Introduction to the Tidyverse
David Robinson
Chief Data Scientist, DataCamp
gapminder %>%
arrange(gdpPercap)
# A tibble: 1,704 x 6
country continent year lifeExp pop gdpPercap
<fct> <fct> <int> <dbl> <dbl> <dbl>
1 Congo, Dem. Rep. Africa 2002 44.966 55379852 241.1659
2 Congo, Dem. Rep. Africa 2007 46.462 64606759 277.5519
3 Lesotho Africa 1952 42.138 748747 298.8462
4 Guinea-Bissau Africa 1952 32.500 580653 299.8503
5 Congo, Dem. Rep. Africa 1997 42.587 47798986 312.1884
6 Eritrea Africa 1952 35.928 1438760 328.9406
7 Myanmar Asia 1952 36.319 20092996 331.0000
8 Lesotho Africa 1957 45.047 813338 335.9971
9 Burundi Africa 1952 39.031 2445618 339.2965
10 Eritrea Africa 1957 38.047 1542611 344.1619
# ... with 1,694 more rows
gapminder %>%
arrange(desc(gdpPercap))
# A tibble: 1,704 x 6
country continent year lifeExp pop gdpPercap
<fct> <fct> <int> <dbl> <dbl> <dbl>
1 Kuwait Asia 1957 58.033 212846 113523.13
2 Kuwait Asia 1972 67.712 841934 109347.87
3 Kuwait Asia 1952 55.565 160000 108382.35
4 Kuwait Asia 1962 60.470 358266 95458.11
5 Kuwait Asia 1967 64.624 575003 80894.88
6 Kuwait Asia 1977 69.343 1140357 59265.48
7 Norway Europe 2007 80.196 4627926 49357.19
8 Kuwait Asia 2007 77.588 2505559 47306.99
9 Singapore Asia 2007 79.972 4553009 47143.18
10 Norway Europe 2002 79.050 4535591 44683.98
# ... with 1,694 more rows
gapminder %>%
filter(year == 2007) %>%
arrange(desc(gdpPercap))
# A tibble: 142 x 6
country continent year lifeExp pop gdpPercap
<fct> <fct> <int> <dbl> <dbl> <dbl>
1 Norway Europe 2007 80.196 4627926 49357.19
2 Kuwait Asia 2007 77.588 2505559 47306.99
3 Singapore Asia 2007 79.972 4553009 47143.18
4 United States Americas 2007 78.242 301139947 42951.65
5 Ireland Europe 2007 78.885 4109086 40676.00
6 Hong Kong, China Asia 2007 82.208 6980412 39724.98
7 Switzerland Europe 2007 81.701 7554661 37506.42
8 Netherlands Europe 2007 79.762 16570613 36797.93
9 Canada Americas 2007 80.653 33390141 36319.24
10 Iceland Europe 2007 81.757 301931 36180.79
# ... with 132 more rows
Introduction to the Tidyverse