How to use Python to analyse cvs file? -


i beginner of programming, trying work out how average of elements in csv file. content of csv file:

enter image description here

and code:

import csv suburbs_average = {'north':0,'south':0,'east':0,'west':0} suburbs_count = {'north':0,'south':0,'east':0,'west':0} csvfile = open("ps1_3_data.csv") csv_reader = csv.reader(csvfile, delimiter=',')  row in csv_reader:    print (row[0],float(row[1]))   print(suburbs_average)

i have spent whole day trying figure out how calculate average of each suburbs(east,north...). need sort same suburb before calculate , how? please me on this? in advance. cheers.

i working standard library think should stick can understand base implementations before installing modules willy-nilly.

the csv module part of standard library, , reading docs learn each module capable of when looking solution. given problem, i'd following:

iterate through csv.reader() object , put values dict()s, average them.

import csv  # keep track of each time see 1 count = {'north': 0,          'south': 0,          'east': 0,          'west': 0}  # store associated values each time see 1 avg = {'north': [],        'south': [],        'east': [],        'west': []}  # rid of newline if not py3 open("ps1_3_data.csv", 'r', newline='') f:      r = csv.reader(f, delimiter=',')     # assumes dont have header row     # if do, uncomment line below     # header = next(r)     row in r:         # increment count each time see 1         count[row[0]] += 1         # add suburbs list of values         avg[row[0]].append(float(row[1])  # here replace lists single value # goes {'north': [15.0, 10.0, 10.0]} # {'north': 11.6666...} suburb in avg:     avg[suburb] = (sum(avg[suburb])/len(avg[suburb])

i made csv data supplied test:

>>> import csv >>> temp = r'c:\users\paul\desktop\temp.csv' >>> count = {'north': 0,      'south': 0,      'east': 0,      'west': 0} >>> avg = {'north': [],      'south': [],      'east': [],      'west': []} >>> open(temp, 'r', newline = '') f:     r = csv.reader(f, delimiter=',')     row in r:         count[row[0]] += 1         avg[row[0]].append(float(row[1]))   >>> count {'north': 3, 'south': 4, 'east': 5, 'west': 5} >>> avg {'north': [15.0, 10.0, 10.0], 'south': [10.0, 5.0, 5.0, 10.0], 'east': [10.0, 5.0, 10.0, 5.0, 10.0], 'west': [20.0, 15.0, 15.0, 20.0, 5.0]} >>> suburb in avg:     avg[suburb] = (sum(avg[suburb])/len(avg[suburb]))   >>> avg {'north': 11.666666666666666, 'south': 7.5, 'east': 8.0, 'west': 15.0} >>>

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