Pular para o conteúdo principal

Curso

Data Transformation with Polars

IntermediárioNível de habilidade

Atualizado 03/2026

Take Polars further with text manipulation, rolling statistics, DataFrame joins, and advanced analytics.

Iniciar Curso Gratuitamente

PythonData Manipulation4 h14 vídeos54 Exercícios4,700 XPCertificado de conclusão

Crie sua conta gratuita

ou

Ao continuar, você aceita nossos Termos de Uso, nossa Política de Privacidade e que seus dados serão armazenados nos EUA.

Preferido por alunos de milhares de empresas

Treinar 2 ou mais pessoas?

Experimentar DataCamp for Business

Descrição do curso

Take your Polars skills further with intermediate techniques for data transformation and analysis. Learn to clean and search text, work with time series using rolling and window functions, and combine DataFrames through joins and concatenation. You'll also create reusable custom expressions and apply advanced analytics, such as quantiles, histograms, and correlations. By the end, you'll be equipped to handle complex data workflows with confidence.

Pré-requisitos

Introduction to Polars Intermediate Python for Developers

1

Transforming Data with Expressions

In this chapter, you'll learn how to clean and search text data, extract patterns from strings, and use conditional expressions to transform columns.

Transforming Data with Expressions

Converting column data types

Removing whitespace

Concatenating text columns

Searching and extracting text

Searching text

Extracting strings from text

Replacing multiple patterns

Creating conditional expressions

Categorizing customers with conditions

Chaining multiple conditions

Filling missing values

Iniciar Capítulo

2

Working with Time Series and Window Functions

Learn how to parse and manipulate dates, filter and aggregate data by time periods, and calculate rolling and cumulative statistics.

Parsing and manipulating dates

Parsing datetime strings

Extracting the hour component

Calculating rental period end times

Filtering and aggregating by time period

Filtering for a specific datetime

Filtering for a time range

Calculating weekly rental totals

Rolling and cumulative aggregations

Calculating a rolling sum

Calculating cumulative rentals

Rolling aggregations on multiple columns

Transforming data by group

Calculating the hourly total with window functions

Calculating the difference from hourly mean

Grouping by multiple columns with window functions

Iniciar Capítulo

3

Combining and Joining DataFrames

This chapter covers combining DataFrames via concatenation, joining on single or multiple columns, and matching rows based on conditions or nearest values.

Concatenating DataFrames

Stacking regional listings

Adding flag columns

Adding new rows efficiently

Joining DataFrames

Adding host information

Matching on unique combinations

Preserving all listings

Finding gaps in both DataFrames

Joining DataFrames by condition or nearest match

Matching listings to budget requests

Filtering with multiple conditions

Matching to the nearest price update

Iniciar Capítulo

4

Custom Transformations and Advanced Analytics

Learn how to build reusable custom expressions, categorize data using quantiles and fixed thresholds, and analyze rankings and correlations.

Applying custom transformations

Converting streams to billions

Creating reusable expressions

Adding a custom expression

Calculating quantiles and histograms

Calculating popularity quantiles

Binning streams into tiers

Building a popularity histogram

Calculating ranks and correlations

Ranking albums with tie handling

Building a correlation matrix

Custom summaries with describe

Wrapping up

Iniciar Capítulo

Data Transformation with Polars

Curso
concluído

Obtenha um certificado de conclusão

Adicione esta credencial ao seu perfil do LinkedIn, currículo ou CV
Compartilhe nas redes sociais e em sua avaliação de desempenhoInscreva-se Agora

Faça como mais de 19 milhões de alunos e comece Data Transformation with Polars hoje mesmo!

Crie sua conta gratuita

ou

Ao continuar, você aceita nossos Termos de Uso, nossa Política de Privacidade e que seus dados serão armazenados nos EUA.

Desenvolva suas habilidades em dados com o app do DataCamp

Continue progredindo em qualquer lugar com nossos cursos para celular e desafios diários de programação de 5 minutos.