Getting started with MeteoNet

1. Kaggle

You are new to MeteoNet? You can start by looking at the data on Kaggle where you will find notebooks to help you explore, cross-check all data types and predict time series! You can contribute to challenges and/or propose yours!

No need to install anything, you just have to create a Kaggle account and you can start playing with MeteoNet!

2. MeteoNet toolbox

You can also look at our sample notebooks on the GitHub Repository!

On this repository, you will find a toolbox including data samples from MeteoNet, the meteonet_toolbox python package with some useful tools and notebooks to help you explore and cross-check all data types.

The notebooks should help you open each data type (grid and point data, different resolutions...) and visualize them with maps and relief overlays.

The notebooks rely on the meteonet_toolbox package and we recommend that you install it. You just have to follow our install guide.

Once the installation is done, navigate inside the repository and run : jupyter notebook

Now, you should be able to open each notebook and explore the sample data!

3. Download

After checking the notebooks, you should have all you need to start playing around with the real dataset. You can download it here.

4. Slack workspace

If you have any question and/or suggestion (about the data, the toolbox, the use-cases, the kaggle page...), do not hesitate to go to our Slack workspace!