data-dashboard

Introduction

data_dashboard library allows you to build HTML Dashboard visualizing not only the data and relationships between features but also automatically search for the best ‘baseline’ sklearn compatible Model.

_images/dashboard.gif

You can install data_dashboard with pip:

pip install data-dashboard

Note

Please keep in mind that package name is data-dashboard (with hyphen: ‘-‘) whereas module to import from is called data_dashboard (with underscore: ‘_’).

To create a Dashboard you need the data: X, y and the output_directory where the HTML files will be placed. You can use toy datasets from Examples (e.g. iris dataset) included in the library as well:

from data_dashboard import Dashboard
from data_dashboard.examples import iris
output_directory = "your_path/dashboard_output"
X, y, descriptions = iris()  # descriptions is additional argument described further in docs

dsh = Dashboard(X, y, output_directory, descriptions)
dsh.create_dashboard()

Note

Depending on the size of your data, fitting process might take some time. Please be patient!

Created HTML Dashboard will contain 3 subpages for you to investigate:

  • Overview with summary statistics of the data;

  • Features where you can dig deeper into each feature in the data;

  • Models showing search results and models performances.

Indices and tables