You'll learn all about iterators and iterables, which you have already worked with when writing for loops. You'll learn some handy functions that will allow you to effectively work with iterators. And you’ll finish the chapter with a use case that is pertinent to the world of data science and dealing with large amounts of data—in this case, data from Twitter that you will load in chunks using iterators.

Introductie tot iterators

Iterators vs. Iterables

Itereren over iterables (1)

Itereren over iterables (2)

Iteratoren als functiargumenten

Spelen met iterators

enumerate gebruiken

Werken met zip

Met * en zip 'unzippen'

Iteratoren gebruiken om grote bestanden in het geheugen te laden

Grote hoeveelheden Twitterdata verwerken

Informatie extraheren uit grote hoeveelheden Twitterdata

Gefeliciteerd!

Using iterators in PythonLand

In this chapter, you'll build on your knowledge of iterators and be introduced to list comprehensions, which allow you to create complicated lists—and lists of lists—in one line of code! List comprehensions can dramatically simplify your code and make it more efficient, and will become a vital part of your Python toolbox. You'll then learn about generators, which are extremely helpful when working with large sequences of data that you may not want to store in memory, but instead generate on the fly.

List comprehensions

Write a basic list comprehension

List comprehension over iterables

Writing list comprehensions

Nested list comprehensions

Advanced comprehensions

Using conditionals in comprehensions (1)

Using conditionals in comprehensions (2)

Dict comprehensions

Introduction to generator expressions

List comprehensions vs. generators

Write your own generator expressions

Changing the output in generator expressions

Build a generator

Wrapping up comprehensions and generators.

List comprehensions for time-stamped data

Conditional list comprehensions for time-stamped data

List comprehensions and generators

This chapter will allow you to apply your newly acquired skills toward wrangling and extracting meaningful information from a real-world dataset—the World Bank's World Development Indicators. You'll have the chance to write your own functions and list comprehensions as you work with iterators and generators to solidify your Python chops.

Welcome to the case study!

Zipping dictionaries

Writing a function to help you

Using a list comprehension

Turning this all into a DataFrame

Using Python generators for streaming data

Processing data in chunks (1)

Writing a generator to load data in chunks (2)

Writing a generator to load data in chunks (3)

Using pandas' read_csv iterator for streaming data

Writing an iterator to load data in chunks (1)

Writing an iterator to load data in chunks (2)

Writing an iterator to load data in chunks (3)

Writing an iterator to load data in chunks (4)

Writing an iterator to load data in chunks (5)

Final thoughts

Bringing it all together!

Tweets

World Bank World Development Indicators

Course Glossary

In deze cursus Python-gereedschapskist bouw je verder aan je gevorderde Python-vaardigheden. Eerst leer je over iterators, objecten die je al bent tegengekomen bij for-lussen. Daarna maak je kennis met list comprehensions, superhandige tools voor alle data professionals en developers die met Python werken. Je rondt de cursus af met een casestudy waarin je alle technieken toepast die je in beide delen van deze cursus hebt geleerd.

De video's bevatten live-transcripts die je kunt tonen door linksonder in de video op "Show transcript" te klikken.
De cursusglossary vind je rechts in de sectie met bronnen.
Om CPE-credits te behalen, moet je de cursus afronden en een score van 70% halen op de gekwalificeerde toets. Je gaat naar de toets door rechts op de callout voor CPE-credits te klikken.

Introduction to Functions in Python

Blijf je moderne Data Science-vaardigheden ontwikkelen met iterators en lijstbegrip.

Python-gereedschapskist

Associate Data Scientist  in Python

Python-ontwikkelaar

Basisprincipes van programmeren in Python

Data Scientist at DataCamp

Met iterators grote bestanden in het geheugen laden

Data in chunks laden

Itereren over data

Laten we oefenen!

Using iterators in PythonLand - Iteratoren gebruiken om grote bestanden in het geheugen te laden

Iteratoren gebruiken om grote bestanden in het geheugen te laden

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