ggplot2 error message: Error in seq.default(range[1], range[2], length.out = nframes) : 'from' must be a finite number

Question

I am trying to make an animated bubble plot of the following data:

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

My code for the bubble plot is:

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')

where C02.per.capita is the data headed by the years. However I keep getting this error:

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

What does this mean and how do I fix it? I am very new to r, so I am sorry if this is really simple to fix.

Answer 1

The problem is that the transition_time function needs to receive a variable in your data that tells it what year it is, but you haven't given it one.

Essentially, your data is in the wrong format for this. You need to start by switching from a wide-format dataframe to a long-format dataframe.

This means instead of having columns with CO2 by year, you have a single column for Country/Region, a single columns for CO2 and a single column for GDP. The countries and GDPs will be repeated once for every year. We can do this with the dplyr and tidyr packages:

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)

Now you can use the Year as the animating variable:

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')

Here is the reproducible data stripped from the question and comments:

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")