Сообщение об ошибке ggplot2: Ошибка в seq.default (range [1], range [2], length.out = nframes): 'from' должно быть конечным числом

Question

Я пытаюсь создать анимированный пузырьковый график из следующих данных:

Country/Region  1971    1972    1973    1974    1975    1976    1977    1978    1979    1980    1981    1982    1983    1984    1985    1986    1987    1988    1989    1990    1991    1992    1993    1994    1995    1996    1997    1998    1999    2000    2001    2002    2003    2004    2005    2006    2007    2008    2009    2010    GDP per Capita
  Albania        3.9    4.5      3.9     4.2     4.5    4.9     5.2     6.2      7.5    7.6     6.4      6.7     7.3     7.6    7.2     7.2     7.5      7.6    7.2     6.3      4.4     2.8     2.3    2.3     1.9     1.9      1.4    1.7     3.0      3.1     3.3     3.8    4.0     4.3     4.1      4.0    4.0     3.9      3.5     3.8 .   5,626
  Austria       48.7    50.5    54.0    51.3    50.2    54.3    51.8    54.5    57.2    55.7    52.8    51.0    51.1    52.9    54.3    53.2    54.2    52.1    52.5    56.4    60.6    55.7    56.0    56.2    59.4    63.1    62.4    62.9    61.4    61.7    65.9    67.4    72.6    73.7    74.6    72.5    70.0    70.6    63.5    69.3    56,259
  Belarus       0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     124.5   119.4   98.8    82.9    70.2    61.4    62.7    61.8    59.3    57.6    58.7    57.8    59.2    60.7    63.0    62.1    66.2    64.0    64.5    62.3    65.3    6,575
  Belgium       116.8   126.7   132.7   130.6   115.6   124.5   123.5   129.0   132.3   125.7   115.5   109.3   100.6   102.6   101.9   102.6   102.8   104.6   105.9   107.9   113.3   112.3   109.8   115.5   115.2   121.3   118.5   120.9   117.4   118.6   119.1   111.9   119.5   116.5   112.6   109.6   105.6   111.0   100.7   106.4   51,237
  Bosnia        0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     23.7    21.2    15.6    13.1    3.0     3.2     4.1    8.3 10.5    10.2    13.5    13.3    14.0    14.3    15.0    15.6    17.2    18.2    19.9    19.4    19.9    6,140
  Bulgaria      62.8    64.8    66.6    67.7    72.2    72.1    74.8    77.9    81.1    83.8    79.9    81.5    80.2    78.3    81.1    82.1    83.1    82.1    81.4    74.8    56.4    54.1    55.1    52.5    53.2    53.8    50.9    48.7    42.8    42.1    44.8    42.0    46.3    45.4    45.9    47.3    50.4    49.0    42.2    43.8    9,811
  Croatia       0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     21.6    15.7    15.2    15.8    15.0    15.8    15.6    17.3    18.4    18.3    17.7    18.6    19.6    21.0    20.4    20.8    20.8    22.1    21.0    19.8    19.0    15,533
  Cyprus        1.8     2.2     2.3     1.8     1.7     2.0     2.1     2.3     2.5     2.6     2.5     2.6     2.7     2.8     2.8     3.1     3.6     3.6     3.8     3.8     4.4     4.7     4.9     5.3     5.2     5.5     5.7     5.8     6.0     6.3     6.2     6.3     7.0     6.9     7.0     7.1     7.3     7.6     7.5     7.2     30,521
Czech Republic  151.0   150.0   147.1   146.3   152.6   157.4   166.9   163.0   172.5   165.8   166.5   169.3   170.5   173.1   173.1   173.1   174.2   170.8   163.5   155.1   140.9   131.4   126.7   120.2   123.7   125.6   124.0   117.6   110.9   121.9   121.4   117.2   120.7   121.8   119.6   120.7   122.0   117.3   110.1   114.5   26,114
  Denmark       55.0    57.1    56.0    49.8    52.5    58.1    59.7    59.2    62.7    62.5    52.5    54.6    51.3    52.9    60.5    61.1    59.3    55.5    49.8    50.4    60.5    54.8    57.1    61.0    58.0    71.2    61.6    57.7    54.6    50.6    52.2    51.9    57.1    51.6    48.3    56.0    51.4    48.4    46.7    47.0    66,196
  Estonia       0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     36.1    32.1    23.5    18.0    17.8    16.1    17.0    16.5    16.0    14.9    14.6    15.1    14.6    16.6    16.7    16.9    15.5    19.3    17.7    14.7    18.5    25,260
  Finland       39.8    43.7    48.0    44.5    44.4    50.5    50.2    54.7    54.4    55.2    46.0    44.5    43.2    44.4    48.6    49.5    53.8    53.1    52.9    54.4    55.9    53.7    54.8    61.4    56.0    62.2    60.1    56.8    56.1    55.1    60.3    63.0    70.8    67.2    55.2    66.8    65.0    57.0    55.0    62.9    54,869
  France        431.9   448.6   484.8   464.6   430.6   469.3   455.3   474.7   481.8   461.4   414.1   396.7   381.0   369.5   360.3   347.8   342.3   340.5   355.9   352.3   379.6   368.0   348.9   344.4   353.8   368.6   361.7   385.3   377.7   376.9   383.8   375.9   385.2   385.4   388.4   379.6   373.1   370.2   351.4   357.8   46,493
  Germany       978.6   1003.2  1053.1  1028.5  975.5   1032.2  1017.2  1055.9  1103.6  1055.6  1022.3  982.3   983.9   1006.1  1014.6  1016.3  1007.2  1001.2  976.8   949.7   924.8   886.5   879.9   868.5   867.8   896.5   865.8   858.9   826.9   825.0   843.3   830.7   839.8   840.8   809.0   820.9   796.3   800.1   747.1   761.6   53,276

