BC3203
Question 1: Your answer should be a function called gapminder_1972. When run like this;
gapminder_1972(gapminder)
it should produce the following outputs;
## # A tibble: 142 × 6
## country continent year lifeExp pop gdpPercap
## <fct> <fct> <int> <dbl> <int> <dbl>
## 1 Afghanistan Asia 1972 36.1 13079460 740.
## 2 Albania Europe 1972 67.7 2263554 3313.
## 3 Algeria Africa 1972 54.5 14760787 4183.
## 4 Angola Africa 1972 37.9 5894858 5473.
## 5 Argentina Americas 1972 67.1 24779799 9443.
## 6 Australia Oceania 1972 71.9 13177000 16789.
## 7 Austria Europe 1972 70.6 7544201 16662.
## 8 Bahrain Asia 1972 63.3 230800 18269.
## 9 Bangladesh Asia 1972 45.3 70759295 630.
## 10 Belgium Europe 1972 71.4 9709100 16672.
## # ℹ 132 more rows
Question 2: Your answer should be a function called gdp. When run like this;
gdp(gapminder)
it should produce the following outputs;
## # A tibble: 1,704 × 7
## country continent year lifeExp pop gdpPercap gdp
## <fct> <fct> <int> <dbl> <int> <dbl> <dbl>
## 1 Afghanistan Asia 1952 28.8 8425333 779. 6567086330.
## 2 Afghanistan Asia 1957 30.3 9240934 821. 7585448670.
## 3 Afghanistan Asia 1962 32.0 10267083 853. 8758855797.
## 4 Afghanistan Asia 1967 34.0 11537966 836. 9648014150.
## 5 Afghanistan Asia 1972 36.1 13079460 740. 9678553274.
## 6 Afghanistan Asia 1977 38.4 14880372 786. 11697659231.
## 7 Afghanistan Asia 1982 39.9 12881816 978. 12598563401.
## 8 Afghanistan Asia 1987 40.8 13867957 852. 11820990309.
## 9 Afghanistan Asia 1992 41.7 16317921 649. 10595901589.
## 10 Afghanistan Asia 1997 41.8 22227415 635. 14121995875.
## # ℹ 1,694 more rows
Question 3: Your answer should be a function called gdp_2007. When run like this;
gdp_2007(gapminder)
it should produce the following outputs;
