Homework4 - Dados bcb

Escolha uma conta ou um item do balanço de pagamentos e faça um gráfico de sua evolução usando o ggplot do R (utilize o período de 2000 até o presente).
Anexe o script do R junto com os dados e a finalização em html ou pdf.

install.packages("GetBCBData")

## Installing package into '/cloud/lib/x86_64-pc-linux-gnu-library/4.2'
## (as 'lib' is unspecified)

install.packages("xts")

## Installing package into '/cloud/lib/x86_64-pc-linux-gnu-library/4.2'
## (as 'lib' is unspecified)

install.packages("tidyverse")

## Installing package into '/cloud/lib/x86_64-pc-linux-gnu-library/4.2'
## (as 'lib' is unspecified)

install.packages("ggthemes")

## Installing package into '/cloud/lib/x86_64-pc-linux-gnu-library/4.2'
## (as 'lib' is unspecified)

library(GetBCBData)
library(xts)

## Loading required package: zoo

## 
## Attaching package: 'zoo'

## The following objects are masked from 'package:base':
## 
##     as.Date, as.Date.numeric

library(tidyverse)

## ── Attaching packages
## ───────────────────────────────────────
## tidyverse 1.3.2 ──

## ✔ ggplot2 3.3.6      ✔ purrr   0.3.4 
## ✔ tibble  3.1.8      ✔ dplyr   1.0.10
## ✔ tidyr   1.2.0      ✔ stringr 1.4.1 
## ✔ readr   2.1.2      ✔ forcats 0.5.2 
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::first()  masks xts::first()
## ✖ dplyr::lag()    masks stats::lag()
## ✖ dplyr::last()   masks xts::last()

library(ggthemes)
library(ggplot2)

cont_fin <- GetBCBData::gbcbd_get_series(
  id = 23623,
  first.date = "2001-12-31",
  last.date = "2021-12-31")

## 
## Fetching id = 23623 [23623] from BCB-SGS with cache 
##   Found 21 observations

tail(cont_fin, 21)

##      ref.date    value id.num series.name
## 1  2001-01-01 -24181.2  23623  id = 23623
## 2  2002-01-01  -8157.9  23623  id = 23623
## 3  2003-01-01   2966.6  23623  id = 23623
## 4  2004-01-01   9020.0  23623  id = 23623
## 5  2005-01-01  13040.3  23623  id = 23623
## 6  2006-01-01  13114.7  23623  id = 23623
## 7  2007-01-01  -2496.3  23623  id = 23623
## 8  2008-01-01 -28806.3  23623  id = 23623
## 9  2009-01-01 -26354.0  23623  id = 23623
## 10 2010-01-01 -70172.3  23623  id = 23623
## 11 2011-01-01 -80711.6  23623  id = 23623
## 12 2012-01-01 -83669.3  23623  id = 23623
## 13 2013-01-01 -78822.7  23623  id = 23623
## 14 2014-01-01 -96856.1  23623  id = 23623
## 15 2015-01-01 -56646.8  23623  id = 23623
## 16 2016-01-01 -16092.5  23623  id = 23623
## 17 2017-01-01 -17075.0  23623  id = 23623
## 18 2018-01-01 -52341.7  23623  id = 23623
## 19 2019-01-01 -64356.8  23623  id = 23623
## 20 2020-01-01 -12472.6  23623  id = 23623
## 21 2021-01-01 -33706.1  23623  id = 23623

times = seq(as.Date("2001-12-31"),
            as.Date("2021-12-31"), 
            by = "year")

ContaFinanceira = data.frame(time = tail(times, 21),
                  ContaFinanceira = tail(cont_fin$value, 21))


ggplot(ContaFinanceira, aes(x = time, y = ContaFinanceira))+
  
  labs(title = 'Serie da Conta Financeira do Balaço de Pagamentos: 2000 a 2021', 
       x = 'Anos', y = 'Conta Financeira (em milhões US$)')+

  geom_line(size = 0.7, colour = "darkgray")