This is a follow-up to this question, where I animated a Kaplan-Meier curve.

I would now like to first show the first curve dynamically, and after it finishes animating, display the second curve. Ideally, the second curve should appear sequentially, rather than both animating at the same time.

Is there a way to achieve this in gganimate (or another approach)?

The example data can be found in the linked question, but here is a minimal version of my setup:

df <- structure(list(time = c(5, 6, 8, 10, 11, 12, 13, 14, 15, 17, 
18, 20, 22, 27, 31, 32, 34, 39, 43, 44, 47, 48, 50, 60, 69, 77, 
120, 1, 4, 6, 7, 8, 9, 11, 12, 13, 14, 15, 17, 19, 22, 23, 25, 
26, 27, 31, 38, 40, 64, 89, 96, 105, 117), surv = c(0.96969696969697, 
0.93841642228739, 0.906057235311963, 0.906057235311963, 0.871208880107657, 
0.871208880107657, 0.871208880107657, 0.871208880107657, 0.829722742959673, 
0.786053124909164, 0.742383506858655, 0.695984537679989, 0.649585568501323, 
0.603186599322657, 0.603186599322657, 0.603186599322657, 0.603186599322657, 
0.542867939390391, 0.482549279458125, 0.42223061952586, 0.42223061952586, 
0.351858849604883, 0.351858849604883, 0.351858849604883, 0.351858849604883, 
0.175929424802442, 0.175929424802442, 1, 0.96551724137931, 0.96551724137931, 
0.929757343550447, 0.892567049808429, 0.892567049808429, 0.892567049808429, 
0.850063856960409, 0.805323653962492, 0.760583450964576, 0.760583450964576, 
0.760583450964576, 0.706256061609964, 0.651928672255351, 0.597601282900738, 
0.597601282900738, 0.597601282900738, 0.597601282900738, 0.522901122538146, 
0.522901122538146, 0.435750935448455, 0.435750935448455, 0.435750935448455, 
0.435750935448455, 0.435750935448455, 0.435750935448455), V3 = c(0.97, 
0.94, 0.91, 0.91, 0.87, 0.87, 0.87, 0.87, 0.83, 0.79, 0.74, 0.7, 
0.65, 0.6, 0.6, 0.6, 0.6, 0.54, 0.48, 0.42, 0.42, 0.35, 0.35, 
0.35, 0.35, 0.18, 0.18, 1, 0.97, 0.97, 0.93, 0.89, 0.89, 0.89, 
0.85, 0.81, 0.76, 0.76, 0.76, 0.71, 0.65, 0.6, 0.6, 0.6, 0.6, 
0.52, 0.52, 0.44, 0.44, 0.44, 0.44, 0.44, 0.44), grupo = c(1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2), risk = c(33, 31, 29, 27, 26, 24, 
23, 22, 21, 19, 18, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 
4, 3, 2, 1, 30, 29, 28, 27, 25, 24, 23, 21, 19, 18, 16, 15, 14, 
13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1)), class = "data.frame", row.names = c(NA, 
-53L))


ggplot(df, aes(x = time, y = surv, group = grupo, color = as.factor(grupo))) +
    geom_line(size = 1.5) +
    geom_point(size = 2, color = "gray") +
    guides(color = guide_legend(override.aes = list(shape = 1))) +
    scale_color_brewer(
        name = "Gender",palette = "Set1", labels = c("Female", "Male")) +
    labs(
        title = "Survival according to gender", 
        x = "Time [weeks]", 
        y = "Survival [%]")  +
    scale_y_continuous(limits = c(0, 1)) +
    scale_x_continuous(                                    # This is new
        breaks = scales::breaks_width(25),                 # Label every 25 weeks
        expand = expansion(mult = c(0, 0.15))) +           # 15% increase on the right
    geom_text(
        aes(y = V3, label = format(V3)),
        size = 6,
        hjust = -0.2,
        vjust = 0.5, 
        show.legend = FALSE) +
    transition_reveal(time) +
    theme_minimal(base_size = 16) +
    theme(
        axis.line = element_line(colour = "black", size = 0.24),
        aspect.ratio = 4/5)

This is a follow-up to this question, where I animated a Kaplan-Meier curve.

