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library(ggvis)
# Scatter plot with loess model line
mtcars %>% ggvis(x = ~wt, y = ~mpg) %>%
layer_points() %>%
compute_smooth(mpg ~ wt, se = F) %>%
layer_paths(x = ~pred_, y = ~resp_, stroke := "red")
# Or with shorthand layer_smooth
mtcars %>% ggvis(x = ~wt, y = ~mpg) %>%
layer_points() %>%
layer_smooths(stroke := "red")
# With confidence region
mtcars %>% ggvis(x = ~wt, y = ~mpg) %>%
layer_points() %>%
layer_smooths(stroke := "red", se = TRUE)
# Scatter plot with lm model line
mtcars %>% ggvis(x = ~wt, y = ~mpg) %>%
layer_points() %>%
layer_model_predictions(stroke := "red", model = "lm")
# Scatterplot with lm and loess
mtcars %>% ggvis(x = ~wt, y = ~mpg) %>%
layer_points() %>%
layer_smooths(stroke := "blue") %>%
layer_model_predictions(stroke := "red", model = "lm")
# Scatter plot with smooth for each level of cyl
mtcars %>% ggvis(x = ~wt, y = ~mpg, stroke = ~factor(cyl)) %>%
group_by(cyl) %>%
layer_points() %>%
layer_smooths()
# Scatter plot with smooth for each level of cyl, but only points coloured
mtcars %>% ggvis(x = ~wt, y = ~mpg) %>%
group_by(cyl) %>%
layer_points(fill = ~factor(cyl)) %>%
layer_smooths()
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