# Multivariate Time Series Analysis

**URL:** <https://community.drivendata.org/t/multivariate-time-series-analysis/1199>\
**Category:** DengAI Competition\
**Created:** [May 29, 2017, 7:45pm UTC](https://community.drivendata.org/t/multivariate-time-series-analysis/1199 "2017-05-29T19:45:11Z")\
**Posts on this page:** 3\
**Page:** 1

<div class="post-metadata">

**Author:** ![rchesak](https://avatars.discourse-cdn.com/v4/letter/r/ea666f/32.png) [@rchesak](https://community.drivendata.org/u/rchesak)\
**Post date:** [May 29, 2017, 7:45pm UTC](https://community.drivendata.org/t/multivariate-time-series-analysis/1199/1 "2017-05-29T19:45:11Z")

</div>

Has anyone come across any good resources for multivariate time series analysis (in Python) they would recommend?

---

<div class="post-metadata">

**Author:** ![isms](https://yyz2.discourse-cdn.com/flex028/user_avatar/community.drivendata.org/isms/32/9_2.png) [@isms](https://community.drivendata.org/u/isms)\
**Post date:** [May 30, 2017, 1:39pm UTC](https://community.drivendata.org/t/multivariate-time-series-analysis/1199/2 "2017-05-30T13:39:50Z")

</div>

Hey @rchesak, just recently heard about Facebook’s [Prophet](https://research.fb.com/prophet-forecasting-at-scale/) library which seems pretty cool. Would be really interested to know how it goes if you end up using it.

---

<div class="post-metadata">

**Author:** ![orenshap](https://avatars.discourse-cdn.com/v4/letter/o/3e96dc/32.png) [@orenshap](https://community.drivendata.org/u/orenshap)\
**Post date:** [October 12, 2019, 5:49pm UTC](https://community.drivendata.org/t/multivariate-time-series-analysis/1199/3 "2019-10-12T17:49:35Z")

</div>

You can try PyOD (python outlier detection)
