TP: Environmental Risk

Work Sheet 1

Task 1.2

Take the palmerpenguins data set (saved as dat_penguins) and make a similar plot:

                                 
1   ggplot(data = ______,
2          aes(x = ______,
              y = ______,
3              col = ______)) +
4  geom_point(aes(shape = ______),
5             size = 3,
6             alpha = 0.8) +
7  geom_smooth(method = "lm", se = FALSE) +
8  scale_color_manual(values = c("darkorange","purple","cyan4")) +
9  labs(title = ______,
       x = ______,
       y = ______) +
10  theme_minimal()

1: Take the dat_penguins data set, and then,
2: Use bill_length_mm as x and bill_depth_mm as y axis
3: Use different colors for the different species
4: Add a point layer, use different point shapes for the different species
5: Define point size
6: and transparency
7: Add lines through the point clouds for each species (takes col = species from the 2
8: Define a manual color scale
9: Define the title, x, y axes, and a name for the colour legend
10: Add a theme

Task 1.3

Calculate the mean, standard deviation (sd()), and replicates (n()) of body_mass_gfor the different species and sexes in dat_penguins.

1dat_penguins %>%
2  group_by(______, ______) %>%
3  summarize(______ = ______,
            ______ = ______,
            ______ = ______)

1: Take the dat_penguins data
2: Group it by species and sex
3: Summarise for mean(), sd(), and n()

Task 1.4

Take the dat_penguins data and

calculate the mean body_mass_g per year and species
change the format from long to wide, year should be distributed across columns

1dat_penguins %>%
2  group_by(______, ______) %>%
3  summarise(______ = mean(______)) %>%
4  pivot_wider(names_from = ______,
5  values_from = ______)

1: Take the dat_penguins data
2: Group it by species and year
3: Calculate the mean() of body_mass_g
4: Transform into a wide data frame, take the column names from year
5: and the values from the mean body_mass_g

Task 1.4 Bonus

Why are there NA values and how can you avoid it?

Have a look at the actual data: