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---
title: How to Version Your Data with pandas and Delta Lake
description: A walkthrough demonstrates versioning pandas datasets using Delta Lake's Python bindings (the deltalake package), which wraps the Rust-based delta-rs project...
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og:description: A walkthrough demonstrates versioning pandas datasets using Delta Lake's Python bindings (the deltalake package), which wraps the Rust-based delta-rs project...
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# How to Version Your Data with pandas and Delta Lake

**[Delta Lake Blog](https://daily.dev/sources/delta-lake)** · 5 min read · 0 upvotes · 0 comments

## Summary

A walkthrough demonstrates versioning pandas datasets using Delta Lake's Python bindings (the deltalake package), which wraps the Rust-based delta-rs project without requiring Spark. It covers installing deltalake and pandas, writing DataFrames to Delta tables, appending data, time-traveling between table versions, and how schema enforcement blocks appends with mismatched schemas. It also touches on interoperability with tools like Spark, Trino, Flink, and Kafka for building multi-technology ETL pipelines.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://delta.io/blog/2022-10-15-version-pandas-dataset>

## Questions this post answers

### How do I version a pandas dataset without using Spark?

Use the deltalake Python package, which wraps the Rust-based delta-rs project and has no Spark dependency (unlike delta-spark). Install it with pip install deltalake, write a pandas DataFrame to a Delta table, and Delta Lake automatically tracks versions in its transaction log, letting you append, overwrite, and time travel between versions.

_daily.dev surfaces practical guides like this for teams choosing lightweight data versioning tools._

### How do I read a previous version of a Delta Lake table with pandas?

Specify the version number when reading the Delta table; if you omit it, pandas reads the latest version by default. Delta Lake keeps all historical versions accessible even after overwrite operations, unlike plain CSV or Parquet data lakes where only the latest data is readable.

_Developers debugging data pipeline history can find pandas and Delta Lake walkthroughs on daily.dev._

### Does Delta Lake prevent schema mismatches when appending data with pandas?

Yes, Delta Lake enforces schema matching and throws an error if you try to append a DataFrame whose columns don't match the existing Delta table schema. This protects against corrupting the dataset, a risk that exists with CSV, Parquet, and JSON data lakes since they allow appends with any schema.

_daily.dev helps engineers comparing data lake formats keep up with schema enforcement techniques._

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---

Tags: [#python](https://daily.dev/tags/python), [#pandas](https://daily.dev/tags/pandas), [#etl](https://daily.dev/tags/etl)

[View this post on daily.dev](https://daily.dev/posts/how-to-version-your-data-with-pandas-and-delta-lake-rtyoavvyj)

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