iso2c iso3c country year gdp_percap population birth_rate neonat_mortal_rate
1 AD AND Andorra 1996 NA 64291 10.9 2.8
2 AD AND Andorra 1994 NA 62707 10.9 3.2
3 AD AND Andorra 2003 NA 74783 10.3 2.0
4 AD AND Andorra 1990 NA 54511 11.9 4.3
5 AD AND Andorra 2009 NA 85474 9.9 1.7
6 AD AND Andorra 2011 NA 82326 NA 1.6
region income
1 Europe & Central Asia High income
2 Europe & Central Asia High income
3 Europe & Central Asia High income
4 Europe & Central Asia High income
5 Europe & Central Asia High income
6 Europe & Central Asia High income
Creating the new variable
When you click the Render button a document will be generated that includes both content and the output of embedded code. You can embed code like this:
iso2c iso3c country year gdp_percap population birth_rate neonat_mortal_rate
1 AD AND Andorra 1996 NA 64291 10.9 2.8
2 AD AND Andorra 1994 NA 62707 10.9 3.2
3 AD AND Andorra 2003 NA 74783 10.3 2.0
4 AD AND Andorra 1990 NA 54511 11.9 4.3
5 AD AND Andorra 2009 NA 85474 9.9 1.7
6 AD AND Andorra 2011 NA 82326 NA 1.6
region income gdp_trillions
1 Europe & Central Asia High income NA
2 Europe & Central Asia High income NA
3 Europe & Central Asia High income NA
4 Europe & Central Asia High income NA
5 Europe & Central Asia High income NA
6 Europe & Central Asia High income NA
Creating First Chart
nations2 <- nations |>filter(country =="China"| country =="Germany"| country =="Japan"| country =="United States")nations2
iso2c iso3c country year gdp_percap population birth_rate
1 CN CHN China 1992 1260.162 1164970000 18.270000
2 CN CHN China 2005 5053.379 1303720000 12.400000
3 CN CHN China 2000 2915.415 1262645000 14.030000
4 CN CHN China 1991 1091.449 1150780000 19.680000
5 CN CHN China 2013 12218.521 1357380000 12.080000
6 CN CHN China 1999 2649.745 1252735000 14.640000
7 CN CHN China 2014 13254.643 1364270000 12.400000
8 CN CHN China 2003 3933.599 1288400000 12.410000
9 CN CHN China 2004 4422.650 1296075000 12.290000
10 CN CHN China 1993 1453.159 1178440000 18.090000
11 CN CHN China 2009 8290.089 1331260000 12.130000
12 CN CHN China 2010 9238.755 1337705000 11.900000
13 CN CHN China 2011 10274.494 1344130000 11.930000
14 CN CHN China 1996 2060.030 1217550000 16.980000
15 CN CHN China 1997 2265.314 1230075000 16.570000
16 CN CHN China 1998 2446.150 1241935000 15.640000
17 CN CHN China 1990 979.979 1135185000 21.060000
18 CN CHN China 2001 3205.927 1271850000 13.380000
19 CN CHN China 2002 3527.352 1280400000 12.860000
20 CN CHN China 2006 5836.833 1311020000 12.090000
21 CN CHN China 1994 1659.313 1191835000 17.700000
22 CN CHN China 2008 7569.680 1324655000 12.140000
23 CN CHN China 1995 1859.830 1204855000 17.120000
24 CN CHN China 2012 11219.928 1350695000 12.100000
25 CN CHN China 2007 6807.112 1317885000 12.100000
26 DE DEU Germany 1997 24183.862 82034771 9.900000
27 DE DEU Germany 1990 19032.696 79433029 11.400000
28 DE DEU Germany 1996 23655.820 81914831 9.700000
29 DE DEU Germany 1992 21230.248 80624598 10.000000
30 DE DEU Germany 1993 21386.501 81156363 9.800000
31 DE DEU Germany 2003 29362.425 82534176 8.600000
32 DE DEU Germany 1995 23093.601 81678051 9.400000
33 DE DEU Germany 1994 22300.868 81438348 9.500000
34 DE DEU Germany 2010 39639.480 81776930 8.300000
35 DE DEU Germany 2007 36777.783 82266372 8.300000
36 DE DEU Germany 2005 32184.055 82469422 8.300000
