Efficient Pandas: Using Chunksize for Large Data Sets

Author(s): Lawrence Alaso Krukrubo

Originally published on Towards AI.

Question One:

Data Science professionals often encounter very large data sets with hundreds of dimensions and millions of observations. There are multiple ways to handle large data sets. We all know about the distributed file systems like Hadoop and Spark for handling big data by parallelizing across multiple worker nodes in a cluster. But for this article, we shall use the pandas chunksize attribute or get_chunk() function.

Imagine for a second that you’re working on a new movie set and you’d like to know:-

1. What’s the most common movie rating from 0.5 to 5.0

2. What’s the average movie rating for most movies produced.

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To… Read the full blog for free on Medium.

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Published via Towards AI