I have a homework assignment to do, having to do with reading files through csv and functions.

The basic idea is to calculate the rusher rating of football players over the course of two years. We use data from a file given to us. A sample file would be:

name, ,pos,team,g,rush,ryds,rtd,rtdr,ravg,fum,fuml,fpts,year 
A.J.,Feeley,QB,STL,5,3,4,0,0,1.3,3,2,20.3,2011
Aaron,Brown,RB,DET,1,1,0,0,0,0,0,0,0.9,2011
Aaron,Rodgers,QB,GB,15,60,257,3,5,4.3,4,0,403.4,2011
Adrian,Peterson,RB,MIN,12,208,970,12,5.8,4.7,1,0,188.9,2011
Ahmad,Bradshaw,RB,NYG,12,171,659,9,5.3,3.9,1,1,156.6,2011

In other words, we have to strip the first line from the file, and read the rest of the lines, splitting at commas.

To calculate rusher rating, we need:

Yds is the average yards gain per attempt. This is [total yards / (4.05 * attempts)]. If this number is greater than 2.375, then 2.375 should be used instead.

perTDs is the percentage of touchdowns per carry. This is [(39.5 * touchdowns) / attempts]. If this number is greater than 2.375, then 2.375 should de used insted.

perFumbles is the percentage of fumbles per carry. This is [2.375 - ((21.5 * fumbles) / attempts)].

The rusher rating is [Yds + perTDs + perFumbles] * (100 / 4.5).

The code I have so far:

playerinfo = []
teaminfo10 = []
teaminfo11 = []

import csv

file = raw_input("Enter filename: ")
read = open(file,"rU")
read.readline()
fileread = csv.reader(read)

#Each line is iterated through, and if rush attempts are greater than 10, the
#player may be used for further statistics.
for playerData in fileread:
    if int(playerData[5]) > 10:

        attempts = int(playerData[5])
        totalYards = int(playerData[6])
        touchdowns = int(playerData[7])
        fumbles = int(playerData[10])

        #Rusher rating for each player is found. This rating, coupled with other
        #data about the player is formatted and appended into a list of players.
        rushRating = ratingCalc(attempts,totalYards,touchdowns,fumbles)
        rusherData = rushFunc(playerData,rushRating)
        playerinfo.append(rusherData)

        #Different data about the player is formatted and added to one of two
        #lists of teams, based on year. 
        teamData = teamFunc(playerData)
        if playerData[13] == '2010':
            teaminfo10.append(teamData)
        else:
            teaminfo11.append(teamData)

#The list of players is sorted in order of decreasing rusher rating.
playerinfo.sort(reverse = True)
#The two team lists of players are sorted by team.
teaminfo10.sort()
teaminfo11.sort()

print "The following statistics are only for the years 2010 and 2011."
print "Only those rushers who have rushed more than 10 times are included."
print
print "The top 50 rushers based on their rusher rating in individual years are:"

#50 players, in order of decreasing rusher ratings, are printed along with other
#data.
rushPrint(playerinfo,50)

#A similar list of running backs is created, in order of decreasing rusher
#ratings.
RBlist = []
for player in playerinfo:
    if player[2] == 'RB':
        RBlist.append(player)

print "\nThe top 20 running backs based on their rusher rating in individual\
years are:"
#The top 20 running backs on the RBlist are printed, with other data.
rushPrint(RBlist,20)


#The teams with the greatest overall rusher rating (if their attempts are
#greater than 10) are listed in order of decreasing rusher rating, for both 2010
#and 2011.
teamListFunc(teaminfo10,'2010')

teamListFunc(teaminfo11,'2011')

#The player(s) with the most yardage is printed.
yardsList = mostStat(6,fObj,False)
print "\nThe people who rushed for the most yardage are:"
for item in yardsList:
    print "%s rushing for %d yards for %s in %s."\
    % (item[1],item[0],item[2],item[3])

#The player(s) with the most touchdowns is printed.
TDlist = mostStat(7,fObj,False)
print"\nThe people who have scored the most rushing touchdowns are:"
for item in TDlist:
    print "%s rushing for %d touchdowns for %s in %s."\
    % (item[1],item[0],item[2],item[3])

