r - 有什么方法可以创建以范围为过渡时间的动画（gganimate）？

Question

有没有办法让 gganimate 为几年范围内的过渡时间工作？在我的数据中，我有三个时间点，其中两个是如下所示的范围。

数据：

Year   rate   group
2012-2014   7   Other CT, White 
2015-2017   11  Other CT, White 
2018    3   Fairfield, Black    
2018    2   Fairfield, Hispanic

这是我想要制作动画的 ggplot 代码示例

data %>% ggplot(aes(y = rate, x = group)) +
  geom_col() +
  coord_flip() +
  labs(title = "Year: {frame_time}") +
  transition_time(Year)

当我将转换时间输入为“年份”时，我收到一个错误，因为我的年份变量是一个容纳范围的字符。这是我得到的错误：

Error: time data must either be integer, numeric, POSIXct, Date, difftime, orhms

我能做些什么来绕过这个错误并继续原样的范围吗？

标签： rggplot2gganimate

Answer 1

我建议要么使用transition_manual并将年份视为类别（失去平滑过渡），要么将年份范围转换为数字。

library(tidyverse); library(gganimate)
df1 <- tribble(~Year, ~rate, ~group,
               "2012-2014", 7, "grp1",
               "2015-2017", 11, "grp1",
               "2018", 3, "grp1")

第一种方法，将 Year 保持原样：

df1 %>% 
  ggplot(aes(y = rate, x = group)) +
  geom_col() +
  coord_flip() +
  labs(title = "Year: {current_frame}") +
  transition_manual(Year)

Second approach, converting year to numeric. In this case, I just used the first year, but you could alternatively assign the value to the average year, or add rows with the value for each year in the range.

df1 %>% 
  mutate(Year_numeric = parse_number(Year)) %>%
  ggplot(aes(y = rate, x = group)) +
  geom_col() +
  coord_flip() +
  labs(title = "Year: {round(frame_time)}") +
  transition_time(Year_numeric)

Finally, if you want to represent all the ranged years at the given level, you can create rows for all the component years. But this takes some elbow grease:

df1 %>% 
  # For ranged years, find how many in range:
  mutate(year_num = 1 + if_else(Year %>% str_detect("-"), 
                            str_sub(Year, start = 6) %>% as.numeric() - 
                              str_sub(Year, end = 4) %>% as.numeric(), 
                            0)) %>%
  # ... and use that to make a row for each year in the range
  tidyr::uncount(year_num) %>%
  group_by(Year) %>%
  mutate(Year2 = str_sub(Year, end = 4) %>% as.numeric() + 
                 row_number() - 1) %>%
  ungroup() %>%

# FYI at this point it looks like:
# A tibble: 7 x 4
#  Year       rate group Year2
#  <chr>     <dbl> <chr> <dbl>
#1 2012-2014     7 grp1   2012
#2 2012-2014     7 grp1   2013
#3 2012-2014     7 grp1   2014
#4 2015-2017    11 grp1   2015
#5 2015-2017    11 grp1   2016
#6 2015-2017    11 grp1   2017
#7 2018          3 grp1   2018

ggplot(aes(y = rate, x = group)) +
  geom_col() +
  coord_flip() +
  labs(title = "Year: {round(frame_time)}") +
  transition_time(Year2)