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DataCamp

Data Transformation with Polars

via DataCamp

Overview

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

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.

Syllabus

  • 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.
  • 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.
  • 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.
  • Custom Transformations and Advanced Analytics
    • Learn how to build reusable custom expressions, categorize data using quantiles and fixed thresholds, and analyze rankings and correlations.

Taught by

Liam Brannigan

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