# Salaries and Experience

salaries_and_tenures = [(83000, 8.7), (88000, 8.1),
                        (48000, 0.7), (76000, 6),
                        (69000, 6.5), (76000, 7.5),
                        (60000, 2.5), (83000, 10),
                        (48000, 1.9), (63000, 4.2)]

print(salaries_and_tenures)

# *************************************************
# Print the table as scatter plot

# import pandas as pd
# import matplotlib.pyplot as plt

# df = pd.DataFrame(salaries_and_tenures)
# print(df)

# df.plot(kind="scatter", x = 1, y = 0)
# plt.show() 
# *************************************************

from collections import defaultdict

# ++++++++++++++++++++++++++++++++++++++++++++++++++++++
# ***** Look at the average salary for each tenure:
# ++++++++++++++++++++++++++++++++++++++++++++++++++++++

# keys are years, values are lists of the salaries for each tenure

salary_by_tenure = defaultdict(list)	# Create a defaultdict that stores lists

for salary, tenure    in    salaries_and_tenures:
    salary_by_tenure[tenure].append(salary)

print("\n\n", salary_by_tenure)

print("*** ", salary_by_tenure.items())

average_salary_by_tenure = {
    tenure : sum(salaries) / len(salaries)
    for tenure, salaries in salary_by_tenure.items()
    }

print("\nAvg Sal by tenure = ", average_salary_by_tenure)