#Aliya Merali
#Assignment 2
#Problem 4
import sys
import csv
from borough import Borough
borInput = sys.argv[1]
borInput = borInput.title()
boroughZipRef = open('boroughs.csv','r')
zipPopRef = open('zipCodes.csv','r')
#Set the input borough as an instance of the class Borough
borObj = Borough(borInput)
#Add to the list of zip codes in the borough class using the method addZipcode
boroughDict = csv.DictReader(boroughZipRef, ['ZipVal','BorName'])
for row in boroughDict:
if row['BorName'] == borInput:
borObj.addZipcode(row['ZipVal'])
#Sum the population in the zips of the borough by comparing zipcode values from the file to the zipcodes list in boroughs
popBorInput = csv.DictReader(zipPopRef)
totPopBor = 0
count = 0
for row in popBorInput:
if row['Total Population per ZIP Code'] != '':
pop = row['Total Population per ZIP Code']
zipcode = row['name']
if zipcode in borObj.zipcodes:
count = count + 1
if userBorough == "staten island": # if its staten island convert
userBorough = "staten"
# check that a valid borough was supplied
acceptableBoroughs = ["manhattan", "brooklyn", "queens", "bronx", "staten"]
if userBorough not in acceptableBoroughs:
print "ERROR: please enter a known borough"
print acceptableBoroughs
sys.exit()
# open the db file containing zipcodes for each borough
dbFile = open("boroughs.csv", "r")
# create a Borough object
borough = Borough(userBorough)
# look through db file for zipcodes in that borough
for line in dbFile:
tempArray = line.strip().split(",")
zipnum = tempArray[0]
# if its in the borough add it to the object
if lower(tempArray[1]) == userBorough:
borough.addZipcode(zipnum)
dbFile.close()
# open the next file and pull relevant pop and area information into borough object
dbFile = open("zipCodes.csv", "r")
for line in dbFile:
boroughcon = csv.reader(boroughfile, delimiter=',')
popfile = open('zipCodes.csv', 'r')
popcon = csv.reader(popfile, delimiter=',')
# remove the duplicates
def clean(list):
checked = []
for x in list:
if x not in checked:
checked.append(x)
return checked
# make a dict
boroughs['Manhattan'] = Borough('Manhattan')
boroughs['Brooklyn'] = Borough('Brooklyn')
boroughs['Queens'] = Borough('Queens')
boroughs['Bronx'] = Borough('Bronx')
boroughs['Staten'] = Borough('Staten')
# find the zipcodes in each borough
for zipline in boroughcon:
zipcode = zipline[0]
for x in boroughs.keys():
if zipline[1] == x:
boroughs[x].addZipcode(zipcode)
# clean
for x in boroughs.keys():
boroughs[x].zipcodes = clean(boroughs[x].zipcodes)
# calculate the population of each borough
popcon.next()
b1=list(boro)
zips=csv.reader(open("zipCodes.csv","rb"),delimiter=',')
z3=list(zips)
#dictionary holding all zip codes' population from zipcodes.csv
zippop={}
#dictionary for borough, takes user input
boroughs={userboro:0}
#fill in zipcode
for i in range(1,len(z3)):
zippop[z3[i][0]]=z3[i][10]
# instantiate Borough class in the dictionary
# class has 3 parameters, name, zipcodes as an array and sum of population in zip codes in the borough
boroughs[userboro]=Borough(userboro)
boroughs[userboro].zipcodes=[]
boroughs[userboro].sumpopul=0
#first check if in boroughs.csv zip exists
#if we find user defined borough name proceed to zip population dictionary
#append the zip code to the class object
#zort is a list as (zipcode, population in the zipcode)
for i in range(0,len(b1)):
if b1[i][1] == userboro:
zipcode = Zipcode(int(b1[i][0]))
if str(zipcode.number) in zippop.keys():
if zippop[str(zipcode.number)]!='':
# Compute the average population of the zip codes in a given borough
import sys
from zipcode import Zipcode
from borough import Borough
targetBorough = Borough(sys.argv[1].split(" ")[0])
fileBorough = open('boroughs_tr.csv','r')
linesBorough = []
for line in fileBorough:
linesBorough.append(line)
fileBorough.close()
zipBoroughDict = {} # create dictionary as in problem3.py
num_linesBorough = len(linesBorough)
for i in range(1, num_linesBorough):
if linesBorough[i].split(',')[10] != '\n':
zipBoroughDict[linesBorough[i].split(',')[0] = (float(linesBorough[i].split(',')[1][:-1]))
filePopulation = open('zipCodes_tr.csv', 'r')
linesPopulation = []
for line in filePopulation:
linesPopulation.append(line)
filePopulation.close()
zipPopulationDict = {} # create dictionary as in problem3.py
num_linesPopulation = len(linesPopulation)
import sys
