edit code in vignette

r-package/vignettes/intro_to_geobr.Rmd

@@ -25,21 +25,21 @@ You can install geobr from CRAN or the development version to use the latest fea
 
 ```{r eval=FALSE, message=FALSE, warning=FALSE}
 # From CRAN
- install.packages("geobr")
+install.packages("geobr")
 
 # Development version
- utils::remove.packages('geobr')
- devtools::install_github("ipeaGIT/geobr", subdir = "r-package")
+utils::remove.packages('geobr')
+devtools::install_github("ipeaGIT/geobr", subdir = "r-package")
 
 ```
 
 Now let's load the libraries we'll use in this vignette.
 
 ```{r eval=TRUE, message=FALSE, warning=FALSE, results='hide'}
- library(geobr)
- library(ggplot2)
- library(sf)
- library(dplyr)
+library(geobr)
+library(ggplot2)
+library(sf)
+library(dplyr)
 ```
 
 
@@ -66,42 +66,52 @@ The syntax of all *geobr* functions operate one the same logic, so the code to d
 Download an specific geographic area at a given year
 ```{r eval=TRUE, message=FALSE, warning=FALSE, results='hide'}
 # State of Sergige
- state <- read_state(code_state="SE", 
- year=2018,
- showProgress = FALSE)
+state <- read_state(
+ code_state="SE",
+ year=2018,
+ showProgress = FALSE
+ )
 
 # Municipality of Sao Paulo
- muni <- read_municipality(code_muni = 3550308, 
- year=2010, 
- showProgress = FALSE)
+muni <- read_municipality(
+ code_muni = 3550308, 
+ year=2010, 
+ showProgress = FALSE
+ )
 
 ```
 
 
 Download all geographic areas within a state at a given year
 ```{r eval=FALSE, message=FALSE, warning=FALSE, results='hide'}
 # All municipalities in the state of Minas Gerais
- muni <- read_municipality(code_muni= "MG", 
-  year=2007,
-  showProgress = FALSE)
+muni <- read_municipality(code_muni= "MG", 
+ year=2007,
+ showProgress = FALSE)
 
 # All census tracts in the state of Rio de Janeiro
- cntr <- read_census_tract(code_tract = "RJ", 
- year = 2010,
- showProgress = FALSE)
+cntr <- read_census_tract(
+ code_tract = "RJ", 
+ year = 2010,
+ showProgress = FALSE
+ )
 
 ```
 
 If the parameter `code_` is not passed to the function, geobr returns the data for the whole country by default.
 
 ```{r eval=TRUE, message=FALSE, warning=FALSE, results='hide'}
 # read all intermediate regions
-inter <- read_intermediate_region(year=2017,
- showProgress = FALSE)
+inter <- read_intermediate_region(
+ year=2017,
+ showProgress = FALSE
+ )
 
 # read all states
-states <- read_state(year=2019, 
- showProgress = FALSE)
+states <- read_state(
+ year=2019, 
+ showProgress = FALSE
+ )
 
 ```
 
@@ -119,18 +129,18 @@ Once you've downloaded the data, it is really simple to plot maps using `ggplot2
 
 ```{r eval=TRUE, message=FALSE, warning=FALSE, fig.height = 8, fig.width = 8, fig.align = "center"}
 # Remove plot axis
- no_axis <- theme(axis.title=element_blank(),
-  axis.text=element_blank(),
-  axis.ticks=element_blank())
+no_axis <- theme(axis.title=element_blank(),
+ axis.text=element_blank(),
+ axis.ticks=element_blank())
 
 
 
 # Plot all Brazilian states
- ggplot() +
-  geom_sf(data=states, fill="#2D3E50", color="#FEBF57", size=.15, show.legend = FALSE) +
-  labs(subtitle="States", size=8) +
-  theme_minimal() +
-  no_axis
+ggplot() +
+ geom_sf(data=states, fill="#2D3E50", color="#FEBF57", size=.15, show.legend = FALSE) +
+ labs(subtitle="States", size=8) +
+ theme_minimal() +
+ no_axis
 
 ```
 
@@ -144,17 +154,19 @@ Plot all the municipalities of a particular state, such as Rio de Janeiro:
 ```{r eval=TRUE, message=FALSE, warning=FALSE, results='hide', fig.height = 8, fig.width = 8, fig.align = "center"}
 
 # Download all municipalities of Rio
- all_muni <- read_municipality( code_muni = "RJ", 
- year= 2010,
- showProgress = FALSE)
+all_muni <- read_municipality(
+ code_muni = "RJ", 
+ year= 2010,
+ showProgress = FALSE
+ )
 
 
 # plot
- ggplot() +
-  geom_sf(data=all_muni, fill="#2D3E50", color="#FEBF57", size=.15, show.legend = FALSE) +
-  labs(subtitle="Municipalities of Rio de Janeiro, 2000", size=8) +
-  theme_minimal() +
-  no_axis
+ggplot() +
+ geom_sf(data=all_muni, fill="#2D3E50", color="#FEBF57", size=.15, show.legend = FALSE) +
+ labs(subtitle="Municipalities of Rio de Janeiro, 2000", size=8) +
+ theme_minimal() +
+ no_axis
 ```
 
 ```{r munis rio, eval=FALSE, echo=FALSE, message=FALSE, out.width='100%'}
@@ -185,12 +197,12 @@ states <- dplyr::left_join(states, df, by = c("name_state" = "uf"))
 #### Plot thematic map
 
 ```{r eval=TRUE, message=FALSE, warning=FALSE, fig.height = 8, fig.width = 8, fig.align = "center" }
- ggplot() +
-  geom_sf(data=states, aes(fill=ESPVIDA2017), color= NA, size=.15) +
-  labs(subtitle="Life Expectancy at birth, Brazilian States, 2014", size=8) +
-  scale_fill_distiller(palette = "Blues", name="Life Expectancy", limits = c(65,80)) +
-  theme_minimal() +
-  no_axis
+ggplot() +
+ geom_sf(data=states, aes(fill=ESPVIDA2017), color= NA, size=.15) +
+ labs(subtitle="Life Expectancy at birth, Brazilian States, 2014", size=8) +
+ scale_fill_distiller(palette = "Blues", name="Life Expectancy", limits = c(65,80)) +
+ theme_minimal() +
+ no_axis
 
 ```