Skip to content

API for manipulating time series on top of Apache Spark: lagged time values, rolling statistics (mean, avg, sum, count, etc), AS OF joins, downsampling, and interpolation

License

Notifications You must be signed in to change notification settings

databrickslabs/tempo

Repository files navigation

tempo - Time Series Utilities for Data Teams Using Databricks

Project Description

The purpose of this project is to make time series manipulation with Spark simpler. Operations covered under this package include AS OF joins, rolling statistics with user-specified window lengths, featurization of time series using lagged values, and Delta Lake optimization on time and partition fields.

image codecov Downloads PyPI version docs

About

API for manipulating time series on top of Apache Spark: lagged time values, rolling statistics (mean, avg, sum, count, etc), AS OF joins, downsampling, and interpolation

Topics

Resources

License

Contributing

Stars

Watchers

Forks

Contributors 22