from borough import Borough
from zipcode import Zipcode
boroughOfInterest = Borough(sys.argv[1].split(" ")[0])
#load the zipcodes for the boroughs
#load the population for the boroughs
boroughPopDict = {'Bronx': 2764960, 'Brooklyn': 5009400, 'Staten': 937460, 'Manhattan': 3037768, 'Queens': 4459862}
#add population to the borough object
boroughOfInterest.population = boroughPopDict[boroughOfInterest.name]
#add zipcodes to borough object
boroughZipDict = {'Bronx': ['10451', '10452', '10453', '10454', '10455', '10456', '10457', '10458', '10459', '10460', '10461', '10462', '10463', '10464', '10465', '10466', '10467', '10468', '10469', '10470', '10471', '10472', '10473', '10474', '10475', '10451', '10452', '10453', '10454', '10455', '10456', '10457', '10458', '10459', '10460', '10461', '10462', '10463', '10464', '10465', '10466', '10467', '10468', '10469', '10470', '10471', '10472', '10473', '10474', '10475'], 'Brooklyn': ['11201', '11203', '11204', '11205', '11206', '11207', '11208', '11209', '11210', '11211', '11212', '11213', '11214', '11215', '11216', '11217', '11218', '11219', '11220', '11221', '11222', '11223', '11224', '11225', '11226', '11228', '11229', '11230', '11231', '11232', '11233', '11234', '11235', '11236', '11237', '11238', '11239', '11241', '11242', '11243', '11249', '11252', '11256', '11201', '11203', '11204', '11205', '11206', '11207', '11208', '11209', '11210', '11211', '11212', '11213', '11214', '11215', '11216', '11217', '11218', '11219', '11220', '11221', '11222', '11223', '11224', '11225', '11226', '11228', '11229', '11230', '11231', '11232', '11233', '11234', '11235', '11236', '11237', '11238', '11239', '11241', '11242', '11243', '11249', '11252', '11256'], 'Queens': ['11004', '11101', '11102', '11103', '11104', '11105', '11106', '11109', '11351', '11354', '11355', '11356', '11357', '11358', '11359', '11360', '11361', '11362', '11363', '11364', '11365', '11366', '11367', '11368', '11369', '11370', '11371', '11372', '11373', '11374', '11375', '11377', '11378', '11379', '11385', '11411', '11412', '11413', '11414', '11415', '11416', '11417', '11418', '11419', '11420', '11421', '11422', '11423', '11426', '11427', '11428', '11429', '11430', '11432', '11433', '11434', '11435', '11436', '11691', '11692', '11693', '11694', '11697', '11101', '11102', '11103', '11004', '11104', '11105', '11106', '11109', '11351', '11354', '11355', '11356', '11357', '11358', '11359', '11360', '11361', '11362', '11363', '11364', '11365', '11366', '11367', '11368', '11369', '11370', '11371', '11372', '11373', '11374', '11375', '11377', '11378', '11379', '11385', '11411', '11412', '11413', '11414', '11415', '11416', '11417', '11418', '11419', '11420', '11421', '11422', '11423', '11426', '11427', '11428', '11429', '11430', '11432', '11433', '11434', '11435', '11436', '11691', '11692', '11693', '11694', '11697'], 'Manhattan': ['10001', '10002', '10003', '10004', '10005', '10006', '10007', '10009', '10010', '10011', '10012', '10013', '10014', '10015', '10016', '10017', '10018', '10019', '10020', '10021', '10022', '10023', '10024', '10025', '10026', '10027', '10028', '10029', '10030', '10031', '10032', '10033', '10034', '10035', '10036', '10037', '10038', '10039', '10040', '10041', '10044', '10045', '10048', '10055', '10060', '10069', '10090', '10095', '10098', '10099', '10103', '10104', '10105', '10106', '10107', '10110', '10111', '10112', '10115', '10118', '10119', '10120', '10121', '10122', '10123', '10128', '10151', '10152', '10153', '10154', '10155', '10158', '10161', '10162', '10165', '10166', '10167', '10168', '10169', '10170', '10171', '10172', '10173', '10174', '10175', '10176', '10177', '10178', '10199', '10270', '10271', '10278', '10279', '10280', '10281', '10282', '10001', '10002', '10003', '10004', '10005', '10006', '10007', '10009', '10010', '10011', '10012', '10013', '10014', '10015', '10016', '10017', '10018', '10019', '10020', '10021', '10022', '10023', '10024', '10025', '10026', '10027', '10028', '10029', '10030', '10031', '10032', '10033', '10034', '10035', '10036', '10037', '10038', '10039', '10040', '10041', '10044', '10045', '10048', '10055', '10060', '10069', '10090', '10095', '10098', '10099', '10103', '10104', '10105', '10106', '10107', '10110', '10111', '10112', '10115', '10118', '10119', '10120', '10121', '10122', '10123', '10128', '10151', '10152', '10153', '10154', '10155', '10158', '10161', '10162', '10165', '10166', '10167', '10168', '10169', '10170', '10171', '10172', '10173', '10174', '10175', '10176', '10177', '10178', '10199', '10270', '10271', '10278', '10279', '10280', '10281', '10282'], 'Staten': ['10301', '10302', '10303', '10304', '10305', '10306', '10307', '10308', '10309', '10310', '10311', '10312', '10314', '10301', '10302', '10303', '10304', '10305', '10306', '10307', '10308', '10309', '10310', '10311', '10312', '10314']}