I would now like to first show the first curve dynamically, and after it finishes animating, display the second curve. Ideally, the second curve should appear sequentially, rather than both animating at the same time.

Is there a way to achieve this in gganimate (or another approach)?

The example data can be found in the linked question, but here is a minimal version of my setup:

df <- structure(list(time = c(5, 6, 8, 10, 11, 12, 13, 14, 15, 17, 
18, 20, 22, 27, 31, 32, 34, 39, 43, 44, 47, 48, 50, 60, 69, 77, 
120, 1, 4, 6, 7, 8, 9, 11, 12, 13, 14, 15, 17, 19, 22, 23, 25, 
26, 27, 31, 38, 40, 64, 89, 96, 105, 117), surv = c(0.96969696969697, 
0.93841642228739, 0.906057235311963, 0.906057235311963, 0.871208880107657, 
0.871208880107657, 0.871208880107657, 0.871208880107657, 0.829722742959673, 
0.786053124909164, 0.742383506858655, 0.695984537679989, 0.649585568501323, 
0.603186599322657, 0.603186599322657, 0.603186599322657, 0.603186599322657, 
0.542867939390391, 0.482549279458125, 0.42223061952586, 0.42223061952586, 
0.351858849604883, 0.351858849604883, 0.351858849604883, 0.351858849604883, 
0.175929424802442, 0.175929424802442, 1, 0.96551724137931, 0.96551724137931, 
0.929757343550447, 0.892567049808429, 0.892567049808429, 0.892567049808429, 
0.850063856960409, 0.805323653962492, 0.760583450964576, 0.760583450964576, 
0.760583450964576, 0.706256061609964, 0.651928672255351, 0.597601282900738, 
0.597601282900738, 0.597601282900738, 0.597601282900738, 0.522901122538146, 
0.522901122538146, 0.435750935448455, 0.435750935448455, 0.435750935448455, 
0.435750935448455, 0.435750935448455, 0.435750935448455), V3 = c(0.97, 
0.94, 0.91, 0.91, 0.87, 0.87, 0.87, 0.87, 0.83, 0.79, 0.74, 0.7, 
0.65, 0.6, 0.6, 0.6, 0.6, 0.54, 0.48, 0.42, 0.42, 0.35, 0.35, 
0.35, 0.35, 0.18, 0.18, 1, 0.97, 0.97, 0.93, 0.89, 0.89, 0.89, 
0.85, 0.81, 0.76, 0.76, 0.76, 0.71, 0.65, 0.6, 0.6, 0.6, 0.6, 
0.52, 0.52, 0.44, 0.44, 0.44, 0.44, 0.44, 0.44), grupo = c(1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2), risk = c(33, 31, 29, 27, 26, 24, 
23, 22, 21, 19, 18, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 
4, 3, 2, 1, 30, 29, 28, 27, 25, 24, 23, 21, 19, 18, 16, 15, 14, 
13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1)), class = "data.frame", row.names = c(NA, 
-53L))


ggplot(df, aes(x = time, y = surv, group = grupo, color = as.factor(grupo))) +
    geom_line(size = 1.5) +
    geom_point(size = 2, color = "gray") +
    guides(color = guide_legend(override.aes = list(shape = 1))) +
    scale_color_brewer(
        name = "Gender",palette = "Set1", labels = c("Female", "Male")) +
    labs(
        title = "Survival according to gender", 
        x = "Time [weeks]", 
        y = "Survival [%]")  +
    scale_y_continuous(limits = c(0, 1)) +
    scale_x_continuous(                                    # This is new
        breaks = scales::breaks_width(25),                 # Label every 25 weeks
        expand = expansion(mult = c(0, 0.15))) +           # 15% increase on the right
    geom_text(
        aes(y = V3, label = format(V3)),
        size = 6,
        hjust = -0.2,
        vjust = 0.5, 
        show.legend = FALSE) +
    transition_reveal(time) +
    theme_minimal(base_size = 16) +
    theme(
        axis.line = element_line(colour = "black", size = 0.24),
        aspect.ratio = 4/5)

