$ git clone https://github.com/georgetown-analytics/nba.git
$ cd nba
$ jupyter notebook
In Jupyter, open the file called "NBA Player Statistics Workshop.ipynb"
Given a dataset of NBA players performance and salary in 2014, you'll use Python to load the dataset and compute the summary statistics for the SALARY field:
- mean
- median
- mode
- minimum
- maximum
You will need to make use of the csv module or use pandas to load the data and interact with it. Computations should require only simple arithmetic.
Bonus:
Determine the relationship of PER (Player Efficiency Rating) to Salary via a visualization of the data.
NBA 2014 Players Dataset: http://bit.ly/gtnbads
If you've completed the certificate program and want to test your data science skills from ingestion through machine learning, follow the instructions in the file called "Data Analysis of NBA Players Challenge.ipynb"