data preparation

In this topic I would like to show how to manage a dataset with many features (especially numeric data with completely unclear meaning and influence on whole dataset)

The dataset contains speech features and clinical variables from participants of a depression related study. Based on speech recordings, vocal features have been derived from different categories. Each feature contains a tag _{pos,neg}, which refers to the vocal task it was extracted from. Clinical and demographic variables of participants can be found at the beginning. The study was meant to show a relation between voice patterns and depression scale (variable ADS).

In this article I want to show some basic data preparation and analytics tasks. Also I want to shown Plotly library for data visualisation.

I have been looking for some datasets that I can easily manipulate to demonstrate the first pre-step of the Machine Learning - data preparation and cleaning. So I started to surf the Internet for datasets I can somehow explain and easily interpret based on my experience.