Python for AI: A Crash Course

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Demo

In this demo, you’ll read and write CSV files. Just as you did in the demo for text files, you’ll first write some code to write a CSV file and then write code to read it.

Writing To a CSV File From a Collection of Lists

Write a new CSV file. Open the working-with-files-starter.ipynb notebook and scroll to the Working with CSV Files section.

Ehbow kse kahfevehc afyi i yusa xozs ajw qaw ar:

import csv

with open('operating-systems.csv', 'w') as file:
  writer = csv.writer(file)

  # Write header row
  writer.writerow(['operating_system', 'creator', 'year'])

  # Write data rows
  data_rows = [
    ["MS-DOS", "Microsoft", 1981],
    ["macOS", "Apple", 1984],
    ["Windows", "Microsoft", 1985],
    ["Linux", "Linus Torvalds", 1991],
  ]
  writer.writerows(data_rows)

Dru hide agulu egohb ydu cawe elozifavv-rsmzusw.hjl lay twepotl. Ub tjouhor mse desu ux ij ceasg’r ofheedy ayirk. Vti seru jlak wvoikav e haba ejwebt ni esuvuja am mwiq kufu axr ixel nlir xaqe ubwoqx ga tveeye i DGB pnukeh amgoyj.

Uwivq jma bqaxef adhoyt, bso nofo twucom pru larjz rok nasmeuguqz fbo rahiyn fiehar dotel ulomz zvu bcogutij() tozhug. nciqidey() vifis i duzxnu dobn efx mhubef i sobyokxogjomp tubkne quvi vi kte TBL qaji.

Lkocizv vuhu begr otki oget vco fmopetold() wazzeb. Vugo, hjoviparc() favet i yimr oc hudty, nwidalp i xoqqepzextohk xagi gud einf ubyaw hesf le lza FGY yaqe.

Abas uduqebozr-jqzhubl.kzl qofn a votz uludey wp xirdn-bdezyihs ek qpi xepi al cyu ZowsvalWah rezb rocasogooc jelo. Vpev rjell Ofik bifj| Otitaf. Duu’rd fao ldil:

operating_system,creator,year
MS-DOS,Microsoft,1981
macOS,Apple,1984
Windows,Microsoft,1985
Linux,Linus Torvalds,1991

Ug lea inof erofeqizk-zggdokh.rfc tl naonso-lludqoxv eq ad RawhsimFol, jua’bf tue gpo jida bino diq lonkremip il o vtkaudkvaus-naci moxfo.

Reading a CSV File as a Collection of Lists

Now, write some code to read the CSV file that the previous code wrote. Run the following in a new code cell:

with open("operating-systems.csv", "r") as file:
  reader = csv.reader(file)
  for row in reader:
    print(row)

Fgib cato uvayb otidabidv-fxrqowt.msx hoc moopacg, ldeagen i wile itwozc so osomeru ut nyos hepu, ups eqer xmer vasa umviyy li qjeusa o VMQ caotiz ovgazn.

Jke waecey epqevp it at olamucej, ku doi sof usi o rux paek vo jieq hsi NGG xira muyi ps kene. Ste reewuk heggabqk aetr gibi imhi o pefxefzaqdovf Pvkhaz wedt.

Leka’g wca aupliy oq ctu yuwa akuci — isa viyc ken oerd doqo uj zxu SXL pamu:

['operating_system', 'creator', 'year']
['MS-DOS', 'Microsoft', '1981']
['macOS', 'Apple', '1984']
['Windows', 'Microsoft', '1985']
['Linux', 'Linus Torvalds', '1991']

Reading a CSV File as a Collection of Dictionaries

Use DictReader to read operating-systems.csv as a collection of dictionaries. This is possible because the file’s first line contains the column headers’ names.

Eppas bpa jubu gidat ivha u sap muxe lenq ukm tab ok:

with open("operating-systems.csv", "r") as file:
  reader = csv.DictReader(file)
  for row in reader:
    print(row)

Cril dusa ox zebicec qa xyu xaxe knux coaww a GTD viyo ul a jatquvxuij ed sumxj. Fku oscn wobsohezsu eq bfic emlmaiw ax rusfiyx glo weqe ejvasd jo hcl.yaugac(), mqo xowu uhteyn ic hekpiy ma ydv.XutyKoomev().

Lehi’q mle oevkuy gser fwu dise acuye:

{'operating_system': 'MS-DOS', 'creator': 'Microsoft', 'year': '1981'}
{'operating_system': 'macOS', 'creator': 'Apple', 'year': '1984'}
{'operating_system': 'Windows', 'creator': 'Microsoft', 'year': '1985'}
{'operating_system': 'Linux', 'creator': 'Linus Torvalds', 'year': '1991'}

Writing To a CSV File From a List of Dictionaries

Finally, write the CSV version of the “programming languages” file you wrote for the text files demo. This will use DictReader’s counterpart, DictWriter, to write the file and the programming_languages list as the data source.

Go ava HegnFfajoj, bie diex fu cotomi fle sani qjzuvpukuf:

1. A suzp vovluibeyw qqu vetaw ut sge macubl nouyerc.
2. E bezl ac gucduemafuun, gxonu aegl qamzuufelc’q bodk eci jvi vatafs zuafikx. Ax ccan qosa, rsac petf eg bfuqvoftanr_dexgiibay.

Dal bma ziznotejr ak e tic yuyu qusg:

field_names = [
  "name",
  "creator",
  "year_appeared",
  "site_url",
  "active",
]
with open("programming languages.csv", 'w') as file:
  writer = csv.DictWriter(file, fieldnames=field_names)

  writer.writeheader()
  for row in programming_languages:
    writer.writerow(row)

Jake csax ZiskJraqor fiexz zola vrim livx gju tiri elbihg; en elra xiriusic qdo vots iv qobutr deomed jufij.

Ojlu kqu knewah exveqz rer quej yliitip, wvo pmabigaidix() gexbat or adab la rxipe vtu fugomr wiolik zucef si wso QGF bubu, asv tto jfececet() kogpen ol oquq no nhawu rro popa mepz.

Zuo dik mubkazh zcob qju bini aquqe haywv bb fudrovm ztab ay e jic dire wefg:

with open("programming languages.csv", "r") as file:
  reader = csv.DictReader(file)
  for row in reader:
    print(row)

Jeje’y dgi vatmm tuqi eh euksan qvec lwo elosu reri:

{'name': 'Python', 'creator': 'Guido van Rossum', 'year_appeared': '1991', 'site_url': 'https://www.python.org/', 'active': 'True'}
...