is there any way to create an animation (gganimate) with ranges as transition times?

Question

Is there any way to make gganimate work for transition times that are ranges of years? In my data I have three time points, two of which are ranges as shown below.

data:

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

here's an example of the code for the ggplot that I'd like to animate

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

when I enter the transition time as "Year" I get an error because my Year variable is a character to accommodate the ranges. This is the error I get:

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

is there anything I can do to bypass this error and continue with the ranges as they are?

Answer 1

我建议您transition_manual将年份与类别一样对待（失去平稳的过渡），或者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)

第二种方法，将年份转换为数字。在这种情况下，我只使用了第一年，但是您也可以将值分配给平均年，或者添加范围内每年的值的行。

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)

最后，如果要表示给定级别上的所有范围年份，则可以为所有组成年份创建行。但这需要一些肘部润滑脂：

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)