37 DE DEU Germany 2013 44184.823 82132753 8.300000
38 DE DEU Germany 2009 37112.881 81902307 8.100000
39 DE DEU Germany 1998 24871.241 82047195 9.600000
40 DE DEU Germany 2011 42142.549 81797673 8.100000
41 DE DEU Germany 2001 27725.110 82349925 8.900000
42 DE DEU Germany 2002 28435.901 82488495 8.700000
43 DE DEU Germany 1991 20520.739 80013896 10.400000
44 DE DEU Germany 2006 34690.333 82376451 8.200000
45 DE DEU Germany 2004 30694.902 82516260 8.600000
46 DE DEU Germany 2012 43600.113 80425823 8.400000
47 DE DEU Germany 2014 46393.877 80982500 8.600000
48 DE DEU Germany 2008 38438.741 82110097 8.300000
49 DE DEU Germany 2000 26630.511 82211508 9.300000
50 DE DEU Germany 1999 25798.280 82100243 9.400000
51 JP JPN Japan 1992 21052.319 124229000 9.800000
52 JP JPN Japan 2002 27241.103 127445000 9.300000
53 JP JPN Japan 2008 33495.178 128063000 8.700000
54 JP JPN Japan 2001 26559.532 127149000 9.300000
55 JP JPN Japan 2007 33313.865 128001000 8.630000
56 JP JPN Japan 1998 24328.820 126400000 9.600000
57 JP JPN Japan 1993 21536.856 124536000 9.600000
58 JP JPN Japan 1999 24606.921 126631000 9.300000
59 JP JPN Japan 1997 24626.417 126057000 9.500000
60 JP JPN Japan 2005 30441.348 127773000 8.413292
61 JP JPN Japan 2014 36577.211 127131800 8.000000
62 JP JPN Japan 2004 29377.344 127761000 8.693605
63 JP JPN Japan 2000 25938.198 126843000 9.400000
64 JP JPN Japan 2012 35735.617 127561489 8.200000
65 JP JPN Japan 1991 20466.647 123921000 9.900000
66 JP JPN Japan 2010 33760.977 128070000 8.500000
67 JP JPN Japan 2011 34335.304 127817277 8.300000
68 JP JPN Japan 2009 31857.372 128047000 8.500000
69 JP JPN Japan 2013 36618.306 127338621 8.200000
70 JP JPN Japan 1996 23888.613 125757000 9.600000
71 JP JPN Japan 1990 19229.666 123537000 10.000000
72 JP JPN Japan 1994 22109.681 124961000 10.000000
73 JP JPN Japan 2003 27941.176 127718000 9.200000
74 JP JPN Japan 2006 31790.655 127854000 8.650000
75 JP JPN Japan 1995 22921.541 125439000 9.540000
76 US USA United States 2001 37273.618 284968955 14.100000
77 US USA United States 2008 48401.427 304093966 14.000000
78 US USA United States 2002 38166.038 287625193 14.000000
79 US USA United States 1999 34620.929 279040000 14.200000
80 US USA United States 2009 47001.555 306771529 13.500000
81 US USA United States 2007 48061.538 301231207 14.300000
82 US USA United States 2003 39677.198 290107933 14.100000
83 US USA United States 2000 36449.855 282162411 14.400000
84 US USA United States 1998 32949.198 275854000 14.300000
85 US USA United States 1996 30068.231 269394000 14.400000
86 US USA United States 1990 23954.479 249623000 16.700000
87 US USA United States 1991 24405.165 252981000 16.200000
88 US USA United States 2012 51433.047 314102623 12.600000
89 US USA United States 2013 52660.295 316427395 12.400000
90 US USA United States 2010 48374.087 309346863 13.000000
91 US USA United States 1997 31572.690 272657000 14.200000
92 US USA United States 1992 25492.952 256514000 15.800000
93 US USA United States 1993 26464.853 259919000 15.400000
94 US USA United States 2006 46437.067 298379912 14.300000
95 US USA United States 2014 54398.460 318907401 12.500000
96 US USA United States 2011 49781.801 311718857 12.700000
97 US USA United States 2004 41921.810 292805298 14.000000
98 US USA United States 1994 27776.636 263126000 15.000000
99 US USA United States 1995 28782.175 266278000 14.600000