#The player(s) with the most yardage per rushing attempt is printed.
ypaList = mostStat(6,fObj,True)
print"\nThe people who have the highest yards per rushing attempt with over 10\
rushes are:"
for item in ypaList:
    print "%s with a %.2f yards per attempt rushing average for %s in %s."\
    % (item[1],item[0],item[2],item[3])

#The player(s) with the most fumbles is printed.
fmblList = mostStat(10,fObj,False)
print"\nThere are %d people with the most fumbles. They are:" % (len(fmblList))
for item in fmblList:
    print "%s with %d fumbles for %s in %s." % (item[1],item[0],item[2],item[3])


def ratingCalc(atts,totalYrds,TDs,fmbls):
    """Calculates rusher rating."""
    yrds = totalYrds / (4.05 * atts)
    if yrds > 2.375:
        yrds = 2.375

    perTDs = 39.5 * TDs / atts
    if perTDs > 2.375:
        perTDs = 2.375

    perFumbles = 2.375 - (21.5 * fmbls / atts)

    rating = (yrds + perTDs + perFumbles) * (100/4.5)

    return rating    

def rushFunc(information,rRating):
    """Formats player info into [rating,name,pos,team,yr,atts]"""
    rusherInfo = []
    rusherInfo.append(rRating)
    name = information[0] + ' ' + information[1]
    rusherInfo.append(name)
    rusherInfo.append(information[2])
    rusherInfo.append(information[3])
    rusherInfo.append(information[13])
    rusherInfo.append(information[5])

    return rusherInfo


def teamFunc(plyrInfo):
    """Formats player info into [team,atts,yrds,TDs,fmbls] for team sorting"""
    teamInfo = []
    teamInfo.append(plyrInfo[3])
    teamInfo.append(plyrInfo[5])
    teamInfo.append(plyrInfo[6])
    teamInfo.append(plyrInfo[7])
    teamInfo.append(plyrInfo[10])

    return teamInfo

def rushPrint(lst,num):
    """Prints players and their data in order of rusher rating."""
    print "Name                           Pos   Year  Attempts   Rating  Team"
    count = 0
    while count < num:
        index = lst[count]
        print "%-30s %-5s %4s  %5s      %3.2f  %s"\
              % (index[1],index[2],index[4],index[5],index[0],index[3])
        count += 1

So yeah, there are still a lot of functions that I have to define. But what do you think of the code so far? Is it inefficient? Can you tell me what's wrong with it? Because it looks to me like this code is going to be incredibly long (like 300 lines or so), but the teacher said it should be a relatively short project.

• python
• csv

Here's a piece of code that should simplify your entire project considerably.

It may take a little to understand the tasks at hand, but on the whole, this will make your life much easier when you deal with the correct datatypes and 'associative arrays' (dicts)

import csv

reader = csv.DictReader(open('mycsv.txt', 'r'))
#opens the csv file into a dictionary

list_of_players = map(dict, reader)
#puts all the dictionaries (by row) as a separate element in a list. 
#this way, its not a one-time iterator and all your info is easily accessible

for i in list_of_players:
    for stat in ['rush','ryds','rtd','fum','fuml','year']:
        i[stat] = int(i[stat])
    #the above loop makes all the intended integers..integers instead of strings
    for stat in ['fpts','ravg','rtdr']:
        i[stat] = float(i[stat])
    #the above loop makes all the intended floats..floats instead of strings

for i in list_of_players:
    print i['name'], i[' '], i['fpts']
    #now you can easily access and loop through your players with meaningful names
    #using 'fpts' rather than predetermined numbers [5]

This sample code show how easy it is to work with their name and their stats, namely firstname, lastname and fpts:

>>> 
A.J. Feeley 20.3
Aaron Brown 0.9
Aaron Rodgers 403.4
Adrian Peterson 188.9
Ahmad Bradshaw 156.6

Some tuning will be required, of course, to get all of your requested stats (max,etc), but this makes doing THOSE tasks less verbose by keeping your datatypes correct from the start.

This assignment can be accomplished now (using these constructs) in much, much less than 300 lines, and the more you use python, you'll learn the traditional idioms that accomplish them. lambda and sorted() are examples of functions you'll fall in love with...in time!