Name: PySpark Chained Conditions
Start: 2025-12-10T19:00:00-05:00
End: 2025-12-10T21:00:00-05:00
Location: Cowork Frederick

Join us for a **hands-on workshop** where we’ll break down **chained conditions in PySpark** — a powerful technique for writing clean, efficient, and flexible filters for complex datasets!

**What to Expect:**
✅ Learn how to build and combine conditional filters using PySpark’s expressive syntax
✅ Explore **real-world examples** from data cleaning, transformations, and analytics workflows
✅ Discover **best practices** for readable and scalable PySpark code
✅ Receive **take-home resources and code templates** to reinforce your learning

Whether you’re **just getting started** with PySpark or looking to **level up your data wrangling and transformation skills**, this session will give you the tools and confidence to tackle real-world data filtering tasks like a pro.

Mike

Statistical Seminars DC

Technology

Statistical Computing

Big Data

Machine Learning

Data Analytics

Data Visualization

Predictive Analytics

Job Search

R Project for Statistical Computing

Data Science

Applied Statistics

Career Network

Python

Professional Networking

Professional Development

Artificial Intelligence

Caleb

NIKHAR SHAH

Elvis Ilunga

Vivek

Rohit

Odysseas

Jerry Yang

PySpark Chained Conditions

Cowork Frederick

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Statistical Seminars DC

PySpark Chained Conditions

Statistical Seminars DC

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