CSV

CSV is good for read and writing tabular data.

Decide if you want to parse each row into:

a dictionary with keys based on the headers
an array

Both have their use cases, but if you need to access the data via keys, let the parser handle that for you.

Dictionary

The one to use with most data

import csv

with open(source, mode='r') as csv_file:
    csv_reader = csv.DictReader(csv_file)
    line_count = 0
    for row in csv_reader:
        if line_count == 0:
            print(f'Header: {", ".join(row)}')
        else:
            print(f'\t{row["name"]}, {row["description"]}')
        line_count += 1
    print(f'Processed {line_count} lines.')

Array

import csv

with open('source') as csv_file:
    csv_reader = csv.reader(csv_file, delimiter=',')
    line_count = 0
    for row in csv_reader:
        if line_count == 0:
            print(f'Header: {", ".join(row)}')
        else:
            print(f'\t{row[0]}, {row[1]}')
        line_count += 1
    print(f'Processed {line_count} lines.')

Via
https://realpython.com/python-csv/

Writing

with open('output_file.csv', mode='w') as csv_output:
    csv_writer = csv.writer(csv_output, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL)

    for row in results:
        csv_writer.writerow(row)

Javascript CSV

More than 1024 columns

I often take an excel file supplied by someone that needs additional processing, open it with Libre Calc, save it as a CSV, then process from there.

However, just ran into a case where the number of columns in the source excel spreadsheet exceeds 1024. There is a hard limit in Libre Calc for the number of columns to 1024. It doesn't look like this will be changed any time soon:
https://bugs.freedesktop.org/show_bug.cgi?id=50916

Keep the data in the native Excel format and use a dedicated library to read it. Back in 2014, this one worked well.

https://pypi.python.org/pypi/openpyxl
http://pythonhosted.org//openpyxl/
https://bitbucket.org/ericgazoni/openpyxl/src