Summary

• A hands-on tutorial analyzing Central Park squirrel census data using pandas in Python
• Demonstrates data import, filtering, and manipulation using a real-world dataset containing squirrel locations and characteristics
• Covers creating a new dataframe from filtered data and exporting results to CSV
• Focuses on analyzing squirrel fur colors (gray, cinnamon/red, black) and their distribution in Central Park
• Practical application of pandas fundamentals including read_csv, filtering, counting, and data export

Resources

2018 Central Park Squirrel Census - Squirrel Data | NYC Open Data

Notes\ Code

Lets play with some data. In this case we will use the 2018 squirrel count of NYC central park. When we pull the CSV over from the Squirrel Census site we can see there's a ton here. This is good practice for what we see in the wild

Our challenge is to make a simple chart from the data using Pandas that has the sum of how many gray, red, and black hair squirrels are in Central Park and put it into a CSV like this.

Lets do it.

import pandas

data = pandas.read_csv("2018_Central_Park_Squirrel_Census_-_Squirrel_Data.csv")
series = data["Primary Fur Color"]
gray = int(series.str.count("Gray").sum())
red = int(series.str.count("Cinnamon").sum())
black = int(series.str.count("Black").sum())

data_dict = {
    "Fur Color": ["Gray", "Red", "Black"],
    "Count": [gray, red, black]
}

table = pandas.DataFrame(data_dict)
table.to_csv("squirrel_count.csv")

Easy peasy lemon squeezy.