This repository contains a set of tutorials prepared for helping readers get started analysing data using tools of the Python ecosystem.

Each tutorial is presented as an independent Python notebook: familiarity with Python is expected to follow them. We recommend to study the tutorials in the following order:

	Notebook	Google Colab	Binder
1.	NumPy
2.	pandas
3.	visualisation

You may also want to look at the exercises available in the exercises directory:

Notebook	Google Colab	Binder
exercise 2022
exercise 2021
exercise 2020
exercise 2019

To run the notebooks of this repository on your own computer, you need a working Python environment which includes:

• NumPy
• pandas
• matplotlib
• bokeh
• requests
• Jupyter

The notebooks were verified to work with Python v3.12 and should work with more recent versions. We strongly recommend to use the Anaconda distribution, which already includes all the packages needed to execute these notebooks.

To execute these notebooks in your own environment proceed as shown below:

$ git clone https://github.com/airnandez/numpandas.git
$ cd numpandas
$ jupyter lab

You will find the notebooks ready to run in the notebooks directory.

This material was developed and is maintained by Fabio Hernandez at IN2P3 / CNRS computing center (Lyon, France).

It was originally intended for students of the DU Data Scientist of the Université Clermont-Auvergne in France, but feel free to use it for other purposes as well.

Copyright 2019-2024 Fabio Hernandez

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.