ixdat has a growing number of tutorials and examples available, addressing different steps in your ixdat workflow.

Browse the tutorials in the pages of the documentation here, or download the jupyter notebook files to try yourself.


Each technique comes with its own methods developed specifically for the types of data handling that are of interest. For example, the electrochemistry technique subclass comes with a subclass CyclicVoltammogram which allows you to select your data according to cycles, the mass spectrometry technique subclass comes with a method to calibrate the MS signals, and the spectroelectrochemistry technique subclass with a method to set a reference spectrum. The tutorials for the technique-specific methods are still work in progress - please, bear with us - you can find all the ones already available below.

As an open source project, ixdat is always happy to get contributions from the users, e.g. in form of new techniques.









Data organization

Data concepts


In ixdat your data is imported with a reader (specific to your data format) into a Measurement object and can then be plotted and/or exported into a format of your choice. You can figure out how in this tutorial:

Jupyter notebook file: https://github.com/ixdat/tutorials/blob/af1b38f2096555904786bb9fbbaf79bc209d4ef9/L1_basic_concepts/ixdat_intro_readers.ipynb



Jupyter notebook file: https://github.com/ixdat/tutorials/blob/af1b38f2096555904786bb9fbbaf79bc209d4ef9/L2_techniques/electrochemistry/ixdat_demo_cyclic_voltammetry.ipynb


Jupyter notebook file: https://github.com/ixdat/tutorials/blob/af1b38f2096555904786bb9fbbaf79bc209d4ef9/L2_techniques/ec_ms_quantification/ixdat_demo_EC-MS.ipynb


Jupyter notebook file: https://github.com/ixdat/tutorials/blob/af1b38f2096555904786bb9fbbaf79bc209d4ef9/L2_techniques/spectroelectrochemistry/ixdat_demo_spectroelectrochemistry.ipynb

Data concepts

While the existing technique subclasses allow for a wide range of general and technique specific data treatment, sometimes this is not enough for your individual needs. Luckily, ixdat also allows for direct data handling in array-type form. How to access data in this way is demonstrated in the tutorials on advanced data handling.

Jupyter notebook file: https://github.com/ixdat/tutorials/blob/af1b38f2096555904786bb9fbbaf79bc209d4ef9/L3_data_structure/ixdat_demo_manipulating_electrochemistry_data.ipynb

The jupyter notebooks

All tutorials linked to above are also hosted and version controlled in the ixdat Tutorials repository: https://github.com/ixdat/tutorials/

This repository is a bit of a mess at the moment, apologies, but the tutorials themselves are not bad, if we may say so ourselves. More are in progress.

Write your own tutorial!

Let the world know how to analyze data of your technique. We are very happy for pull requests to the tutorials repository! Please clear all output of your jupyter notebook when you make your pull request to that repository, as jupiter notebook output does not verson control well. Please also make it clear in first markdown cell where one can download the data needed to run it (link to another repository, dropbox folder, or zenodo DOI, for example). More details to come on the tutorials repo README.

Development scripts

For developers:

The basics of importing and plotting from each reader are demonstrated in the development_scripts/reader_demonstrators folder of the repository: https://github.com/ixdat/ixdat/tree/main/development_scripts/reader_demonstrators/