Parquet

Lesson in the Python for Data Analysis Roadmap · Stage 7: Reading Local Files

Last updated 14 September 2026

What is Parquet?

Parquet is a columnar file format optimized for analytical workloads. It stores data with type information, supports efficient compression, and reads much faster than CSV for large datasets. pd.read_parquet() requires the pyarrow or fastparquet library and is the preferred format for storing processed DataFrames on disk.

Study this in the interactive course See the whole Python for Data Analysis roadmap

Free resources to learn Parquet

Official docspandas.read_parquet
VideoReading Parquet Files in Python

Parquet: common questions

Can I learn Parquet in Hindi?

This lesson is written in English. Once you sign in, open it in the interactive course and ask the AI tutor to explain Parquet in Hindi or Hinglish. The tutor answers from this lesson’s own text, so it stays on the syllabus, and it runs on your own Google, OpenAI or Anthropic key.

Is this Parquet tutorial for beginners?

It is lesson 51 of 112 in the free Python for Data Analysis roadmap, in stage 7, Reading Local Files. If you are new to Python for Data Analysis, start from stage 1 and come back here in order; if you already know the earlier stages, this lesson stands on its own.