Мой код для пузырькового графика:

ggplot(europe.gdp, aes(europe.gdp$`GDP per capita`, europe.gdp$CO2.per.capita, size = europe.gdp$CO2.per.capita, color = europe.gdp$`Country/Region`)) +geom_point() +scale_x_log10() +theme_bw() +labs(title = 'Year: {frame_time}', x = 'GDP per capita', y = 'CO2 emissions/ tonnes per capita') +transition_time('Year: {frame_time}) +ease_aes('linear')

, где C02.per.capita данные во главе с годами. Однако я продолжаю получать эту ошибку:

no non-missing arguments to min; returning Infno non-missing arguments to max; returning -InfError in seq.default(range[1], range[2], length.out = nframes) : 
  'from' must be a finite number

Что это значит и как ее исправить? Я очень новичок в r, поэтому прошу прощения, если это действительно просто исправить.

Answer 1

Проблема заключается в том, что функции transition_time необходимо получить переменную в ваших данных, которая сообщает ей, какой это год, но вы ее не указали.

По сути, ваши данные находятся в неправильный формат для этого. Вам нужно начать с переключения с широкоформатного кадра данных на длинноформатный.

Это означает, что вместо столбцов с CO2 по годам у вас есть один столбец для страны / региона, один столбец для CO2 и один столбец для ВВП. Страны и ВВП будут повторяться один раз в год. Мы можем сделать это с помощью пакетов dplyr и tidyr:

library(tidyr)
library(dplyr)
library(ggplot2)
library(gganimate)

df <- europe.gdp                                                    %>% 
      group_by(`Country/Region`)                                    %>%
      gather(key = "Year", value = "CO2", 
             -`Country/Region`, -`GDP per Capita`, -CO2.per.capita) %>% 
      as.data.frame
df$GDP <- rep(europe.gdp$`GDP per Capita`, 40)
df$Year <- as.numeric(df$Year)

Теперь вы можете использовать Год в качестве переменной анимации:

ggplot(data = df, 
       aes(x     = GDP, 
           y     = CO2, 
           size  = CO2, 
           color = `Country/Region`)) + 
  geom_point()                        + 
  scale_x_log10()                     +
  theme_bw()                          +
  labs(title = 'Year: {frame_time}', 
       x     = 'GDP per capita', 
       y     = 'CO2 emissions/ tonnes per capita') + 
  transition_time(Year) + ease_aes('linear')

