Data

The dataset for this assignment can be found as a csv file at here. The variable descriptions are as follows:

• name: A unique name given to the Pokémon
• species: The Pokémon’s type, e.g. Pidgey.
• cp: Pre-evolution Combat Power, which is a summary of the Pokémon’s strength for battling prior to the evolution of the Pokémon.
• hp: Pre-evolution Hit Points, which is a summary of how difficult it is to weaken the Pokémon in a battle.
• weight: Pre-evolution weight, in kilograms.
• height: Pre-evolution height, in meters.
• power_up_stardust: Pre-evolution stardust required to power up the Pokémon.
• power_up_candy: Pre-evolution candy required to power up the Pokémon.
• attack_weak: The name of the pre-evolution weaker attack of the Pokémon.
• attack_weak_type: The type of the pre-evolution weaker attack.
• attack_weak_value: The damage done by the pre-evolution weaker attack.
• attack_strong: The name of the pre-evolution stronger attack.
• attack_strong_type: The type of the pre-evolution stronger attack.
• attack_strong_value: The damage done by the pre-evolution stronger attack.
• cp_new: Post-evolution Combat Power.
• hp_new: Post-evolution Hit Points.
• weight_new: Post-evolution weight, in kilograms.
• height_new: Post-evolution height, in meters.
• power_up_stardust_new: Post-evolution stardust required to power up the Pokémon.
• power_up_candy_new: Post-evolution candy required to power up the Pokémon.
• attack_weak_new: The name of the post-evolution weaker attack.
• attack_weak_type_new: The type of the post-evolution weaker attack.
• attack_weak_value_new: The damage done by the post-evolution weaker attack.
• attack_strong_new: The name of the post-evolution stronger attack.
• attack_strong_type_new: The type of the post-evolution stronger attack.
• attack_strong_value_new: The damage done by the post-evolution stronger attack.
• notes: Any additional notes made while collecting the data.

Packages

In this lab we will work with the tidyverse and scales packages. This package has already been installed for you, and is loaded in your R Markdown file as well.

If you’d like to run your code in the Console as well you’ll also need to load the packages there. To do so, run the following in the console.

library(tidyverse) 
library(scales) 

Exercises

1. Calculate the diference in heights pre and post evolution and save this as a new variable, height_diff. Calculate the percentage of Pokémon that grew during evolution. Also visualize the distribution of change in height by species and provide a discussion of how change in height varies across species.

This is a good place to pause, commit changes with an informative commit message, and push. Make sure to commit and push all changed files.

2. Pick two categorical variables and make a bar plot that depicts the relationship between them. These can be variables from the original data or ones that you create based on the given data.

This is another good place to pause, commit changes with an informative commit message, and push. Make sure to commit and push all changed files.

3. Pick a numerical and a categorical variable, and construct side-by-side box plots depicting the relationship between them.

Don’t forget to commit and push your changes sporadically while working on your homework assignment.

4. Learn something new: violin plots! Read about them at http://ggplot2.tidyverse.org/reference/geom_violin.html, and convert your side-by-side box plots from the previous task to violin plots. What do the violin plots reveal that box plots do not? What features are apparent in the box plots but not in the violin plots?

5. Recreate the following plot, and interpret what you see in context of the data.

6. Recreate the following plot. Note that height_diff refers to difference in height between pre and post-evolution, and weight_diff is calculated similarly.

⊕Hint: The colors are from the viridis color palette. Take a look at the functions starting with scale_viridis_*.

7. Rework the previous plot using principles of effective data visualizations we have learned about in class. Then, describe the relationship between the changes in heights and weights of Pokemon and their species.

8. Describe what the following code is doing in each line, and interpret the numbers in the output.

⊕Hint: We use the :: operator to explicitly indicate that the FUN in PKG::FUN is in the PKG.

pokemon %>%
  group_by(species, attack_weak_type_new) %>%
  summarise(n = n()) %>%
  mutate(prop = scales::percent(n / sum(n)))

## # A tibble: 9 x 4
## # Groups:   species [4]
##   species  attack_weak_type_new     n prop 
##   <chr>    <chr>                <int> <chr>
## 1 Caterpie Bug                      3 30.0%
## 2 Caterpie Normal                   7 70.0%
## 3 Eevee    Electric                 1 16.7%
## 4 Eevee    Fire                     3 50.0%
## 5 Eevee    Water                    2 33.3%
## 6 Pidgey   Flying                  15 38.5%
## 7 Pidgey   Steel                   24 61.5%
## 8 Weedle   Bug                     10 50.0%
## 9 Weedle   Poison                  10 50.0%

9. What characteristics correspond to an evolved Pokémon with a high combat power? You do not need to come up with an exhaustive list, but you should walk us through your reasoning for answering this question and include all relevant summary statistics and visualizations.