• r
• ggplot2
• survival-analysis
• gganimate

Share Follow asked Mar 7 at 22:35 TarJaeTarJae 79.7k66 gold badges2929 silver badges9090 bronze badges Recognized by R Language Collective 2

• 1 I found this stackoverflow/a/71021479/28479453. I think the Idea is to assign numbers to each datapoints and animate through them sequentially. You could maybe also anim_save two animations and combine them afterwards. – Tim G Commented Mar 8 at 0:12
• 1 Following the idea in the answer referenced by TimG you can use transition_reveal(as.numeric(interaction(time, grupo))) to create an index column on the fly. – stefan Commented Mar 8 at 6:51

Add a comment  | 

1 Answer 1

Sorted by: Reset to default 2

Solution according to @Tim G (Many thanks):

library(tidyverse)
library(gganimate)
library(gifski)


df$transition_value <- 1:nrow(df)

p <- ggplot(df, aes(x = time, y = surv, group = grupo, color = as.factor(grupo))) +
  geom_line(size = 1.5) +
  geom_point(size = 2, color = "gray") +
  guides(color = guide_legend(override.aes = list(shape = 1))) +
  scale_color_brewer(
    name = "Gender",palette = "Set1", labels = c("Female", "Male")) +
  labs(
    title = "Survival according to gender", 
    x = "Time [weeks]", 
    y = "Survival [%]")  +
  scale_y_continuous(limits = c(0, 1)) +
  scale_x_continuous(                                    # This is new
    breaks = scales::breaks_width(25),                 # Label every 25 weeks
    expand = expansion(mult = c(0, 0.15))) +           # 15% increase on the right
  geom_text(
    aes(y = V3, label = format(V3)),
    size = 6,
    hjust = -0.2,
    vjust = 0.5, 
    show.legend = FALSE) +
  transition_reveal(time) +
  theme_minimal(base_size = 16) +
  theme(
    axis.line = element_line(colour = "black", size = 0.24),
    aspect.ratio = 4/5)


# reveal with the new value
play <- p + transition_reveal(transition_value)

# render plot using gifski
animate(play,renderer = gifski_renderer(),  fps = 10, nframes = 150, end_pause = 30) 

Solution according to @stefan (Many thanks):

library(tidyverse)
library(gganimate)
library(gifski)

p <- ggplot(df, aes(x = time, y = surv, group = grupo, color = as.factor(grupo))) +
  geom_line(size = 1.5) +
  geom_point(size = 2, color = "gray") +
  guides(color = guide_legend(override.aes = list(shape = 1))) +
  scale_color_brewer(
    name = "Gender",palette = "Set1", labels = c("Female", "Male")) +
  labs(
    title = "Survival according to gender", 
    x = "Time [weeks]", 
    y = "Survival [%]")  +
  scale_y_continuous(limits = c(0, 1)) +
  scale_x_continuous(                                    # This is new
    breaks = scales::breaks_width(25),                 # Label every 25 weeks
    expand = expansion(mult = c(0, 0.15))) +           # 15% increase on the right
  geom_text(
    aes(y = V3, label = format(V3)),
    size = 6,
    hjust = -0.2,
    vjust = 0.5, 
    show.legend = FALSE) +
  transition_reveal(time) +
  theme_minimal(base_size = 16) +
  theme(
    axis.line = element_line(colour = "black", size = 0.24),
    aspect.ratio = 4/5)


play <- p + transition_reveal(as.numeric(interaction(time, grupo)))

# render plot using gifski
animate(play,renderer = gifski_renderer(), fps = 10, nframes = 350, end_pause = 30)