## Python Pandas and D&D Monsters

As you may be aware the Dungeon Brawl application I’ve been working on defines monsters in YaML format (check out the data/monsters directory) .

I thought it would be interesting to load this data in to Pandas and do a bit of data analysis.

While in the Dungeon Brawl repository I started up an ipython shell, then import a couple libraries:

In [1]: import yaml

In [2]: import glob

In [3]: import pandas



Next I need to find each of my monster’s YaML documents, these files reside in the data directory.

Using the glob library I can easily find all files in the directory with the .yaml extension:

In [4]: files = glob.glob('data/monsters/*.yaml')



I’m now able to iterate over each of my files, open them, parse them as YaML, then store the results in a new list:

In [5]: data = []

In [6]: for _file in files:



The data list now contains a dictionary for each of my monsters:

In [7]: len(data)
Out[7]: 762

In [8]: data[0]['name']
Out[8]: 'Empyrean'



All that is left is to load this data into a Pandas DataFrame :

In [9]: df = pandas.DataFrame(data)



## Analyzing

One of the first things I checked was the average hit points and armor class of a monster by challenge rating: I then dug a bit deeper into each of the stats using the Pandas describe method, this gives things like standard deviation, mean, min, and max.

Below are a couple attempts as useful describe tables:

Hit Points by Challenge Rating

Armor Class by Challenge Rating

Challenge Rating by Monster Type

Hit Points by Monster Size

Challenge Rating by Monster Size

Well that is it, hope you found something in this post interesting.