# Using a Netdata Pandas Collector to Process Structured Data for Monitoring

DevFeed: [Using a Netdata Pandas Collector to Process Structured Data for Monitoring](<https://devfeed.tech/articles/using-pandas-in-python-data-analysis-performance-insights-45023.md>)

Original publisher: [Read original article](<https://www.netdata.cloud/blog/pandas-python/>)

Published: 2022-10-19T00:00:00Z

Content type: tutorial

Language: en

Sources: [Blog on Netdata](<https://devfeed.tech/sources/blog-on-netdata.md>)

Topics: [pandas](<https://devfeed.tech/topics/pandas.md>), [Python](<https://devfeed.tech/topics/python.md>), [Data analysis](<https://devfeed.tech/topics/data-analysis.md>), [Grafana](<https://devfeed.tech/topics/grafana.md>), [data-processing](<https://devfeed.tech/topics/data-processing.md>)

Tags: [analysis](<https://devfeed.tech/tags/analysis.md>), [data-analysis](<https://devfeed.tech/tags/data-analysis.md>), [http](<https://devfeed.tech/tags/http.md>), [json](<https://devfeed.tech/tags/json.md>), [metrics](<https://devfeed.tech/tags/metrics.md>), [monitoring](<https://devfeed.tech/tags/monitoring.md>), [pandas](<https://devfeed.tech/tags/pandas.md>), [python](<https://devfeed.tech/tags/python.md>)

## AI overview

This tutorial introduces Netdata's Pandas collector and demonstrates how to use it to retrieve structured data from an HTTP or API endpoint, process it with Pandas, and expose metrics for monitoring. The example uses weather forecasts from Open-Meteo and shows transformations that produce the collector's expected output.

## Source excerpt

Netdata just got a Pandas collector. Pandas is a de-facto standard in reading and processing most types of structured data in Python so if you have some csv/json/xml data, either locally or via some HTTP endpoint, containing metrics you'd like to monitor, chances are you can now easily do this by leveraging the Pandas collector without having to develop your own custom collector as you might have in the past.