How can I read and process 100 bytes at a time from a large CSV file? - python-3.x

Question

The below csv is only a snippet of my main data file.
customer.csv
customer_id,order_id,number_of_items
10,4736,9
5,3049,1
1,4689,3
6,4114,9
1,4524,15
2,3727,16
3,3507,7
7,3988,3
5,4993,16
6,1945,4
7,3081,7
3,3707,2
5,1739,12
9,4167,17
7,3242,12
2,3109,10
10,2197,20
10,3528,13
8,4917,2
5,1713,19
8,4224,4
7,2160,2
10,2044,19
10,2956,8
3,3906,2
5,2288,16
7,1854,20
7,4404,2
9,1622,2
7,3685,2
10,2755,10
3,3390,10
6,1424,6
3,2127,15
4,1221,15
9,2994,14
1,1413,13
7,2771,7
3,4579,13
10,2208,4
CURRENTLY ALL I HAVE
import os
os.path.getsize("customer.csv") # outputs, 424 bytes
HOW I THINK I NEED TO PROCEED
I think I need to do something with open csv and read bytes? Then look at each row bit wise?
Please note, I am not looking specifically for someone to just give me an answer on how to do this (although that would be appreciated). Therefore, if someone could just point me in the right direction or give me some topics to look into that would be great. Side note, I know I am supposed to use encoding and decoding somewhere for this task.

Answer 1

This script will use the csv to load the data from customer.csv and compute the average using the builtin statistics module:
import csv
from statistics import mean
with open('customer.csv', newline='') as csvfile:
data = csv.DictReader(csvfile)
# group the customers by customer_id
customers = {}
for order in data:
customers.setdefault(order['customer_id'], []).append(int(order['number_of_items']))
# print the `average`:
print('{:<15} {}'.format('customer_id', 'average'))
for k, v in customers.items():
print('{:<15} {:.2f}'.format(k, mean(v)))
Prints:
customer_id average
10 11.86
5 12.80
1 10.33
6 6.33
2 13.00
3 8.17
7 6.88
9 11.00
8 3.00
4 15.00