Microsoft Word - ds2500_lab03_seaborn.docx
DS 2501: Intermediate Programming with Data / Lab Practicum
Prof. Rachlin and Prof. Park
Northeastern University
Seaborn Hack-a-thon
In this lab exercise you’ll explore the capabilities of the Seaborn visualization li
ary. You are
free to use any dataset and develop any type of visualization you find most interesting, as long
as it uses the Seaborn li
ary.
1. Review the Seaborn examples we did in class.
2. Now put Seaborn to work! First, find some interesting data to investigate. You can use
the datasets built into Seaborn:
import seaborn as sns
sns.get_dataset_names()
iris = sns.load_dataset(‘iris’)
or explore an online data repository such as:
• https:
www.data.gov
• https:
data.boston.gov
3. You are encouraged (but not required) to use Pandas to filter and refine your data.
4. Create an interesting visualization of your data. Include a sentence or two explaining
your visualization and what it reveals about your data. (This sentence may be embedded
in your code as a triple-quoted string.)
5. Feel free to explore plotting features not covered in class. Here are some useful
esources:
https:
seaborn.pydata.org/examples/index.html
https:
seaborn.pydata.org/tutorial.html
https:
seaborn.pydata.org/api.html
6. Submit your work to GradeScope by the end of the day on Thursday.