# 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:
tempArray = line.strip().split(",")
zipnum = tempArray[1]
# check that this is a zipcode in the user supplied borough
if zipnum in borough.zipcodes:
# check that all values exist for that zip
# check that area is valid
if len(tempArray[7]) > 0:
area = float(tempArray[7])
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
totPopBor = totPopBor + int(pop)
#Calculate Average through the method in the borough class
borObj.calcAvgPop(totPopBor, count)
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)
for i in range(1, num_linesPopulation):
if linesPopulation[i].split(',')[10] != '\n':
zipPopulationDict[linesPopulation[i].split(',')[0] = (float(linesPopulation[i].split(',')[10]))
# Last part
for zip in zipBoroughDict:
if zipBoroughDict[zip][0:5] == targetBorough[0:5]:
if zip in zipPopulationDict:
zipCode = zipcode.Zipcode(zip, zipPopulationDict[zip])
targetBorough.addZipcode(zipCode)
# Output average population
average = targetBorough.averagePopulation()
print average
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()
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)
borough.zipcodes = makeunique(borough.zipcodes)
with open('zipCodes.csv') as f:
rows = csv.reader(f, delimiter=',')
rows.next()
for row in rows:
if (row[10] != ''):
rowzip = row[1]
rowpop = float(row[10].strip())
for line in borough.zipcodes:
if (int(rowzip) == int(line)):
borough.addPopulation(rowpop)