Вот воспроизводимые данные, снятые с вопроса и комментариев:

europe.gdp <- structure(list(`Country/Region` = c("Albania", "Austria", "Belarus", 
"Belgium", "Bosnia", "Bulgaria", "Croatia", "Cyprus", "Czech Republic", 
"Denmark", "Estonia", "Finland", "France", "Germany"), `1971` = c(3.9, 
48.7, 0, 116.8, 0, 62.8, 0, 1.8, 151, 55, 0, 39.8, 431.9, 978.6
), `1972` = c(4.5, 50.5, 0, 126.7, 0, 64.8, 0, 2.2, 150, 57.1, 
0, 43.7, 448.6, 1003.2), `1973` = c(3.9, 54, 0, 132.7, 0, 66.6, 
0, 2.3, 147.1, 56, 0, 48, 484.8, 1053.1), `1974` = c(4.2, 51.3, 
0, 130.6, 0, 67.7, 0, 1.8, 146.3, 49.8, 0, 44.5, 464.6, 1028.5
), `1975` = c(4.5, 50.2, 0, 115.6, 0, 72.2, 0, 1.7, 152.6, 52.5, 
0, 44.4, 430.6, 975.5), `1976` = c(4.9, 54.3, 0, 124.5, 0, 72.1, 
0, 2, 157.4, 58.1, 0, 50.5, 469.3, 1032.2), `1977` = c(5.2, 51.8, 
0, 123.5, 0, 74.8, 0, 2.1, 166.9, 59.7, 0, 50.2, 455.3, 1017.2
), `1978` = c(6.2, 54.5, 0, 129, 0, 77.9, 0, 2.3, 163, 59.2, 
0, 54.7, 474.7, 1055.9), `1979` = c(7.5, 57.2, 0, 132.3, 0, 81.1, 
0, 2.5, 172.5, 62.7, 0, 54.4, 481.8, 1103.6), `1980` = c(7.6, 
55.7, 0, 125.7, 0, 83.8, 0, 2.6, 165.8, 62.5, 0, 55.2, 461.4, 
1055.6), `1981` = c(6.4, 52.8, 0, 115.5, 0, 79.9, 0, 2.5, 166.5, 
52.5, 0, 46, 414.1, 1022.3), `1982` = c(6.7, 51, 0, 109.3, 0, 
81.5, 0, 2.6, 169.3, 54.6, 0, 44.5, 396.7, 982.3), `1983` = c(7.3, 
51.1, 0, 100.6, 0, 80.2, 0, 2.7, 170.5, 51.3, 0, 43.2, 381, 983.9
), `1984` = c(7.6, 52.9, 0, 102.6, 0, 78.3, 0, 2.8, 173.1, 52.9, 
0, 44.4, 369.5, 1006.1), `1985` = c(7.2, 54.3, 0, 101.9, 0, 81.1, 
0, 2.8, 173.1, 60.5, 0, 48.6, 360.3, 1014.6), `1986` = c(7.2, 
53.2, 0, 102.6, 0, 82.1, 0, 3.1, 173.1, 61.1, 0, 49.5, 347.8, 
1016.3), `1987` = c(7.5, 54.2, 0, 102.8, 0, 83.1, 0, 3.6, 174.2, 
59.3, 0, 53.8, 342.3, 1007.2), `1988` = c(7.6, 52.1, 0, 104.6, 
0, 82.1, 0, 3.6, 170.8, 55.5, 0, 53.1, 340.5, 1001.2), `1989` = c(7.2, 
52.5, 0, 105.9, 0, 81.4, 0, 3.8, 163.5, 49.8, 0, 52.9, 355.9, 
976.8), `1990` = c(6.3, 56.4, 124.5, 107.9, 23.7, 74.8, 21.6, 
3.8, 155.1, 50.4, 36.1, 54.4, 352.3, 949.7), `1991` = c(4.4, 
60.6, 119.4, 113.3, 21.2, 56.4, 15.7, 4.4, 140.9, 60.5, 32.1, 
