Python - Working with Paths (pathlib)
The pathlib module, introduced in Python 3.4, replaces string-based path manipulation with Path objects. This eliminates common errors from manual string concatenation and platform-specific…
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PySpark: Working with Nested JSON
If you’ve worked with data from REST APIs, MongoDB exports, or event logging systems, you’ve encountered deeply nested JSON. A single record might contain arrays of objects, objects within objects,…
Read more →Polars: Working with Large Datasets
Pandas has been the default choice for data manipulation in Python for over a decade. But if you’ve ever tried to process a 10GB CSV file on a laptop with 16GB of RAM, you know the pain. Pandas loads…
Read more →Pandas: Working with DateTime
Time-based data appears everywhere: server logs, financial transactions, sensor readings, user activity streams. Yet datetime handling remains one of the most frustrating aspects of data analysis….
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