#add zipCodes to the borough object
for v in boroughZipDict[boroughOfInterest.name]:
boroughOfInterest.addZipcode(Zipcode(v))
#calculate average
average_pop = float(boroughOfInterest.population) / (boroughOfInterest.zipCounter)
print "The average population of the zip codes in", sys.argv[1], "is", str(average_pop)
"""
# from borough import *
from borough import Borough
# reuse the functions in problem 4
from problem3 import getzippopulation, getboroughzipcode
from sys import argv as bname
if __name__ == "__main__":
# get the population and borough information from the data in dictionary form
populationdic = getzippopulation()
boroughdic = getboroughzipcode()
# turn the input into the captalized form
bname = bname[1].split(" ")[0].capitalize()
# initialize the object in Borough class
BOROUGH = Borough(bname)
# put the data stored from two dictions into the object
for zp in boroughdic[bname]:
if zp in populationdic:
BOROUGH.addZipcode(zp)
BOROUGH.addPopulation(populationdic[zp])
# use the class function to get the average number
print BOROUGH.PopuPerZip()
import sys
import csv
import collections
#from zip import Zipcode
from borough import Borough
#import and open the files
bor = sys.argv[1]
filezipCode = open('zipCodes.csv')
csvreaderzc = csv.reader(filezipCode, delimiter=',')
fileboroughs = open('boroughs.csv')
csvreaderb = csv.reader(fileboroughs, delimiter=',')
seq = csvreaderb
BorObj = Borough(bor)
#csvreaderb = csv.reader(fileboroughs, ['namezip','namebor'])
#counting population per zipcode
population = {}
count = 0
for line in csvreaderzc:
if count > 0 and line[10] != '':
population[line[1]] = line[10]
count = count + 1
#print population
#tried to add the population for the whole borough but wasn't working and was
#messing up the rest - seems to be the same issue I'm having in problem #3
popMan = 0
#Kara Leary
#Urban Informatics
#Assignment 2 - Problem 4
import sys
import csv
from zipcode import Zipcode
from borough import Borough
#In this code, first I import the name of the borough from the command line. I assume that Staten Island is being input simply as 'Staten'. I set the input to the name of the Borough object 'borough'. I define the same 'makeunique' function that I used in problem 3. Next, I opened 'boroughs.csv' and read through each entry row by row. I set the zip code of the entry to 'thiszip', and take the name of the borough listed. I make the name lowercase as well, so that I can match it to the inputted borough without having to worry about differences in capitalization. If the name matches the one inputted by the user, I use the 'borough.addZipcode method to add the zipcode to the list of that borough's zips. I then employ the 'makeunique' function defined earlier to weed out any duplicates in that boroughs zipcode dictionary. I then go through the file 'zipCodes.csv' row by row. First I ensure that I am only looking at rows that have an entry for population; otherwise it is useless to me. If the row has a population entry, I set the rowzip to that row's zipcode, and rowpop to that row's population. i then go through the entries in the zipcode dictionary: if the row zipcode matches an entry in the dictionary, then it must be part of that borough, and I use the 'addPopulation' method to add the population to the borough's running total. Finally, I use the borough.findAverage function to compute the average population of the zipcodes.
boroughname = sys.argv[1]
borough = Borough(boroughname.lower())
def makeunique(list):
found = []
keep = []
for entry in list:
if entry not in found:
found.append(entry)
keep.append(entry)
return keep
with open('boroughs.csv') as f:
rows = csv.reader(f, delimiter=',')
for row in rows:
thiszip = Zipcode(row[0])
rowentry = row[1]
if (rowentry.lower() == borough.name):
borough.addZipcode(thiszip.number)
