Cleanse and validate data with Python

There are many different Python libraries that make it much easier to clean and validate data. We will use these libraries in practical examples to recognise and clean up problems in the data.

Training objective

You will be able to check whether data is missing or contains outliers. You will also be able to check the similarity of texts and, more generally, find duplicates in your data. You can find a schema in your data and check future data against this schema. You can also check whether your data matches certain hypotheses. You can transform your data to make it more suitable for certain simulations. Finally, you will also be able to map satellite data to geo-locations.

Target group

Anyone who wants to cleanse or validate their data.

Course content

  • Day 1

    • Recognising and filtering missing data and outliers

    • Deduplicate similar data

    • Create data schemas

    • Schema validation of the data

  • Day 2

    • Checking dynamic data and hypotheses

    • Prepare data for simulations

    • Assign satellite data to geo-locations

What we offer

In our in-house and online seminars, we customise the content exactly to your needs. We coordinate the content with you in advance. We will be happy to provide you with a customised offer.

Your advantages:

Price:

from €1.920 (plus VAT)

Get in touch

Do you have a question that is not answered here? Veit will be happy to answer your questions and create a customised offer for your training.

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