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Exploratory data analysis in python

Exploratory data analysis in python

Learn how to apply exploratory data analysis models with python!

Tidspunkt

19.03.2019 kl. 12.30 - 20.03.2019 kl. 15.30

Beskrivelse

Building on a basic knowledge of python and statistics, this workshop series teaches you how to do exploratory data analysis with python in Jupyter Notebooks. The purpose of exploratory data analysis (EDA) is to apply an inductive approach to data and gain insights from data without necessarily working from a pre-defined hypothesis.

In this 2-day workshop we will briefly review the usage of Python Pandas package for tabular data (that has been in the focus of an earlier CALDISS workshop).

Day one will cover various ways to explore larger datasets with a time dimension as well as visualize some of the results. We will be working with the Dataset from Stanford’s Open Policing project: https://openpolicing.stanford.edu/.

Day two will go deeper, exploring unsupervised machine learning techniques (dimensionality reduction – PCA, NMF, T-SNE, UMAP and clustering – Kmeans, Hierarchical, (H)DBSCAN) for exploratory analysis.

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Times

  • 19/03-2019 12:30-15:30
  • 20/03-2019 12:30-15:30

Location

CALDISS – Fibigerstræde 5, room 37 – 9220 Aalborg Ø

Instructor

Assistant Professor Roman Jurowetski

Prerequisites

  • Basic python (see our introduction to python)
  • Statistics

Requirements

Own laptop or MacBook.

Participants

Students and staff associated with the Faculty of Social Sciences at AAU.