First, make sure you downloaded the tidyverse and are able to load it. Furthermore, you need to install the palmerpenguins package to access the data sets. Load both packages and check if you have any NAMESPACE conflicts.

# Insert code here



# End

My conflicts are stats::filter() and stats::lag(), which should not be an issue.

Have a look at the class and structure of the penguins_raw data set. Also, make yourself familiar with the columns. Since the data set is part of a package, you can also use the corresponding help page (? or F1).

# Insert code here



# End

Next, for easier data handling, clean the column names by removing all special characters (e.g., brackets, units, …) and replacing all white spaces with an underscore. Last, makle sure all column names are either all lower case or all upper case

# Insert code here



# End

Now, remove all rows that don’t have a measure for stable isotopes (both Delta 15 N or Delta 13 C). Save this into a new tibble.

# Insert code here



# End

Filter the data set to include only the 50% smallest individuals in terms of body mass. Select the individual id, species, the culmen dimensions, and the sex columns. Save this into a new tibble called penguins_small (or something similar).

# Insert code here



# End

Create a new column (culmen_class) in which each male individual with a culmen length larger than 50 mm is identified by 1, each female individual with a culmen length larger than 45 mm is identified by 2, and all other individuals are identified by 0.

# Insert code here



# End

Calculate the relative number (%) of individuals within each group and the ratio between the minimum culmen length and depth as well as between the maximum culmen length and depth. Add a sex_new column again (culmen_class 1 = "male", culmen_class 2 = "female", culmen_class 0 = "mixed). Save the result as penguings_sum.

# Insert code here



# End

Now, combine penguins and penguins_sum to one tibble using sex and sex_new as ID columns.

# Insert code here



# End

Reshape the penguins_small tibble from wide to long in a way that the culmen length and depth columns are tidy. The name of the new column specifying the information should be fun, the new column containing the values should be measurements. Save the results as penguins_small_long tibble.

# Insert code here



# End

Use the map function to fit a linear model (flipper_length_mm ~ body_mass_g) to the penguins data set, but seperated by species. Extract the R squared and p value and save the results in a data.frame that additionally includes the species. (Tip: Have a look at broom::glance, however, there are many ways to achieve this).

# Insert code here



# End