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diff --git a/collectors/python.d.plugin/pandas/README.md b/collectors/python.d.plugin/pandas/README.md index 14154947..19b11d5b 100644 --- a/collectors/python.d.plugin/pandas/README.md +++ b/collectors/python.d.plugin/pandas/README.md @@ -1,16 +1,15 @@ -<!-- -title: "Pandas" -custom_edit_url: https://github.com/netdata/netdata/edit/master/collectors/python.d.plugin/pandas/README.md ---> - -# Pandas Netdata Collector +# Ingest structured data (Pandas) <a href="https://pandas.pydata.org/" target="_blank"> <img src="https://pandas.pydata.org/docs/_static/pandas.svg" alt="Pandas" width="100px" height="50px" /> </a> -A python collector using [pandas](https://pandas.pydata.org/) to pull data and do pandas based -preprocessing before feeding to Netdata. +[Pandas](https://pandas.pydata.org/) is a de-facto standard in reading and processing most types of structured data in Python. +If you have metrics appearing in a CSV, JSON, XML, HTML, or [other supported format](https://pandas.pydata.org/docs/user_guide/io.html), +either locally or via some HTTP endpoint, you can easily ingest and present those metrics in Netdata, by leveraging the Pandas collector. + +The collector uses [pandas](https://pandas.pydata.org/) to pull data and do pandas-based +preprocessing, before feeding to Netdata. ## Requirements @@ -20,6 +19,12 @@ This collector depends on some Python (Python 3 only) packages that can usually sudo pip install pandas requests ``` +Note: If you would like to use [`pandas.read_sql`](https://pandas.pydata.org/docs/reference/api/pandas.read_sql.html) to query a database, you will need to install the below packages as well. + +```bash +sudo pip install 'sqlalchemy<2.0' psycopg2-binary +``` + ## Configuration Below is an example configuration to query some json weather data from [Open-Meteo](https://open-meteo.com), @@ -66,12 +71,11 @@ temperature: `chart_configs` is a list of dictionary objects where each one defines the sequence of `df_steps` to be run using [`pandas`](https://pandas.pydata.org/), and the `name`, `title` etc to define the -[CHART variables](https://learn.netdata.cloud/docs/agent/collectors/python.d.plugin#global-variables-order-and-chart) +[CHART variables](https://github.com/netdata/netdata/blob/master/docs/guides/python-collector.md#create-charts) that will control how the results will look in netdata. The example configuration above would result in a `data` dictionary like the below being collected by Netdata -at each time step. They keys in this dictionary will be the -[dimension](https://learn.netdata.cloud/docs/agent/web#dimensions) names on the chart. +at each time step. They keys in this dictionary will be the "dimensions" of the chart. ```javascript {'athens_max': 26.2, 'athens_mean': 19.45952380952381, 'athens_min': 12.2, 'berlin_max': 17.4, 'berlin_mean': 10.764285714285714, 'berlin_min': 5.7, 'dublin_max': 15.3, 'dublin_mean': 12.008928571428571, 'dublin_min': 6.6, 'london_max': 18.9, 'london_mean': 12.510714285714286, 'london_min': 5.2, 'paris_max': 19.4, 'paris_mean': 12.054166666666665, 'paris_min': 4.8} |