Melhorando a visualização

Carregando as bibliotecas

library("ggplot2")
library("dplyr")
library("gapminder")

Cores por continente

gap_07 <- filter(gapminder, year == 2007)
ggplot(gap_07, aes(x = gdpPercap, y = lifeExp,
                   color = continent)) +
  geom_point() +
  theme_minimal()

Usando formas e cores diferentes

ggplot(gap_07, aes(x = gdpPercap, y = lifeExp,
                   shape = continent, color = continent)) +
  geom_point() +
  theme_minimal()

Cores e tamanho

ggplot(gap_07, aes(x = gdpPercap, y = lifeExp,
                   size = pop, color = continent)) +
  geom_point() +
  theme_minimal()

Sumario dos dados para obter pop média por continente

gap_pop <- gapminder %>% 
  group_by(continent, year) %>% 
  summarize(pop = mean(pop))

#> `summarise()` has grouped output by 'continent'. You can override using the
#> `.groups` argument.

head(gap_pop)

#> # A tibble: 6 × 3
#> # Groups:   continent [1]
#>   continent  year      pop
#>   <fct>     <int>    <dbl>
#> 1 Africa     1952 4570010.
#> 2 Africa     1957 5093033.
#> 3 Africa     1962 5702247.
#> 4 Africa     1967 6447875.
#> 5 Africa     1972 7305376.
#> 6 Africa     1977 8328097.

Grafico de linha com cores

ggplot(gap_pop, aes(x = year, y = pop, color = continent)) +
  geom_line() + 
  geom_point() +
  theme_minimal()

Criando grids entre os anos de 2002 e 2007

gap_0207 <- gapminder %>% filter(between(year, 2002, 2007))
ggplot(gap_0207, aes(x = gdpPercap, y = lifeExp)) +
  geom_point() +
  facet_grid(continent ~ year) +
  theme_minimal()

Outro tipo de apresentações de grid

gap_life <- gapminder %>% 
  group_by(continent, year) %>% 
  summarize(lifeExp = mean(lifeExp))

#> `summarise()` has grouped output by 'continent'. You can override using the
#> `.groups` argument.

ggplot(gap_life, aes(x = year, y = lifeExp)) +
  geom_line() +
  facet_grid(continent ~ .) +
  theme_minimal()

Grid em outra direção

ggplot(gap_life, aes(x = year, y = lifeExp)) +
  geom_line() +
  facet_grid(. ~ continent) +
  theme_minimal()

Usando o wrap

ggplot(gap_life, aes(x = year, y = lifeExp)) +
  geom_line() +
  facet_wrap( ~ continent) +
  theme_minimal()

Filtrando dados e fazendo grafico de dispersão padrão

gapminder |> 
  filter(year == 2007) |>   
  ggplot(aes(x = gdpPercap, y = lifeExp)) +
  geom_point() +
  theme_minimal()

Transformando o eixo x para escala logarítimica

gapminder |> 
  filter(year == 2007) |>
  ggplot(aes(x = gdpPercap, y = lifeExp)) +
  geom_point() +
  scale_x_continuous(trans = "log10") +
  theme_minimal()

Outra forma de transformação do eixo x

gapminder |> 
  filter(year == 2007) |>
  ggplot(aes(x = gdpPercap, y = lifeExp)) +
  geom_point() +
  scale_x_log10() +
  theme_minimal()

Definindo limites para o eixo y

gapminder |> 
  filter(year == 2007) |>
  ggplot(aes(x = gdpPercap, y = lifeExp)) +
  geom_point() +
  scale_x_log10() +
  scale_y_continuous(limits = c(0, 95)) +
  theme_minimal()

Grafico com cores normais

gap_07 <- gapminder |> filter(year == 2007)
ggplot(gap_07, aes(x = gdpPercap, y = lifeExp, color = continent)) +
  geom_point() +
  scale_x_log10() +
  theme_minimal()

Grafico usando outra paleta de cores

ggplot(gap_07, aes(x = gdpPercap, y = lifeExp, color = continent)) +
  geom_point() +
  scale_x_log10() +
  scale_color_brewer(palette = "Dark2")  +
  theme_minimal()

Usando codigos manuais para as cores

ggplot(gap_07, aes(x = gdpPercap, y = lifeExp, color = continent)) +
  geom_point() +
  scale_x_log10() +
  scale_color_manual(values = c("#FF0000", "#00A08A", "#F2AD00",
                                "#F98400", "#5BBCD6"))  +
  theme_minimal()

Definindo as cores e tamanho dos pontos

ggplot(gap_07, aes(x = gdpPercap, y = lifeExp)) +
  geom_point(color = "darkblue", size = 3) +
  scale_x_log10()  +
  theme_minimal()

Customizando títulos, rótulos de eixo e legendas

ggplot(gap_07, aes(x = gdpPercap, y = lifeExp, color = continent)) +
  geom_point(size = 2) +
  scale_x_log10() +
  theme_minimal() +
  theme(legend.position = "bottom")

Sem legenda

ggplot(gap_07, aes(x = gdpPercap, y = lifeExp, color = continent)) +
  geom_point(size = 2) +
  scale_x_log10() +
  theme_minimal() +
  theme(legend.position = "none")

Salvando o gráfico

graf1 <- ggplot(gap_07, aes(x = gdpPercap, y = lifeExp, color = continent)) +
  geom_point(size = 2) +
  scale_x_log10() +
  theme_light() 

graf1

Aumentando o tamanho do texto e mudando para portugues

graf2 <- ggplot(gap_07, aes(x = gdpPercap, y = lifeExp, color = continent)) +
  geom_point(size = 2) +
  scale_x_log10() +
  theme_light() +
  theme(legend.key = element_blank(),
        axis.text = element_text(size = 12),
        axis.title = element_text(size = 14)) +
  labs(x = "PIB Per capita (US$)", 
       y = "Expectativa de Vida (anos)", 
       title = "Expectativa de Vida vs PIB em 2007",
       color = "Continente")

graf2