Python has become an essential tool for data scientists across the world.
To help you boost your efficiency doing data science, we’ve put together a list of the 10 most useful Python libraries for data scientists.
From speeding up your workflow with distributed computing to helping you perform feature engineering, these libraries will help streamline your workflow and turn you into an efficient data scientist.
Let’s dive in.
Here’s one for Machine Learning we recently published
10 Python Libraries for Machine Learning You Should Try Out
Elevate your machine learning game in 2023!
1. Fugue
Forget learning Spark or go to the documentation for Ray and Dask; with Fugue, you can just set engine = "Spark|Ray|Dask" and get access to distributed computing. With Fugue, you can port your code in Python, Pandas, and SQL to Spark, Dask, and Ray, minimizing the amount of code you have to write while making your code run efficiently.