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python - How to read a CSV file without using external libraries (such as Numpy, Pandas)?

This is a question that usually appears in interviews.

I know how to read csv files using Pandas.

However I am struggling to find a way to read files without using external libraries.

Does Python come with any module that would help read csv files?

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You most likely will need a library to read a CSV file. While you could potentially open and parse the data yourself, this would be tedious and time consuming. Luckily python comes with a standard csv module that you won't have to pip install! You can read your file in like this:

import csv

with open('file.csv', 'r') as file:
    my_reader = csv.reader(file, delimiter=',')
    for row in my_reader:
        print(row)

This will show you that each row is being read in as a list. You can then process it based on index! There are other ways to read in data too as described at https://docs.python.org/3/library/csv.html one of which will create a dictionary instead of a list!

update

You linked your github for the project I took the snip

product_id,product_name,aisle_id,department_id
9327,Garlic Powder,104,13
17461,Air Chilled Organic Boneless Skinless Chicken Breasts,35,12
17668,Unsweetened Chocolate Almond Breeze Almond Milk,91,16
28985,Michigan Organic Kale,83,4
32665,Organic Ezekiel 49 Bread Cinnamon Raisin,112,3
33120,Organic Egg Whites,86,16
45918,Coconut Butter,19,13
46667,Organic Ginger Root,83,4
46842,Plain Pre-Sliced Bagels,93,3

Saved it as file.csv and ran it with the above code I posted. Result:

['product_id', 'product_name', 'aisle_id', 'department_id']
['9327', 'Garlic Powder', '104', '13']
['17461', 'Air Chilled Organic Boneless Skinless Chicken Breasts', '35', '12']
['17668', 'Unsweetened Chocolate Almond Breeze Almond Milk', '91', '16']
['28985', 'Michigan Organic Kale', '83', '4']
['32665', 'Organic Ezekiel 49 Bread Cinnamon Raisin', '112', '3']
['33120', 'Organic Egg Whites', '86', '16']
['45918', 'Coconut Butter', '19', '13']
['46667', 'Organic Ginger Root', '83', '4']
['46842', 'Plain Pre-Sliced Bagels', '93', '3']

This does what you have asked in your question. I am not going to do your project for you, you should be able to work it from here.


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