100 US USA United States 2005 44307.921 295516599 14.000000
neonat_mortal_rate region income gdp_trillions
1 29.4 East Asia & Pacific Upper middle income 1.468052
2 14.0 East Asia & Pacific Upper middle income 6.588191
3 21.2 East Asia & Pacific Upper middle income 3.681134
4 29.7 East Asia & Pacific Upper middle income 1.256017
5 6.3 East Asia & Pacific Upper middle income 16.585176
6 22.2 East Asia & Pacific Upper middle income 3.319429
7 5.9 East Asia & Pacific Upper middle income 18.082912
8 17.1 East Asia & Pacific Upper middle income 5.068050
9 15.5 East Asia & Pacific Upper middle income 5.732087
10 28.8 East Asia & Pacific Upper middle income 1.712461
11 9.1 East Asia & Pacific Upper middle income 11.036264
12 8.2 East Asia & Pacific Upper middle income 12.358729
13 7.5 East Asia & Pacific Upper middle income 13.810256
14 25.7 East Asia & Pacific Upper middle income 2.508189
15 24.4 East Asia & Pacific Upper middle income 2.786506
16 23.3 East Asia & Pacific Upper middle income 3.037959
17 29.7 East Asia & Pacific Upper middle income 1.112457
18 20.1 East Asia & Pacific Upper middle income 4.077459
19 18.6 East Asia & Pacific Upper middle income 4.516421
20 12.6 East Asia & Pacific Upper middle income 7.652205
21 28.0 East Asia & Pacific Upper middle income 1.977627
22 10.1 East Asia & Pacific Upper middle income 10.027214
23 26.9 East Asia & Pacific Upper middle income 2.240826
24 6.9 East Asia & Pacific Upper middle income 15.154700
25 11.3 East Asia & Pacific Upper middle income 8.970991
26 2.9 Europe & Central Asia High income: OECD 1.983918
27 3.4 Europe & Central Asia High income: OECD 1.511825
28 3.0 Europe & Central Asia High income: OECD 1.937762
29 3.5 Europe & Central Asia High income: OECD 1.711680
30 3.3 Europe & Central Asia High income: OECD 1.735651
31 2.7 Europe & Central Asia High income: OECD 2.423404
32 3.1 Europe & Central Asia High income: OECD 1.886240
33 3.2 Europe & Central Asia High income: OECD 1.816146
34 2.3 Europe & Central Asia High income: OECD 3.241595
35 2.5 Europe & Central Asia High income: OECD 3.025575
36 2.6 Europe & Central Asia High income: OECD 2.654200
37 2.2 Europe & Central Asia High income: OECD 3.629021
38 2.4 Europe & Central Asia High income: OECD 3.039631
39 2.9 Europe & Central Asia High income: OECD 2.040616
40 2.3 Europe & Central Asia High income: OECD 3.447162
41 2.7 Europe & Central Asia High income: OECD 2.283161
42 2.7 Europe & Central Asia High income: OECD 2.345635
43 3.5 Europe & Central Asia High income: OECD 1.641944
44 2.6 Europe & Central Asia High income: OECD 2.857667
45 2.6 Europe & Central Asia High income: OECD 2.532829
46 2.3 Europe & Central Asia High income: OECD 3.506575
47 2.2 Europe & Central Asia High income: OECD 3.757092
48 2.4 Europe & Central Asia High income: OECD 3.156209
49 2.8 Europe & Central Asia High income: OECD 2.189334
50 2.8 Europe & Central Asia High income: OECD 2.118045
51 2.4 East Asia & Pacific High income: OECD 2.615309
52 1.7 East Asia & Pacific High income: OECD 3.471742
53 1.2 East Asia & Pacific High income: OECD 4.289493
54 1.7 East Asia & Pacific High income: OECD 3.377018
55 1.3 East Asia & Pacific High income: OECD 4.264208
56 1.9 East Asia & Pacific High income: OECD 3.075163
57 2.3 East Asia & Pacific High income: OECD 2.682114
