def runs(T, D):
'''
compute the expected runs created by a team based upon Bill James' runs created formula.
You need to first compute the total number of hits (H) in the team, and total number of second base (_2B) in the team, etc.
Then you could use Bill James' runs created formula to compute the expected runs created by the team.
Input:
T: a python list of playerID's, for example, ['zitoba01', 'hiljuer01', ...]
D: a data frame loaded from 'Batting2001AJS.csv', which we processed in problem4.py.
Output:
RC: the expected runs created/scored by a team, a float scalar.
'''
#########################################
## INSERT YOUR CODE HERE
f = filtering(D, 'playerID', T)
H = sum_column(f, 'H')
_2B = sum_column(f, '2B')
_3B = sum_column(f, '3B')
HR = sum_column(f, 'HR')
BB = sum_column(f, 'BB')
AB = sum_column(f, 'AB')
RC = runs_created(H, _2B, _3B, HR, BB, AB)
#########################################
return RC
''' TEST: Now you can test the correctness of your code above by typing `nosetests -v test6.py:test_runs' in the terminal. '''
def sum_salaries(T, D):
'''
Given a team of players (T), compute the sum of salaries of all the players in the team.
Input:
T: a python list of playerID's, for example, ['zitoba01', 'hiljuer01', ...]
D: a data frame loaded from 'Batting2001AJS.csv', which we processed in problem4.py.
Output:
S: an integer scalar, the sum of salaries of all the players in the team.
'''
#########################################
## INSERT YOUR CODE HERE
Salary = filtering(D, 'playerID', T)
S = sum_column(Salary, 'salary')
#########################################
return S
''' TEST: Now you can test the correctness of your code above by typing `nosetests -v test6.py:test_sum_salaries' in the terminal. '''
def sum_stat(T, D, key='H'):
'''
Given a team of players (T), compute the sum of game statistics of all the players in the team.
For example, suppose we have a team with two players, the number of hits: 100, 200.
Then the sum of hits in the team will be: 100+200 = 300
Input:
T: a python list of playerID's, for example, ['zitoba01', 'hiljuer01', ...]
D: a data frame loaded from 'Batting2001AJS.csv', which we processed in problem4.py.
key: the column to be summed, for example, 'H' represents the number of hits
Output:
S: an integer scalar, the sum of statistics of all the players in the team.
'''
#########################################
## INSERT YOUR CODE HERE
df = filtering(D, 'playerID', T)
S = sum_column(df, key)
#########################################
return S
''' TEST: Now you can test the correctness of your code above by typing `nosetests -v test6.py:test_sum_stat' in the terminal. '''