5  Lösungen Dinojudo

5.1 Lösung 1

# Aufgabe 1 

library(tidyverse)

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.4     ✔ readr     2.1.5
✔ forcats   1.0.0     ✔ stringr   1.5.1
✔ ggplot2   3.5.1     ✔ tibble    3.2.1
✔ lubridate 1.9.3     ✔ tidyr     1.3.1
✔ purrr     1.0.2     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

#1.1
library(readr)
Jurassic_Park <- read_csv("https://raw.githubusercontent.com/raphaelbalzer/Tutorium_QM1_SoSe23/main/Jurassic_Park.csv")

New names:
Rows: 291 Columns: 11
── Column specification
──────────────────────────────────────────────────────── Delimiter: "," chr
(9): name, diet, period, lived_in, type, taxonomy, named_by, species, link dbl
(2): ...1, Length
ℹ Use `spec()` to retrieve the full column specification for this data. ℹ
Specify the column types or set `show_col_types = FALSE` to quiet this message.
• `` -> `...1`

#1.2
head(Jurassic_Park, n = 10)

ABCDEFGHIJ0123456789

...1 <dbl>	name <chr>	diet <chr>
19	confuciusornis	carnivorous
20	shanag	carnivorous
21	archaeopteryx	carnivorous
22	microceratus	herbivorous
23	compsognathus	carnivorous
24	micropachycephalosaurus	herbivorous
25	shuvuuia	omnivorous
26	gasparinisaura	herbivorous
27	juravenator	carnivorous
28	microraptor	carnivorous

1-10 of 10 rows | 1-3 of 11 columns

#1.3
tail(Jurassic_Park, n = 10)

ABCDEFGHIJ0123456789

...1 <dbl>	name <chr>	diet <chr>
300	lurdusaurus	herbivorous
301	maiasaura	herbivorous
302	malawisaurus	herbivorous
303	megalosaurus	carnivorous
304	poekilopleuron	carnivorous
305	saurolophus	herbivorous
306	sonidosaurus	herbivorous
307	stegosaurus	herbivorous
308	triceratops	herbivorous
309	yimenosaurus	herbivorous

1-10 of 10 rows | 1-3 of 11 columns

5.2 Lösung 2

# Aufgabe 2

#2.1
Jurassic_Park2 <- Jurassic_Park %>% 
  select(name, diet,lived_in,type,Length, species, named_by)

#2.2
Jurassic_Park2 %>% 
  arrange(-Length) -> Jurassic_Park2

#2.3
Jurassic_Park2 %>% 
  count(Length > 7.5)

ABCDEFGHIJ0123456789

Length > 7.5 <lgl>	n <int>
FALSE	191
TRUE	100

2 rows

5.3 Lösung 3

# Aufgabe 3

#3.1
Jurassic_Park %>% 
  summarise(mean(Length))

ABCDEFGHIJ0123456789

mean(Length) <dbl>
7.200584

1 row

#3.2
Jurassic_Park %>% 
  count(diet)

ABCDEFGHIJ0123456789

diet <chr>	n <int>
carnivorous	92
herbivorous	170
herbivorous/omnivorous	1
omnivorous	27
unknown	1

5 rows

#3.3
Jurassic_Park2 %>% 
  select(named_by, name) %>% 
  filter(name == "gobisaurus")

ABCDEFGHIJ0123456789

named_by <chr>	name <chr>
Vickaryous Russell Currie and Zhao (2001)	gobisaurus

1 row

5.4 Lösung 4

#4.1
Jurassic_Park %>% 
  group_by(diet) %>% 
  summarise(mean(Length))

ABCDEFGHIJ0123456789

diet <chr>	mean(Length) <dbl>
carnivorous	5.193696
herbivorous	8.898824
herbivorous/omnivorous	5.150000
omnivorous	3.651852
unknown	1.000000

5 rows

#4.2
Jurassic_Park %>% 
  select(type, lived_in) %>% 
  filter(type == "armoured dinosaur") %>% 
  count(lived_in)

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lived_in <chr>	n <int>
Australia	1
Canada	1
China	4
Germany	1
Mongolia	4
Spain	1
Tanzania	1
USA	12
United Kingdom	4

9 rows

#4.3
Jurassic_Park %>% 
  select(Length, type) %>% 
  filter(type == "small theropod") %>% 
  arrange(Length)

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Length <dbl>	type <chr>
0.25	small theropod
0.45	small theropod
0.50	small theropod
0.60	small theropod
0.65	small theropod
0.80	small theropod
0.80	small theropod
0.90	small theropod
1.00	small theropod
1.00	small theropod

Next

123456

Previous

1-10 of 59 rows

#4.4
Jurassic_Park %>% 
  select(diet, lived_in) %>%
  filter(lived_in == "USA") %>% 
  count(diet)

ABCDEFGHIJ0123456789

diet <chr>	n <int>
carnivorous	20
herbivorous	53
omnivorous	2

3 rows

5.5 Lösung 5

# Dino1
Jurassic_Park %>% 
  select(type, diet, lived_in, Length) %>% 
  filter(lived_in == "North Africa",
         type == "large theropod",
         diet == "carnivorous") %>%
  summarise(mean(Length))

ABCDEFGHIJ0123456789

mean(Length) <dbl>
15

1 row

# Dino2
Jurassic_Park %>% 
  select(type, diet, lived_in, Length) %>% 
  filter(lived_in == "China",
         type == "sauropod",
         diet == "herbivorous") %>%
  summarise(mean(Length))

ABCDEFGHIJ0123456789

mean(Length) <dbl>
11.58333

1 row