58 1.8 East Asia & Pacific High income: OECD 3.115999
59 2.0 East Asia & Pacific High income: OECD 3.104332
60 1.4 East Asia & Pacific High income: OECD 3.889582
61 1.0 East Asia & Pacific High income: OECD 4.650127
62 1.5 East Asia & Pacific High income: OECD 3.753279
63 1.8 East Asia & Pacific High income: OECD 3.290079
64 1.0 East Asia & Pacific High income: OECD 4.558488
65 2.5 East Asia & Pacific High income: OECD 2.536247
66 1.1 East Asia & Pacific High income: OECD 4.323768
67 1.0 East Asia & Pacific High income: OECD 4.388645
68 1.2 East Asia & Pacific High income: OECD 4.079241
69 1.0 East Asia & Pacific High income: OECD 4.662925
70 2.1 East Asia & Pacific High income: OECD 3.004160
71 2.5 East Asia & Pacific High income: OECD 2.375575
72 2.2 East Asia & Pacific High income: OECD 2.762848
73 1.6 East Asia & Pacific High income: OECD 3.568591
74 1.3 East Asia & Pacific High income: OECD 4.064562
75 2.2 East Asia & Pacific High income: OECD 2.875255
76 4.6 North America High income: OECD 10.621824
77 4.3 North America High income: OECD 14.718582
78 4.6 North America High income: OECD 10.977514
79 4.6 North America High income: OECD 9.660624
80 4.2 North America High income: OECD 14.418739
81 4.3 North America High income: OECD 14.477635
82 4.6 North America High income: OECD 11.510670
83 4.6 North America High income: OECD 10.284779
84 4.7 North America High income: OECD 9.089168
85 4.9 North America High income: OECD 8.100201
86 5.8 North America High income: OECD 5.979589
87 5.6 North America High income: OECD 6.174043
88 3.9 North America High income: OECD 16.155255
89 3.8 North America High income: OECD 16.663160
90 4.1 North America High income: OECD 14.964372
91 4.8 North America High income: OECD 8.608515
92 5.4 North America High income: OECD 6.539299
93 5.2 North America High income: OECD 6.878718
94 4.4 North America High income: OECD 13.855888
95 3.7 North America High income: OECD 17.348072
96 4.0 North America High income: OECD 15.517926
97 4.5 North America High income: OECD 12.274928
98 5.1 North America High income: OECD 7.308755
99 5.0 North America High income: OECD 7.664060
100 4.5 North America High income: OECD 13.093726
c1 <- nations2 |>ggplot(aes(x = year, y = gdp_trillions, color = country)) +geom_line() +geom_point()+scale_color_brewer(palette ="Set1") +scale_y_continuous(name ="GPD (Trillions of $)") +scale_x_continuous(name ="Year") +labs(title ="China's Rise to Become the Largest Economy") +theme_minimal()c1
`summarise()` has grouped output by 'region'. You can override using the
`.groups` argument.
nations3
# A tibble: 175 × 3
# Groups: region [7]
region year GDP
<chr> <int> <dbl>
1 East Asia & Pacific 1990 5.52
2 East Asia & Pacific 1991 6.03
3 East Asia & Pacific 1992 6.50
4 East Asia & Pacific 1993 7.04
5 East Asia & Pacific 1994 7.64
6 East Asia & Pacific 1995 8.29
7 East Asia & Pacific 1996 8.96
8 East Asia & Pacific 1997 9.55
9 East Asia & Pacific 1998 9.60
10 East Asia & Pacific 1999 10.1
# ℹ 165 more rows
c2 <- nations3 |>ggplot(aes(x = year, y = GDP, fill = region)) +geom_area(color ="white", size =0.1) +scale_fill_brewer(palette ="Set2") +scale_x_continuous(name ="Year") +scale_y_continuous(name ="GPD ($ trillion)" ) +labs(title ="GPD by World Bank Region") +theme_minimal()
Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
ℹ Please use `linewidth` instead.
