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Data Engineering with Polars in Python
Published 12/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 44m | Size:
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Transform and Manipulate Data

What you'll learn
Wrangle Data Like a Pro
Master the Basics of Polars
Perform Aggregation Functions on Tabular Data
Extract, Transform, and Manipulate Data
Requirements
No prior experience necessary
Description
Whether you're looking to launch a career in data engineering or aiming to enhance your existing data manipulation skills, this course offers a comprehensive toolkit for success in today's data-driven landscape. This course is meticulously crafted to provide you with an in-depth understanding of data engineering using Polars, a blazingly fast DataFrame library for Python that empowers you to handle large datasets effortlessly.
Data Extraction
Dive into the world of data by learning how to extract data from various sources, including databases, CSV files, and APIs. Discover the art of handling different data formats and structures, ensuring data integrity and completeness.
Data Transformation
Master the art of data transformation as you explore techniques to clean, reshape, and restructure raw data into a usable format. Learn to handle missing values, perform data imputation, and apply advanced transformation operations to make your data analysis-ready.
Data Analysis
Unleash the full potential of the Polars library as you delve into its powerful capabilities for data manipulation. From filtering and aggregating to joining and grouping, you'll learn how to perform complex operations with incredible speed and efficiency.
Real-World Scenarios
Make your learning experience applicable using real world scenarios that simulate the challenges data engineers face daily. We've carefully crafted our lectures to help you conquer essential data engineering tasks. You'll gain job ready skills and knowledge on how to address common data problems.
Who this course is for
Data Engineers looking to Expand Their Toolkit
Data Cleaning Professionals

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