Working with Different Files as Data Sources in Python | CodeSignal Learn

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Working with Different Files as Data Sources in Python

Data Science & Analytics

4 courses

69 practices

5 hours

Dive into the dynamic world of data with Python! This thrilling course empowers Data Engineers to master handling text, CSV, JSON, and large datasets, unleashing the power of efficient data manipulation, storage, and processing for cutting-edge applications.

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Verified skills you'll gain

DEVELOPING

Big Data Processing

INTERMEDIATE

Data Ingestion and Extraction

INTERMEDIATE

Programming and Algorithms

Tools you'll use

Python

Course 1

Fundamentals of Text Data Manipulation

4 lessons

19 practices

Explore the basics of text data manipulation. Learn techniques to read and write files efficiently, delving into line-by-line and character-by-character parsing to build a strong foundation in handling textual data using Python.

Course 2

Parsing Table Data

4 lessons

18 practices

Master parsing and writing techniques for scientific data using both TXT and CSV formats. This course provides practical skills for working with tabular data, ensuring you can manage various structured data files effectively.

Course 3

Hierarchical and Structured Data Formats

4 lessons

17 practices

Dive into JSON, XML, and scientific data storage. Discover how to parse, construct, and store structured data formats, leveraging Python's capabilities to manage complex datasets essential for data-driven applications.

Course 4

Large Data Handling Techniques

4 lessons

15 practices

Learn efficient techniques for managing large datasets. From compressed file management with `zipfile` and `tarfile`, to batch processing, this course equips you to handle data at scale.

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