madisonlondon/MLB_Salary_Data

This program scrapes data, from https://madisonlondon.github.io/mlbsalarydata.github.io/, and pandas, a software library, to organize the salary data and then calculates the average salary as well as if there are any outliers.

Madison London

How the program works: 

    This program reads data from https://madisonlondon.github.io/mlbsalarydata.github.io/ and uses pandas, a software library, 
    to organize the data and store it in a DataFrame. The program then stores the date and time at which the data was pulled. 
    Next, the program will iterate through the column of salaries, first checking if the value at the current index is not empty. 
    Then, given the condition that we are working with a syntactically correct monetary value, we will remove the dollar sign(s) 
    and comma(s) to store the salary as a float. We find any outliers in the dataset using IQR and then calculate the average. 
    Finally, the program will print its findings. 

How to run the program: 

    Simply download the code to your desired location. Then navigate to that directory and run the following command in 
    your terminal:

    python3 solution.py

Output: 

    The program outputs the average value of the salaries as well as if there are any outliers. After this output, given the condition
    that there are outliers, the user will have the option to decide whether or not they want to see the outliers listed. 

Sources: 

I used the pandas documentation (https://pandas.pydata.org/pandas-docs/version/0.23.4/index.html) as well as the Python datetime
documentation (https://docs.python.org/3/library/datetime.html) for assistance during my completion of this task.