Q:

Python CSV file import and object manipulation

I am trying to import a .csv file and save data in objects for later manipulation in Python. I am very new to coding so please do let me know my fundamental errors.
import csv
import os
import time
import numpy
import itertools

def __init__(p):        
    p.playerFile = csv.reader(open("dk.csv", "rb"))
    p.playerList = []
    p.playerName = ''
    p.playerPosition = ''
    p.PlayerGameInfo = ''
    p.playerPrice = 0

def loadCSV(p):
    for row in p.playerFile:
        playerObject = Player()
        playerObject.setPlayerName(row[1])     # Store player name
        playerObject.setPlayerPosition(row[0]) # Store player position
        playerObject.setPlayerGameInfo(row[3]) # Store player team
        playerObject.setPlayerPrice(row[2])    # Store player price

def getPlayerName(p):
    return p.PlayerName

def getPosition(p):
    return p.playerPosition

def getGameInfo(p):
    return p.PlayerGameInfo

def getPrice(p):
    return p.PlayerPrice

def setPlayerName(p, player):
    p.playerName = name

def setPlayerPosition(p, playerPosition):
    p.playerPosition = position

def setPlayerGameInfo(p, PlayerGameInfo):
    p.PlayerGameInfo = team

def setPlayerPrice(p, playerPrice):
    p.playerPrice = price

with open('~/dk.csv') as csvfile:
    readCSV = csv.reader(csvfile, delimiter=',')
    for row in readCSV:
        print (row)

A:

Style
Use snake_case instead of mixedCase when in Python. In general, follow PEP 8. 
Implementation
It seems you have a Player class defined somewhere. Then, you use global functions as getters and setters. This has two problems:

In OOP, getters and setters should be instance methods, e.g. of the Player class.
Python is not Java. Pythonic code wouldn't normally use getters and setters.

Design
Judging by loadCSV, each row of a CSV file will become a Player object. However, all Players do is store attributes for getting and setting. Save the hassle by using a dictionary for a player. Then just store all your dictionaries in a list. 
To understand this code, you will need to understand comprehensions.
import csv

# Map row to dictionary (dictionary comprehension)
def player(column_names, row):
    return {column_names[column]: data for column, data in enumerate(row) if column < len(column_names)}

# Map CSV file to list of dictionaries (list comprehension)
players = [player(['name', 'position', 'game_info', 'price'], row) for row in csv.reader(open('dk.csv', 'r'))]

Running this code on the following CSV file

Louis Fernando,Batter,Washington,400
Hose Ricardo,Pitcher,San Fernando,900

sets players to a list of dictionaries as below.

[{'game_info': 'Washington',
  'name': 'Louis Fernando',
  'position': 'Batter',
  'price': '400'},
 {'game_info': 'San Fernando',
  'name': 'Hose Ricardo',
  'position': 'Pitcher',
  'price': '900'}]

Then player objects can be accessed like so
print(players[0]['game_info']) # prints Washington
players[1]['name'] = "James Jones"

Notes
Types
This doesn't take care of types, e.g. the price field maps to a string, not a number. I'm not exactly sure what you're doing overall, so I'll leave that to you.
CSV Format
Columns in your CSV file beyond those named in column_names will be ignored.
e.g. passing four names (['name', 'position', 'game_info', 'price']) to player when a row in the CSV file contains five columns.

Louis Fernando,Batter,Washington,400,lol
Hose Ricardo,Pitcher,San Fernando,900

will produce the same result as the first example. 

