paste0(min(df.bcb$ref.date), ' to ', max(df.bcb$ref.date)),
       x = '', y = 'Percentage*100') + facet_wrap(~series.name)
  

print(p)

```