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Using Pandas Dataframes in InfluxDB with Python

  • Meet the Developer Series

This page documents an earlier version of . is the latest stable version. View this page in the documentation.

A pandas dataframe might not be as cute and cuddly as a real panda, but for data scientists pandas dataframes are important data sources. Here, Zoe Steinkamp goes over some of the basics of using pandas dataframes with InfluxDB and the difference between pandas and Flux (InfluxDB’s native query and analytics language).

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The future of Flux

Flux is going into maintenance mode. You can continue using it as you currently are without any changes to your code.

Flux is going into maintenance mode and will not be supported in InfluxDB 3.0. This was a decision based on the broad demand for SQL and the continued growth and adoption of InfluxQL. We are continuing to support Flux for users in 1.x and 2.x so you can continue using it with no changes to your code. If you are interested in transitioning to InfluxDB 3.0 and want to future-proof your code, we suggest using InfluxQL.

For information about the future of Flux, see the following:

State of the InfluxDB Cloud Serverless documentation

InfluxDB Cloud Serverless documentation is a work in progress.

The new documentation for InfluxDB Cloud Serverless is a work in progress. We are adding new information and content almost daily. Thank you for your patience!

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