title: Large CSV Project
body: <p>so I am working on a project that reads, parses, and writes a MASSIVE csv file. The part I am focusing on right now is population of each region of earth. With each region there are three categories of population split into age. Population 1-15, Population 15-65, and Population 65+, I am writing this all in python and have come across some problems I cannot figure out. I will paste the code and explain further</p>
  
  <pre><code>from tkinter import *
  from tkinter import filedialog 
  import csv
  root = Tk()
  root.geometry("500x600")
  with open("REGION.csv", "r") as csv_file:
      csv_reader = csv.DictReader(csv_file)
      for line in csv_reader :
          print(line ["REGION_ID"])
          print(line ["POPULATION_15"])
          print(line ["POPULATION_15_65"])
          print(line ["POPULATION_65"])
  
  
  lbl1 = Label(root, text = "Enter orginal population (Estimate, Past figures only)").pack()
  orpop = Entry(root).pack()
  
  
  mainloop()
  </code></pre>
  
  <p>(code may be a little sloppy, it is my first project.)
  Ok, now, they are about 2806 regions, and all have 3 categories of pop, now, the first thing i want to do is add all of the populations of all regions, so POPULATION_15 + POPULATION_15_65 + POPULATION_65
  if someone can give me that code it would be appreciated.
  Next I prompt the user to give a population in the past, a TOTAL of earth. then, the program will divide that population from the original one, then split it up evenly into three categories and all the regions. 
  After all that it would export a new file of the new data.</p>
  
  <p>Total pop divided by population less then orginal given by user, the ratio would be given of how much the populations of all three categories of each region would need to be reduced. like if you enter a population that was half of it was today, it would reduce all the populations by 50%. Whatever way works aslong as it gets the job done.</p>