Nkululeko: how to visualize your data distribution

If you just want to see how your data distributes on the target with nkululeko, you can do a value_counts plot with the explore module

In your config, you would specify like this:

# all samples, or only test or train split?
sample_selection = all 
# activate the plot
value_counts = [['age'], ['gender'], ['duration'], ['duration', 'age']] 

and then, run this with the explore module:

python -m nkululeko.explore --config myconfig.ini

The results, for a data set with target=depression, looks similar to this for all samples:

and this for the speakers (if there is a speaker annotation)

If you prefer a kernel density estimation over a histogram, you can select this with

dist_type = kde

which would result for duration to:

Nkululeko distinguishes between categorical and continuous properties, this would be the output for gender

You can show the distribution of two sample properties at once, by using a scatter plot:

In addition, this module will automatically plot the distribution of samples per speaker, per gender (if annotated):

2 thoughts on “Nkululeko: how to visualize your data distribution”

  1. Load your data: Import your dataset into nkululeko. This can be done by reading your data from a file or connecting to a database.

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