## # A tibble: 142 × 7
## country continent year lifeExp pop gdpPercap gdp
## <fct> <fct> <int> <dbl> <int> <dbl> <dbl>
## 1 Afghanistan Asia 2007 43.8 31889923 975. 31079291949.
## 2 Albania Europe 2007 76.4 3600523 5937. 21376411360.
## 3 Algeria Africa 2007 72.3 33333216 6223. 207444851958.
## 4 Angola Africa 2007 42.7 12420476 4797. 59583895818.
## 5 Argentina Americas 2007 75.3 40301927 12779. 515033625357.
## 6 Australia Oceania 2007 81.2 20434176 34435. 703658358894.
## 7 Austria Europe 2007 79.8 8199783 36126. 296229400691.
## 8 Bahrain Asia 2007 75.6 708573 29796. 21112675360.
## 9 Bangladesh Asia 2007 64.1 150448339 1391. 209311822134.
## 10 Belgium Europe 2007 79.4 10392226 33693. 350141166520.
## # ℹ 132 more rows
Question 4: Your answer should be a plot that looks like this;
Question 5: Your answer should be a plot that looks like this;
Question 6: Your answer should be a plot that looks like this;
Question 7: Your answer should be a plot that looks like this;
Question 8: Your answer should be a function called without_droids. When run like this;
without_droids(starwars)
it should produce the following outputs;
## # A tibble: 77 × 14
## name height mass hair_color skin_color eye_color birth_year sex gender
## <chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr> <chr>
## 1 Luke Sk… 172 77 blond fair blue 19 male mascu…
## 2 Darth V… 202 136 none white yellow 41.9 male mascu…
## 3 Leia Or… 150 49 brown light brown 19 fema… femin…
## 4 Owen La… 178 120 brown, gr… light blue 52 male mascu…
## 5 Beru Wh… 165 75 brown light blue 47 fema… femin…
## 6 Biggs D… 183 84 black light brown 24 male mascu…
## 7 Obi-Wan… 182 77 auburn, w… fair blue-gray 57 male mascu…
## 8 Anakin … 188 84 blond fair blue 41.9 male mascu…
## 9 Wilhuff… 180 NA auburn, g… fair blue 64 male mascu…
## 10 Chewbac… 228 112 brown unknown blue 200 male mascu…
## # ℹ 67 more rows
## # ℹ 5 more variables: homeworld <chr>, species <chr>, films <list>,
## # vehicles <list>, starships <list>
Question 9: Your answer should be a function called add_bmi. It adds a column called bmi according to this formula.
When run like this;
add_bmi(starwars)
it should produce the following outputs;
## # A tibble: 87 × 15
## name height mass hair_color skin_color eye_color birth_year sex gender
## <chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr> <chr>
## 1 Luke Sk… 172 77 blond fair blue 19 male mascu…
## 2 C-3PO 167 75 <NA> gold yellow 112 none mascu…
## 3 R2-D2 96 32 <NA> white, bl… red 33 none mascu…
## 4 Darth V… 202 136 none white yellow 41.9 male mascu…
## 5 Leia Or… 150 49 brown light brown 19 fema… femin…
## 6 Owen La… 178 120 brown, gr… light blue 52 male mascu…
## 7 Beru Wh… 165 75 brown light blue 47 fema… femin…
## 8 R5-D4 97 32 <NA> white, red red NA none mascu…
## 9 Biggs D… 183 84 black light brown 24 male mascu…
## 10 Obi-Wan… 182 77 auburn, w… fair blue-gray 57 male mascu…
## # ℹ 77 more rows
## # ℹ 6 more variables: homeworld <chr>, species <chr>, films <list>,
## # vehicles <list>, starships <list>, bmi <dbl>
Question 10: Your answer should produce a tibble that looks like this;
## # A tibble: 87 × 3
## name height mass
## <chr> <int> <dbl>
## 1 Luke Skywalker 172 77
## 2 C-3PO 167 75
## 3 R2-D2 96 32
## 4 Darth Vader 202 136
## 5 Leia Organa 150 49
## 6 Owen Lars 178 120
## 7 Beru Whitesun Lars 165 75
## 8 R5-D4 97 32
## 9 Biggs Darklighter 183 84
## 10 Obi-Wan Kenobi 182 77
## # ℹ 77 more rows
Question 11: Your answer should produce a tibble that looks like this;
## # A tibble: 49 × 2
## homeworld total_mass
## <chr> <dbl>
## 1 Alderaan NA
## 2 Aleen Minor 15
## 3 Bespin 79
## 4 Bestine IV 110
## 5 Cato Neimoidia 90
## 6 Cerea 82
## 7 Champala NA
## 8 Chandrila NA
## 9 Concord Dawn 79
## 10 Corellia 157
## # ℹ 39 more rows
Question 12: Your answer should produce a tibble that looks like this;
## # A tibble: 3 × 2
## gender num_characters
## <chr> <int>
## 1 feminine 17
## 2 masculine 66
## 3 <NA> 4
Question 13: Your answer should produce a tibble that looks like this;
## # A tibble: 176 × 4
## name species stat value
## <chr> <chr> <chr> <dbl>
## 1 Ackbar Mon Calamari birth_year 41
## 2 Ackbar Mon Calamari height 180
## 3 Ackbar Mon Calamari mass 83
## 4 Adi Gallia Tholothian height 184
## 5 Adi Gallia Tholothian mass 50
## 6 Anakin Skywalker Human birth_year 41.9
## 7 Anakin Skywalker Human height 188
## 8 Anakin Skywalker Human mass 84
## 9 Ayla Secura Twi'lek birth_year 48
## 10 Ayla Secura Twi'lek height 178
## # ℹ 166 more rows
Question 14: Your answer should be a plot that looks like this;
