R로 배우는 plotly 중급 인터랙티브 데이터 시각화
Adam Loy
Statistician, Carleton College
world2014
# A tibble: 193 x 11 country year income co2 military population urban life_expectancy four_regions <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <chr> 1 Afghan… 2014 1780 0.299 1.3 32800000 8.05e6 57.8 asia 2 Albania 2014 10700 1.96 1.35 2920000 1.63e6 77.4 europe 3 Algeria 2014 13500 3.72 5.55 39100000 2.75e7 77.1 africa 4 Andorra 2014 44900 5.83 NA 79200 7.01e4 82.6 europe 5 Angola 2014 6260 1.29 4.7 26900000 1.69e7 63.3 africa 6 Antigu… 2014 19500 5.38 NA 98900 2.49e4 77.1 americas # … with 187 more rows, and 2 more variables: eight_regions <chr>, six_regions <chr>
p1 <- world2014 %>% plot_ly(x = ~income, y = ~co2) %>% add_markers() p2 <- world2014 %>% plot_ly(x = ~military, y = ~co2) %>% add_markers() subplot(p1, p2, titleX = TRUE, titleY = TRUE) %>% hide_legend()
library(crosstalk) shared_data <- SharedData$new(world2014) p1 <- shared_data %>% plot_ly(x = ~income, y = ~co2) %>% add_markers() p2 <- shared_data %>% plot_ly(x = ~military, y = ~co2) %>% add_markers() subplot(p1, p2, titleX = TRUE, titleY = TRUE) %>% hide_legend()
library(crosstalk) shared_data <- SharedData$new(world2014)
p1 <- shared_data %>% plot_ly(x = ~income, y = ~co2) %>% add_markers() p2 <- shared_data %>% plot_ly(x = ~military, y = ~co2) %>% add_markers()
subplot(p1, p2, titleX = TRUE, titleY = TRUE) %>% hide_legend()
highlight()로 연결된 브러싱 활성화
highlight()
subplot(p1, p2, titleX = TRUE, titleY = TRUE) %>% hide_legend() %>% highlight(on = "plotly_selected")
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