55.9, 379.6, 924.8), `1992` = c(2.8, 55.7, 98.8, 112.3, 15.6, 
54.1, 15.2, 4.7, 131.4, 54.8, 23.5, 53.7, 368, 886.5), `1993` = c(2.3, 
56, 82.9, 109.8, 13.1, 55.1, 15.8, 4.9, 126.7, 57.1, 18, 54.8, 
348.9, 879.9), `1994` = c(2.3, 56.2, 70.2, 115.5, 3, 52.5, 15, 
5.3, 120.2, 61, 17.8, 61.4, 344.4, 868.5), `1995` = c(1.9, 59.4, 
61.4, 115.2, 3.2, 53.2, 15.8, 5.2, 123.7, 58, 16.1, 56, 353.8, 
867.8), `1996` = c(1.9, 63.1, 62.7, 121.3, 4.1, 53.8, 15.6, 5.5, 
125.6, 71.2, 17, 62.2, 368.6, 896.5), `1997` = c(1.4, 62.4, 61.8, 
118.5, 8.3, 50.9, 17.3, 5.7, 124, 61.6, 16.5, 60.1, 361.7, 865.8
), `1998` = c(1.7, 62.9, 59.3, 120.9, 10.5, 48.7, 18.4, 5.8, 
117.6, 57.7, 16, 56.8, 385.3, 858.9), `1999` = c(3, 61.4, 57.6, 
117.4, 10.2, 42.8, 18.3, 6, 110.9, 54.6, 14.9, 56.1, 377.7, 826.9
), `2000` = c(3.1, 61.7, 58.7, 118.6, 13.5, 42.1, 17.7, 6.3, 
121.9, 50.6, 14.6, 55.1, 376.9, 825), `2001` = c(3.3, 65.9, 57.8, 
119.1, 13.3, 44.8, 18.6, 6.2, 121.4, 52.2, 15.1, 60.3, 383.8, 
843.3), `2002` = c(3.8, 67.4, 59.2, 111.9, 14, 42, 19.6, 6.3, 
117.2, 51.9, 14.6, 63, 375.9, 830.7), `2003` = c(4, 72.6, 60.7, 
119.5, 14.3, 46.3, 21, 7, 120.7, 57.1, 16.6, 70.8, 385.2, 839.8
), `2004` = c(4.3, 73.7, 63, 116.5, 15, 45.4, 20.4, 6.9, 121.8, 
51.6, 16.7, 67.2, 385.4, 840.8), `2005` = c(4.1, 74.6, 62.1, 
112.6, 15.6, 45.9, 20.8, 7, 119.6, 48.3, 16.9, 55.2, 388.4, 809
), `2006` = c(4, 72.5, 66.2, 109.6, 17.2, 47.3, 20.8, 7.1, 120.7, 
56, 15.5, 66.8, 379.6, 820.9), `2007` = c(4, 70, 64, 105.6, 18.2, 
50.4, 22.1, 7.3, 122, 51.4, 19.3, 65, 373.1, 796.3), `2008` = c(3.9, 
70.6, 64.5, 111, 19.9, 49, 21, 7.6, 117.3, 48.4, 17.7, 57, 370.2, 
800.1), `2009` = c(3.5, 63.5, 62.3, 100.7, 19.4, 42.2, 19.8, 
7.5, 110.1, 46.7, 14.7, 55, 351.4, 747.1), `2010` = c(3.8, 69.3, 
65.3, 106.4, 19.9, 43.8, 19, 7.2, 114.5, 47, 18.5, 62.9, 357.8, 
761.6), `GDP per Capita` = c(5626, 56259, 6575, 51237, 6140, 
9811, 15533, 30521, 26114, 66196, 25260, 54869, 46493, 53276), 
    CO2.per.capita = c(186.9, 2358.2, 1482.4, 4586.8, 293.2, 
    2495, 389.5, 176.5, 5690, 2218.2, 388.2, 2171.1, 15679.1, 
    37054)), row.names = c(NA, -14L), class = "data.frame")