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Pandas vs PySpark: What are the differences?
What is Pandas? High-performance, easy-to-use data structures and data analysis tools for the Python programming language. Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more.
What is PySpark? The Python API for Spark. It is the collaboration of Apache Spark and Python. it is a Python API for Spark that lets you harness the simplicity of Python and the power of Apache Spark in order to tame Big Data.
Pandas and PySpark can be categorized as "Data Science" tools.
Pandas is an open source tool with 20.7K GitHub stars and 8.16K GitHub forks. Here's a link to Pandas's open source repository on GitHub.
Instacart, Twilio SendGrid, and Sighten are some of the popular companies that use Pandas, whereas PySpark is used by Repro, Autolist, and Shuttl. Pandas has a broader approval, being mentioned in 110 company stacks & 341 developers stacks; compared to PySpark, which is listed in 8 company stacks and 6 developer stacks.
Pros of Pandas
- Easy data frame management21
- Extensive file format compatibility1