ggplot2 错误消息：seq.default(range[1], range[2], length.out = nframes) 中的错误：'from' 必须是有限数
ggplot2 error message: Error in seq.default(range[1], range[2], length.out = nframes) : 'from' must be a finite number
我正在尝试制作以下数据的动画气泡图：
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
我的气泡图代码是：
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')
其中C02.per.capita是以年份为首的数据。
但是我不断收到此错误：
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
这是什么意思，我该如何解决？
我是 r 的新手，所以如果这真的很容易修复，我很抱歉。
问题是 transition_time 函数需要在您的数据中接收一个变量，告诉它现在是哪一年，但您没有给它一个。
基本上，您的数据格式错误。您需要首先从宽格式数据帧切换到长格式数据帧。
这意味着不再有按年显示 CO2 的列，而是有 Country/Region 的单列、CO2 的单列和 GDP 的单列。国家和 GDP 将每年重复一次。我们可以使用 dplyr 和 tidyr 包来做到这一点：
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)
现在您可以使用年份作为动画变量：
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')
这是从问题和评论中删除的可重现数据：
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")
我正在尝试制作以下数据的动画气泡图：
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
我的气泡图代码是：
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')
其中C02.per.capita是以年份为首的数据。 但是我不断收到此错误：
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
这是什么意思，我该如何解决？ 我是 r 的新手，所以如果这真的很容易修复，我很抱歉。
问题是 transition_time 函数需要在您的数据中接收一个变量，告诉它现在是哪一年，但您没有给它一个。
基本上，您的数据格式错误。您需要首先从宽格式数据帧切换到长格式数据帧。
这意味着不再有按年显示 CO2 的列，而是有 Country/Region 的单列、CO2 的单列和 GDP 的单列。国家和 GDP 将每年重复一次。我们可以使用 dplyr 和 tidyr 包来做到这一点：
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)
现在您可以使用年份作为动画变量：
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')
这是从问题和评论中删除的可重现数据：
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")